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 rospy
import actionlib
from operate_gripper_skill_msgs.msg import OperateGripperSkillAction, OperateGripperSkillResult, OperateGripperSkillFeedback
from ur_msgs.srv import SetIO, SetIORequest
class OperateGripperSkill(object):
def __init__(self, action_name='OperateGripperSkill'):
self.action_nam... | operate_gripper/operate_gripper_skill_server/src/operate_gripper_skill_class.py | import rospy
import actionlib
from operate_gripper_skill_msgs.msg import OperateGripperSkillAction, OperateGripperSkillResult, OperateGripperSkillFeedback
from ur_msgs.srv import SetIO, SetIORequest
class OperateGripperSkill(object):
def __init__(self, action_name='OperateGripperSkill'):
self.action_nam... | 0.349533 | 0.15772 |
from enum import Enum
import kgprim.ct.models as ctmodels
import kgprim.ct.repr.mxcommon as common
class CoordinatesConvention(Enum):
rotationOnTop = 0
translationOnTop = 1
class VectorType(Enum):
motion = 0
force = 1
block_bottom_left = (slice(3,6),slice(0,3))
block_bottom_right= (slice(3,6),slice... | src/kgprim/ct/repr/spatial.py | from enum import Enum
import kgprim.ct.models as ctmodels
import kgprim.ct.repr.mxcommon as common
class CoordinatesConvention(Enum):
rotationOnTop = 0
translationOnTop = 1
class VectorType(Enum):
motion = 0
force = 1
block_bottom_left = (slice(3,6),slice(0,3))
block_bottom_right= (slice(3,6),slice... | 0.809012 | 0.324356 |
import itertools
def child_generator(parent_selector,
reproduction_function,
development_function,
fitness_function):
while True:
children_genotypes = reproduction_function(parent_selector)
for child_genotype in children_genotypes:
... | vi-python/vi/ea/system.py | import itertools
def child_generator(parent_selector,
reproduction_function,
development_function,
fitness_function):
while True:
children_genotypes = reproduction_function(parent_selector)
for child_genotype in children_genotypes:
... | 0.466116 | 0.216612 |
from typing import TYPE_CHECKING
from grouper.constants import (
AUDIT_MANAGER,
PERMISSION_ADMIN,
PERMISSION_CREATE,
PERMISSION_GRANT,
USER_ADMIN,
)
from grouper.entities.pagination import ListPermissionsSortKey, Pagination
from grouper.entities.permission import PermissionAccess
from grouper.useca... | grouper/services/user.py | from typing import TYPE_CHECKING
from grouper.constants import (
AUDIT_MANAGER,
PERMISSION_ADMIN,
PERMISSION_CREATE,
PERMISSION_GRANT,
USER_ADMIN,
)
from grouper.entities.pagination import ListPermissionsSortKey, Pagination
from grouper.entities.permission import PermissionAccess
from grouper.useca... | 0.812347 | 0.117066 |
from . import DatabaseConnection as DB
from models.game.Board import Board
from weka.core.dataset import Instance, Instances, Attribute
import weka.core.converters as converters
# load weka dataset defns. These allow us to convert from numpy arrays to weka instances
categorical_dataset = converters.load_any_file("mo... | models/data/BoardDataModel.py | from . import DatabaseConnection as DB
from models.game.Board import Board
from weka.core.dataset import Instance, Instances, Attribute
import weka.core.converters as converters
# load weka dataset defns. These allow us to convert from numpy arrays to weka instances
categorical_dataset = converters.load_any_file("mo... | 0.666062 | 0.485722 |
import numpy as np
class validate_raw_data:
"""
Class Name: validate_raw_data
Description: Validates the prediction data.
On Failure: Raise Exception
Written By: <NAME>
... | Modules/RawDataValidation/validateRawPredictionData.py | import numpy as np
class validate_raw_data:
"""
Class Name: validate_raw_data
Description: Validates the prediction data.
On Failure: Raise Exception
Written By: <NAME>
... | 0.572125 | 0.381969 |
from pyomo.environ import *
model = m = ConcreteModel()
m.b1 = Var(within=Binary,bounds=(0,1),initialize=0)
m.b2 = Var(within=Binary,bounds=(0,1),initialize=1)
m.b3 = Var(within=Binary,bounds=(0,1),initialize=0)
m.b4 = Var(within=Binary,bounds=(0,1),initialize=0)
m.b5 = Var(within=Binary,bounds=(0,1),initialize=1)... | models_nonconvex_simple/ghg_1veh.py |
from pyomo.environ import *
model = m = ConcreteModel()
m.b1 = Var(within=Binary,bounds=(0,1),initialize=0)
m.b2 = Var(within=Binary,bounds=(0,1),initialize=1)
m.b3 = Var(within=Binary,bounds=(0,1),initialize=0)
m.b4 = Var(within=Binary,bounds=(0,1),initialize=0)
m.b5 = Var(within=Binary,bounds=(0,1),initialize=1)... | 0.373076 | 0.242957 |
import os
import torchvision
from tensorboardX import SummaryWriter
import numpy as np
from PIL import Image
# tensor to PIL Image
def tensor2img(img):
img = img[0].cpu().float().numpy()
if img.shape[0] == 1:
img = np.tile(img, (3, 1, 1))
img = (np.transpose(img, (1, 2, 0)) + 1) / 2.0 * 255.0
return img.as... | DRIT/src/saver.py | import os
import torchvision
from tensorboardX import SummaryWriter
import numpy as np
from PIL import Image
# tensor to PIL Image
def tensor2img(img):
img = img[0].cpu().float().numpy()
if img.shape[0] == 1:
img = np.tile(img, (3, 1, 1))
img = (np.transpose(img, (1, 2, 0)) + 1) / 2.0 * 255.0
return img.as... | 0.539469 | 0.193433 |
import os
import re
import shutil
from conans import ConanFile, CMake, tools
from fnmatch import fnmatch
class LibITKConan(ConanFile):
name = "itk"
upstream_version = "4.13"
upstream_patch = "2"
package_revision = "-r4"
version = "{0}.{1}{2}".format(upstream_version, upstream_patch, package_revis... | conanfile.py | import os
import re
import shutil
from conans import ConanFile, CMake, tools
from fnmatch import fnmatch
class LibITKConan(ConanFile):
name = "itk"
upstream_version = "4.13"
upstream_patch = "2"
package_revision = "-r4"
version = "{0}.{1}{2}".format(upstream_version, upstream_patch, package_revis... | 0.308607 | 0.095223 |
import os
from .clip import _download, available_models
_S3_BUCKET = 'https://clip-as-service.s3.us-east-2.amazonaws.com/models/onnx/'
_MODELS = {
'RN50': ('RN50/textual.onnx', 'RN50/visual.onnx'),
'RN101': ('RN101/textual.onnx', 'RN101/visual.onnx'),
'RN50x4': ('RN50x4/textual.onnx', 'RN50x4/visual.onnx'... | server/clip_server/model/clip_onnx.py | import os
from .clip import _download, available_models
_S3_BUCKET = 'https://clip-as-service.s3.us-east-2.amazonaws.com/models/onnx/'
_MODELS = {
'RN50': ('RN50/textual.onnx', 'RN50/visual.onnx'),
'RN101': ('RN101/textual.onnx', 'RN101/visual.onnx'),
'RN50x4': ('RN50x4/textual.onnx', 'RN50x4/visual.onnx'... | 0.424889 | 0.101991 |
from dis import dis
from keras.layers import Input, Reshape, Dropout, Dense, Flatten, BatchNormalization, Activation, ZeroPadding2D
from keras.layers.advanced_activations import LeakyReLU
from keras.layers.convolutional import UpSampling2D, Conv2D
from keras.models import Sequential, Model, load_model
from keras.optimi... | art_gan.py | from dis import dis
from keras.layers import Input, Reshape, Dropout, Dense, Flatten, BatchNormalization, Activation, ZeroPadding2D
from keras.layers.advanced_activations import LeakyReLU
from keras.layers.convolutional import UpSampling2D, Conv2D
from keras.models import Sequential, Model, load_model
from keras.optimi... | 0.911145 | 0.475423 |
import itertools
import codecs
import json
import numpy as np
import pandas as pd
import hunspell
data_hu = pd.read_json('hungarian.txt')
file = open('italian.txt', 'r')
data_it = []
for line in file:
data_it.append(json.loads(line))
data_it = pd.DataFrame(data_it)
# remove all breaklines
it_posts = data_it["te... | tcc/dumps.py |
import itertools
import codecs
import json
import numpy as np
import pandas as pd
import hunspell
data_hu = pd.read_json('hungarian.txt')
file = open('italian.txt', 'r')
data_it = []
for line in file:
data_it.append(json.loads(line))
data_it = pd.DataFrame(data_it)
# remove all breaklines
it_posts = data_it["te... | 0.124466 | 0.271306 |
from pybtex.database.input import bibtex
import bib2yml.libs.LatexAccents as TeXAccents
import argparse
import os
def YAMLprinter(inputFile,outputFile):
# Open BibTeX file
parser = bibtex.Parser()
# Initialize TeX Accent Converter
converter = TeXAccents.AccentConverter()
bibdata = parser.parse_fi... | bib2yml/__main__.py | from pybtex.database.input import bibtex
import bib2yml.libs.LatexAccents as TeXAccents
import argparse
import os
def YAMLprinter(inputFile,outputFile):
# Open BibTeX file
parser = bibtex.Parser()
# Initialize TeX Accent Converter
converter = TeXAccents.AccentConverter()
bibdata = parser.parse_fi... | 0.199776 | 0.144601 |
import logging
import os
import subprocess
import six
class ExecutableBase(object):
''' Base class for external programs '''
name = 'program_name'
standards_args = []
skip_stdout_lines = 0
_detected_path = None # automatically detected path to the program
def __init__(self, executabl... | utils/link/base.py | import logging
import os
import subprocess
import six
class ExecutableBase(object):
''' Base class for external programs '''
name = 'program_name'
standards_args = []
skip_stdout_lines = 0
_detected_path = None # automatically detected path to the program
def __init__(self, executabl... | 0.520009 | 0.128854 |
# ***********************IMPORTANT NMAP LICENSE TERMS************************
# * *
# * The Nmap Security Scanner is (C) 1996-2013 Insecure.Com LLC. Nmap is *
# * also a registered trademark of Insecure.Com LLC. This program is free *
# * sof... | src/GaIA/pkgs/nmap/nmap-6.40/zenmap/zenmapGUI/Icons.py |
# ***********************IMPORTANT NMAP LICENSE TERMS************************
# * *
# * The Nmap Security Scanner is (C) 1996-2013 Insecure.Com LLC. Nmap is *
# * also a registered trademark of Insecure.Com LLC. This program is free *
# * sof... | 0.53437 | 0.111822 |
import pytest
import mock
import responses
import drydock_provisioner.drydock_client.session as dc_session
import drydock_provisioner.drydock_client.client as dc_client
def test_blank_session_error():
with pytest.raises(Exception):
dc_session.DrydockSession()
def test_session_init_minimal():
port =... | tests/unit/test_drydock_client.py | import pytest
import mock
import responses
import drydock_provisioner.drydock_client.session as dc_session
import drydock_provisioner.drydock_client.client as dc_client
def test_blank_session_error():
with pytest.raises(Exception):
dc_session.DrydockSession()
def test_session_init_minimal():
port =... | 0.584745 | 0.236842 |
from __future__ import absolute_import
import pandas as pd
from carto.exceptions import CartoException, CartoRateLimitException
from tqdm import tqdm
from ....utils.columns import DataframeColumnsInfo, _first_value
from ....utils.geom_utils import (compute_geodataframe, decode_geometry,
... | cartoframes/data/dataset/registry/dataframe_dataset.py | from __future__ import absolute_import
import pandas as pd
from carto.exceptions import CartoException, CartoRateLimitException
from tqdm import tqdm
from ....utils.columns import DataframeColumnsInfo, _first_value
from ....utils.geom_utils import (compute_geodataframe, decode_geometry,
... | 0.749821 | 0.359617 |
from PIL import Image
import unittest as ut
import numpy as np
from reso.palette import pR, pY, pG, pC, pB, pM
from reso.palette import pr, py, pg, pc, pb, pm
from reso.palette import pO, pL, pT, pS, pP, pV
from reso.palette import po, pl, pt, ps, pp, pv
from reso.palette import get, resel_to_rgb, rgb_to_resel
from re... | tests/tests.py | from PIL import Image
import unittest as ut
import numpy as np
from reso.palette import pR, pY, pG, pC, pB, pM
from reso.palette import pr, py, pg, pc, pb, pm
from reso.palette import pO, pL, pT, pS, pP, pV
from reso.palette import po, pl, pt, ps, pp, pv
from reso.palette import get, resel_to_rgb, rgb_to_resel
from re... | 0.284179 | 0.49939 |
import json
import re
from django.db.models import Q
"""Search Syntax Quick Guide
A search string is made up of one or more EXPRESSIONS which are joined by
OPERATORS.
- An expression is a string of non-whitespace unicode characters which may or
may not be enclosed by quotation marks.
- An expression enclosed... | lw2/search.py | import json
import re
from django.db.models import Q
"""Search Syntax Quick Guide
A search string is made up of one or more EXPRESSIONS which are joined by
OPERATORS.
- An expression is a string of non-whitespace unicode characters which may or
may not be enclosed by quotation marks.
- An expression enclosed... | 0.512205 | 0.527499 |
import numpy as np
# ============================================================================
# 5. 相対湿度
# ============================================================================
def get_h(Theta):
"""(1)
Args:
Theta: 空気温度（℃）
Returns:
相対湿度（%）
"""
P_v = get_P_v()
P_vs = ... | src/pyhees/section11_5.py |
import numpy as np
# ============================================================================
# 5. 相対湿度
# ============================================================================
def get_h(Theta):
"""(1)
Args:
Theta: 空気温度（℃）
Returns:
相対湿度（%）
"""
P_v = get_P_v()
P_vs = ... | 0.680666 | 0.471345 |
import urllib
import urllib2
import re
from pyquery import PyQuery as pq
from lxml import etree
import os
import string
import StringIO
username=""
password=""
host="http://172.16.17.32/"
session=""
name=""
classlist={}
classres=""
onhook=0
gnmkdm=""
aspxsession=""
loginpage="default5.aspx"
#urllib函数，用于提交http数据
def ope... | xuanke.py | import urllib
import urllib2
import re
from pyquery import PyQuery as pq
from lxml import etree
import os
import string
import StringIO
username=""
password=""
host="http://172.16.17.32/"
session=""
name=""
classlist={}
classres=""
onhook=0
gnmkdm=""
aspxsession=""
loginpage="default5.aspx"
#urllib函数，用于提交http数据
def ope... | 0.058973 | 0.087058 |
from zipfile import ZipFile
import numpy as np
import pyarmnn as ann
import example_utils as eu
import os
def unzip_file(filename):
"""Unzips a file to its current location.
Args:
filename (str): Name of the archive.
Returns:
str: Directory path of the extracted files.
"""
with ... | python/pyarmnn/examples/tflite_mobilenetv1_quantized.py |
from zipfile import ZipFile
import numpy as np
import pyarmnn as ann
import example_utils as eu
import os
def unzip_file(filename):
"""Unzips a file to its current location.
Args:
filename (str): Name of the archive.
Returns:
str: Directory path of the extracted files.
"""
with ... | 0.723602 | 0.337586 |
import argparse
from typing import List
from protobufs.institution.coldwallet_pb2 import DESCRIPTOR
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
from coldwallet.servicer import ColdWalletServicer
from coldwallet.sql.base import Base
from coldwallet.utils.cm_scoped_session_factory impor... | coldwallet/coldwallet/coldwallet.py | import argparse
from typing import List
from protobufs.institution.coldwallet_pb2 import DESCRIPTOR
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
from coldwallet.servicer import ColdWalletServicer
from coldwallet.sql.base import Base
from coldwallet.utils.cm_scoped_session_factory impor... | 0.541409 | 0.157169 |
from __future__ import absolute_import
from __future__ import print_function
import contextlib
import os
import re
import shutil
import subprocess
import sys
import tempfile
import merge_requirements as merge_module
import readlink
# Once this code doesn't need to support Python 2, we can simply use
# tempfile.Tem... | tools/pip_install.py |
from __future__ import absolute_import
from __future__ import print_function
import contextlib
import os
import re
import shutil
import subprocess
import sys
import tempfile
import merge_requirements as merge_module
import readlink
# Once this code doesn't need to support Python 2, we can simply use
# tempfile.Tem... | 0.433262 | 0.096791 |
# # # Identifying various features of customer Churn with XGBoost (Extreme Gradient Boosting)
# XGBoost is an optimized distributed gradient boosting library designed to be highly efficient, flexible and portable. It implements machine learning algorithms under the Gradient Boosting framework.
# In[101]:
import nump... | XGBoost-Churn-Analysis.py |
# # # Identifying various features of customer Churn with XGBoost (Extreme Gradient Boosting)
# XGBoost is an optimized distributed gradient boosting library designed to be highly efficient, flexible and portable. It implements machine learning algorithms under the Gradient Boosting framework.
# In[101]:
import nump... | 0.416797 | 0.618694 |
import random
import sys
import time
class Solution:
def merge_sort_rec(self, arr):
left_len = len(arr) // 2
right_len = len(arr) - left_len
self.merge_rec(arr, 0, left_len, right_len)
return arr
def merge_rec(self, arr, left, left_len, right_len):
if le... | Practice/Sort/MergeSort.py | import random
import sys
import time
class Solution:
def merge_sort_rec(self, arr):
left_len = len(arr) // 2
right_len = len(arr) - left_len
self.merge_rec(arr, 0, left_len, right_len)
return arr
def merge_rec(self, arr, left, left_len, right_len):
if le... | 0.182171 | 0.309924 |
from markov_engine import MarkovTrieDb, MarkovFilters, MarkovGenerator
from models.structure import StructureModelScheduler
from common.nlp import CapitalizationMode
from typing import Optional, List
from multiprocessing import Process, Queue, Event
from threading import Thread
from queue import Empty
from spacy.tokens... | connectors/connector_common.py | from markov_engine import MarkovTrieDb, MarkovFilters, MarkovGenerator
from models.structure import StructureModelScheduler
from common.nlp import CapitalizationMode
from typing import Optional, List
from multiprocessing import Process, Queue, Event
from threading import Thread
from queue import Empty
from spacy.tokens... | 0.773216 | 0.140602 |
import re
import traverseService as rst
"""
Power.1.1.1.Power , Power.v1_0_0.Power
"""
versionpattern = 'v[0-9]_[0-9]_[0-9]'
def compareRedfishURI(expected_uris, uri, my_id):
if expected_uris is not None:
regex = re.compile(r"{.*?}")
for e in expected_uris:
e_left, e_right = tuple(... | commonRedfish.py |
import re
import traverseService as rst
"""
Power.1.1.1.Power , Power.v1_0_0.Power
"""
versionpattern = 'v[0-9]_[0-9]_[0-9]'
def compareRedfishURI(expected_uris, uri, my_id):
if expected_uris is not None:
regex = re.compile(r"{.*?}")
for e in expected_uris:
e_left, e_right = tuple(... | 0.679285 | 0.263217 |
import csv
import pathlib
import datetime as dt
from pymms.sdc import selections as sel
# NOTES:
# - sdc.sitl_selections filters files the same way that the science files
# are filtered. The file with the time stamp just prior to the requested
# interval start time is kept, all previous are discarded. This is o... | bin/write_burst_selections.py | import csv
import pathlib
import datetime as dt
from pymms.sdc import selections as sel
# NOTES:
# - sdc.sitl_selections filters files the same way that the science files
# are filtered. The file with the time stamp just prior to the requested
# interval start time is kept, all previous are discarded. This is o... | 0.59561 | 0.397617 |
from datetime import timedelta
import logging
from homeassistant.core import callback
from homeassistant.helpers.dispatcher import async_dispatcher_connect
from homeassistant.helpers.entity import Entity
from .const import DATA_UPDATED, DOMAIN
_LOGGER = logging.getLogger(__name__)
SCAN_INTERVAL = timedelta(seconds=... | custom_components/kraken/sensor.py | from datetime import timedelta
import logging
from homeassistant.core import callback
from homeassistant.helpers.dispatcher import async_dispatcher_connect
from homeassistant.helpers.entity import Entity
from .const import DATA_UPDATED, DOMAIN
_LOGGER = logging.getLogger(__name__)
SCAN_INTERVAL = timedelta(seconds=... | 0.86094 | 0.130562 |
import numpy as np
from src.continuous.normal import NormalDist
from src.continuous.uniform import UniformDist
from src.prob_distribution import ProbDist
from src.spaces.spaces1d_leafs import ContinuousSpace
class WaldDist(ProbDist):
"""Simple Wald distribution."""
def __init__(self, loc = 0, scale = 1):
... | src/continuous/wald.py | import numpy as np
from src.continuous.normal import NormalDist
from src.continuous.uniform import UniformDist
from src.prob_distribution import ProbDist
from src.spaces.spaces1d_leafs import ContinuousSpace
class WaldDist(ProbDist):
"""Simple Wald distribution."""
def __init__(self, loc = 0, scale = 1):
... | 0.936409 | 0.587352 |
from random import randint
from time import time
from pygame.math import Vector2
from entities.base_entity import State
from entities.bullet.entity import Bullet
class SurvivorStateExploring(State):
""" Exploring is the default survivor state when the entity
wanders around looking for supplies """
... | entities/survivor/states.py | from random import randint
from time import time
from pygame.math import Vector2
from entities.base_entity import State
from entities.bullet.entity import Bullet
class SurvivorStateExploring(State):
""" Exploring is the default survivor state when the entity
wanders around looking for supplies """
... | 0.617859 | 0.385722 |
import sys
from utilz import utils_capture
import threading
from time import time, sleep
from agents import sis
from app import client
import os
import config
config = config.Config()
cwd = os.getcwd()
recording_folder = cwd+'/datasets/recording/'
test_folder = recording_folder+'/test/'
train_folder = recording_folder... | __main__.py | import sys
from utilz import utils_capture
import threading
from time import time, sleep
from agents import sis
from app import client
import os
import config
config = config.Config()
cwd = os.getcwd()
recording_folder = cwd+'/datasets/recording/'
test_folder = recording_folder+'/test/'
train_folder = recording_folder... | 0.315525 | 0.113949 |
import re
from collections import namedtuple
from delphin.mrs.components import Lnk
_yy_token = namedtuple(
'YyToken',
(
'id', # token identifier
'start', # start vertex
'end', # end vertex
'lnk', # <from:to> charspan (optional)
'paths', # path mem... | delphin/tokens.py | import re
from collections import namedtuple
from delphin.mrs.components import Lnk
_yy_token = namedtuple(
'YyToken',
(
'id', # token identifier
'start', # start vertex
'end', # end vertex
'lnk', # <from:to> charspan (optional)
'paths', # path mem... | 0.689933 | 0.272805 |
import numpy as np
import theano.tensor as T
import lasagne
def flatten_spatial(x, axis=1):
other_dims = list(range(axis)) + list(range(axis + 1, x.ndim))
axis_at_back = other_dims + [axis]
x_reordered = x.transpose(*axis_at_back)
return x_reordered.reshape((-1, x.shape[axis])), x_reordered.shape
def... | britefury_lasagne/util.py | import numpy as np
import theano.tensor as T
import lasagne
def flatten_spatial(x, axis=1):
other_dims = list(range(axis)) + list(range(axis + 1, x.ndim))
axis_at_back = other_dims + [axis]
x_reordered = x.transpose(*axis_at_back)
return x_reordered.reshape((-1, x.shape[axis])), x_reordered.shape
def... | 0.67971 | 0.512205 |
from ...managers import get_python_manager
from . import _get_opposite_operator
class MetaField:
def __init__(self, name, index=None, meta_condition=None, meNode=None, t=None, reMetaNode=None):
if (meta_condition is not None) and (meNode is not None):
raise ValueError("you cannot mix condition... | gmql/dataset/DataStructures/MetaField.py | from ...managers import get_python_manager
from . import _get_opposite_operator
class MetaField:
def __init__(self, name, index=None, meta_condition=None, meNode=None, t=None, reMetaNode=None):
if (meta_condition is not None) and (meNode is not None):
raise ValueError("you cannot mix condition... | 0.707708 | 0.093761 |
from __future__ import absolute_import
import sys
import os
import re
# python 2 and python 3 compatibility library
from six import iteritems
from ..configuration import Configuration
from ..api_client import ApiClient
class V1topologiesApi(object):
"""
NOTE: This class is auto generated by the swagger cod... | whoville/cloudbreak/apis/v1topologies_api.py | from __future__ import absolute_import
import sys
import os
import re
# python 2 and python 3 compatibility library
from six import iteritems
from ..configuration import Configuration
from ..api_client import ApiClient
class V1topologiesApi(object):
"""
NOTE: This class is auto generated by the swagger cod... | 0.630457 | 0.061904 |
import argparse
import configparser
import numpy as np
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
plt.rcParams.update({'font.size': 18})
import seaborn as sns
import datasets
import models
import functions
from visualization import visualize_2d
import sys
sys.path.append('..')
from evalua... | synthetic/run_experiment.py | import argparse
import configparser
import numpy as np
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
plt.rcParams.update({'font.size': 18})
import seaborn as sns
import datasets
import models
import functions
from visualization import visualize_2d
import sys
sys.path.append('..')
from evalua... | 0.421552 | 0.181535 |
import numpy as np
import matplotlib.pyplot as plt
from livapordata.vaporpressure import press_Browning_and_Potter
from livapordata.utility import error_bands
from livapordata.transport import *
plt.style.use('seaborn-colorblind')
fig = plt.figure(figsize=(6, 4))
ax = fig.add_subplot(1, 1, 1)
colors = []
for i in ra... | examples/plot_literature_viscosities.py | import numpy as np
import matplotlib.pyplot as plt
from livapordata.vaporpressure import press_Browning_and_Potter
from livapordata.utility import error_bands
from livapordata.transport import *
plt.style.use('seaborn-colorblind')
fig = plt.figure(figsize=(6, 4))
ax = fig.add_subplot(1, 1, 1)
colors = []
for i in ra... | 0.532911 | 0.619443 |
import numpy as np
import matplotlib.pyplot as plt
import h5py as h5
from scipy.optimize import curve_fit
import scipy.constants as sc
import os
from scipy.integrate import simps
def gauss(x, a, x0, sigma, offset):
return a*np.exp(-(x-x0)**2/(2*sigma**2))+offset
def getData(fileName, sensorName):
"""
Read... | loadData.py | import numpy as np
import matplotlib.pyplot as plt
import h5py as h5
from scipy.optimize import curve_fit
import scipy.constants as sc
import os
from scipy.integrate import simps
def gauss(x, a, x0, sigma, offset):
return a*np.exp(-(x-x0)**2/(2*sigma**2))+offset
def getData(fileName, sensorName):
"""
Read... | 0.699254 | 0.633155 |
import numpy as np
import matplotlib.pyplot as plt
from cosmoTransitions import pathDeformation as pd
class Potential:
"""
A sample potential. The depth of the absolute minimum is controlled with
the parameters `fx` and `fy`.
This potential has no physical significance whatsoever.
"""
def __... | examples/fullTunneling.py | import numpy as np
import matplotlib.pyplot as plt
from cosmoTransitions import pathDeformation as pd
class Potential:
"""
A sample potential. The depth of the absolute minimum is controlled with
the parameters `fx` and `fy`.
This potential has no physical significance whatsoever.
"""
def __... | 0.796134 | 0.715617 |
from dataclasses import dataclass
import ipywidgets as ipyw
import pandas as pd
import traitlets as trt
@dataclass
class RegressionConfiguration:
dataframe: pd.DataFrame
inputs: list
target: str
validation_feature: str
validation_value: trt.Any()
@dataclass
class TrainedModel:
... | src/ipyml/utils.py | from dataclasses import dataclass
import ipywidgets as ipyw
import pandas as pd
import traitlets as trt
@dataclass
class RegressionConfiguration:
dataframe: pd.DataFrame
inputs: list
target: str
validation_feature: str
validation_value: trt.Any()
@dataclass
class TrainedModel:
... | 0.566978 | 0.19923 |
import pytest
import numpy as np
from numpy.testing import assert_almost_equal, assert_warns, assert_raises
from ...sims import linear
from .. import RV
class TestRVStat:
@pytest.mark.parametrize("n", [10, 100, 1000])
@pytest.mark.parametrize("obs_stat", [1.0])
@pytest.mark.parametrize("obs_pvalue", [1 /... | hyppo/independence/tests/test_rvcorr.py | import pytest
import numpy as np
from numpy.testing import assert_almost_equal, assert_warns, assert_raises
from ...sims import linear
from .. import RV
class TestRVStat:
@pytest.mark.parametrize("n", [10, 100, 1000])
@pytest.mark.parametrize("obs_stat", [1.0])
@pytest.mark.parametrize("obs_pvalue", [1 /... | 0.768733 | 0.788827 |
import logging
import numbers
from collections.abc import Iterable
import numpy as np
import pandas as pd
from sklearn.model_selection import BaseCrossValidator
from sklearn.utils import indexable
from ..utils.validation import _num_samples
logger = logging.getLogger(__name__)
__all__ = ["PurgedKFold", "check_cv"]
... | src/nntm/model_selection/_split.py |
import logging
import numbers
from collections.abc import Iterable
import numpy as np
import pandas as pd
from sklearn.model_selection import BaseCrossValidator
from sklearn.utils import indexable
from ..utils.validation import _num_samples
logger = logging.getLogger(__name__)
__all__ = ["PurgedKFold", "check_cv"]
... | 0.887558 | 0.473353 |
import os
from DINGO.base import (DINGOFlow, DINGONode)
from DINGO.interfaces.dsistudio import (DSIStudioSource,
DSIStudioReconstruct,
DSIStudioTrack,
DSIStudioAnalysis,
... | DINGO/workflows/dsistudio.py | import os
from DINGO.base import (DINGOFlow, DINGONode)
from DINGO.interfaces.dsistudio import (DSIStudioSource,
DSIStudioReconstruct,
DSIStudioTrack,
DSIStudioAnalysis,
... | 0.594551 | 0.15444 |
from ..context import Context, Result, Token
from . import Parser
from .combinators import DelegateParser
from typing import Callable, Generic, List, TypeVar
T = TypeVar('T', covariant=True)
R = TypeVar('R', covariant=True)
class ActionParser(DelegateParser[R], Generic[T, R]):
__slots__ = '_function', '_has_sid... | petitparser/parser/actions.py | from ..context import Context, Result, Token
from . import Parser
from .combinators import DelegateParser
from typing import Callable, Generic, List, TypeVar
T = TypeVar('T', covariant=True)
R = TypeVar('R', covariant=True)
class ActionParser(DelegateParser[R], Generic[T, R]):
__slots__ = '_function', '_has_sid... | 0.85753 | 0.305322 |
import os
import sys
import json
import logging
import argparse
import uuid
import time
from shutil import copyfile
import shure
import offline
import tornado_server
APPNAME = 'micboard'
CONFIG_FILE_NAME = 'config.json'
FORMAT = '%(asctime)s %(levelname)s:%(message)s'
config_tree = {}
gif_dir = ''
group_update_l... | py/config.py | import os
import sys
import json
import logging
import argparse
import uuid
import time
from shutil import copyfile
import shure
import offline
import tornado_server
APPNAME = 'micboard'
CONFIG_FILE_NAME = 'config.json'
FORMAT = '%(asctime)s %(levelname)s:%(message)s'
config_tree = {}
gif_dir = ''
group_update_l... | 0.163713 | 0.041521 |
import pkg_resources
from kinto.events import ServerFlushed
from kinto.core.events import AfterResourceChanged
from . import indexer
from . import listener
#: Module version, as defined in PEP-0396.
__version__ = pkg_resources.get_distribution(__package__).version
def includeme(config):
# Register a global in... | kinto_elasticsearch/__init__.py | import pkg_resources
from kinto.events import ServerFlushed
from kinto.core.events import AfterResourceChanged
from . import indexer
from . import listener
#: Module version, as defined in PEP-0396.
__version__ = pkg_resources.get_distribution(__package__).version
def includeme(config):
# Register a global in... | 0.358129 | 0.075142 |
from dfcompare import BufferedIterator, compare, Identical, Different, Unmatched
import pandas as pd
import unittest
class TestBufferedIterator(unittest.TestCase):
def test_head(self):
it = BufferedIterator(iter([1, 2, 3]))
self.assertEqual(it.head(), 1)
self.assertEqual(next(it), 1)
... | test_dfcompare.py | from dfcompare import BufferedIterator, compare, Identical, Different, Unmatched
import pandas as pd
import unittest
class TestBufferedIterator(unittest.TestCase):
def test_head(self):
it = BufferedIterator(iter([1, 2, 3]))
self.assertEqual(it.head(), 1)
self.assertEqual(next(it), 1)
... | 0.590071 | 0.769535 |
from apitools.base.py import encoding
from googlecloudsdk.api_lib.compute import base_classes
from googlecloudsdk.calliope import base
from googlecloudsdk.calliope import exceptions
from googlecloudsdk.command_lib.compute.instances import flags
from googlecloudsdk.core import log
class SetDiskAutoDelete(base.UpdateC... | google-cloud-sdk/lib/surface/compute/instances/set_disk_auto_delete.py | from apitools.base.py import encoding
from googlecloudsdk.api_lib.compute import base_classes
from googlecloudsdk.calliope import base
from googlecloudsdk.calliope import exceptions
from googlecloudsdk.command_lib.compute.instances import flags
from googlecloudsdk.core import log
class SetDiskAutoDelete(base.UpdateC... | 0.582729 | 0.094678 |
"""Tests for the ClientSocket class."""
import unittest
from ibapipy.core.client_socket import ClientSocket
from multiprocessing import Queue
TEST_ACCOUNT_NAME = 'DU109588'
class ClientSocketTests(unittest.TestCase):
"""Test cases for the ClientSocket class."""
def test_constructor(self):
client = ... | client_socket_tests.py | """Tests for the ClientSocket class."""
import unittest
from ibapipy.core.client_socket import ClientSocket
from multiprocessing import Queue
TEST_ACCOUNT_NAME = 'DU109588'
class ClientSocketTests(unittest.TestCase):
"""Test cases for the ClientSocket class."""
def test_constructor(self):
client = ... | 0.75037 | 0.316739 |
class Solution:
def length_of_longest_substring_1(self, s: str) -> int:
"""
time complexity: O(N^2)
space complexity: O(N)
"""
n = len(s)
store = {}
max_len = 0
for i in range(n):
if n - i <= max_len:
break
cur_l... | python-algorithm/leetcode/problem_3.py | class Solution:
def length_of_longest_substring_1(self, s: str) -> int:
"""
time complexity: O(N^2)
space complexity: O(N)
"""
n = len(s)
store = {}
max_len = 0
for i in range(n):
if n - i <= max_len:
break
cur_l... | 0.578091 | 0.345768 |
import torch
class PostNet(torch.nn.Module):
"""
From Tacotron2
Postnet module for Spectrogram prediction network.
This is a module of Postnet in Spectrogram prediction network,
which described in `Natural TTS Synthesis by
Conditioning WaveNet on Mel Spectrogram Predictions`_.
The Postne... | Layers/PostNet.py | import torch
class PostNet(torch.nn.Module):
"""
From Tacotron2
Postnet module for Spectrogram prediction network.
This is a module of Postnet in Spectrogram prediction network,
which described in `Natural TTS Synthesis by
Conditioning WaveNet on Mel Spectrogram Predictions`_.
The Postne... | 0.945096 | 0.648689 |
import numpy as np
import theano
import theano.tensor as T
from theano.tensor.nnet import conv2d
from theano.tensor.signal import downsample
from theano.sandbox.rng_mrg import MRG_RandomStreams as RandomStreams
import sys
import glob
import matplotlib.pyplot as plt
from sklearn.cross_validation import train_test_split
... | theano/production_model.py | import numpy as np
import theano
import theano.tensor as T
from theano.tensor.nnet import conv2d
from theano.tensor.signal import downsample
from theano.sandbox.rng_mrg import MRG_RandomStreams as RandomStreams
import sys
import glob
import matplotlib.pyplot as plt
from sklearn.cross_validation import train_test_split
... | 0.387459 | 0.277319 |
import io
import os
import time
import json
import hashlib
import requests
class Vault8():
"""
Vault8 class implementation
"""
def __init__(self, public_key: str, secret_key: str, service_url: str):
self._public_key = public_key
self._secret_key = secret_key
self._service_url = ... | vault8/__init__.py | import io
import os
import time
import json
import hashlib
import requests
class Vault8():
"""
Vault8 class implementation
"""
def __init__(self, public_key: str, secret_key: str, service_url: str):
self._public_key = public_key
self._secret_key = secret_key
self._service_url = ... | 0.553747 | 0.141133 |
import pytest
from tsfeast.funcs import *
class TestGetBusdaysInMonth:
def test_dt_monthbegin(self):
actual = get_busdays_in_month(pd.to_datetime('2020-01-01'))
expected = 21
assert actual == expected
def test_dt_monthend(self):
actual = get_busdays_in_month(pd.to_datetime('2... | tests/test_funcs.py | import pytest
from tsfeast.funcs import *
class TestGetBusdaysInMonth:
def test_dt_monthbegin(self):
actual = get_busdays_in_month(pd.to_datetime('2020-01-01'))
expected = 21
assert actual == expected
def test_dt_monthend(self):
actual = get_busdays_in_month(pd.to_datetime('2... | 0.642657 | 0.678852 |
# template file: justice_py_sdk_codegen/__main__.py
# justice-platform-service (4.10.0)
# pylint: disable=duplicate-code
# pylint: disable=line-too-long
# pylint: disable=missing-function-docstring
# pylint: disable=missing-module-docstring
# pylint: disable=too-many-arguments
# pylint: disable=too-many-branches
# p... | accelbyte_py_sdk/api/platform/models/currency_create.py |
# template file: justice_py_sdk_codegen/__main__.py
# justice-platform-service (4.10.0)
# pylint: disable=duplicate-code
# pylint: disable=line-too-long
# pylint: disable=missing-function-docstring
# pylint: disable=missing-module-docstring
# pylint: disable=too-many-arguments
# pylint: disable=too-many-branches
# p... | 0.7586 | 0.146301 |
from typing import Any, ClassVar, Dict, List, Optional, Tuple, Type, Union, TYPE_CHECKING
from ..config import Config
from .irbasemapping import IRBaseMapping
from .irhttpmapping import IRHTTPMapping
from .irtcpmapping import IRTCPMapping
if TYPE_CHECKING:
from .ir import IR
def unique_mapping_name(aconf: Conf... | python/ambassador/ir/irmappingfactory.py | from typing import Any, ClassVar, Dict, List, Optional, Tuple, Type, Union, TYPE_CHECKING
from ..config import Config
from .irbasemapping import IRBaseMapping
from .irhttpmapping import IRHTTPMapping
from .irtcpmapping import IRTCPMapping
if TYPE_CHECKING:
from .ir import IR
def unique_mapping_name(aconf: Conf... | 0.812644 | 0.204521 |
from pathlib import Path
import json
import re
# We don't want a bunch of `fixme` warnings for this script.
# pylint: disable=fixme
def parse_part(part):
"""Converts KiCad's string representation of a part to a dict."""
if not '\nF ' in part:
return None
lines = part.split('\n')
name = None... | bin/kicad_import.py | from pathlib import Path
import json
import re
# We don't want a bunch of `fixme` warnings for this script.
# pylint: disable=fixme
def parse_part(part):
"""Converts KiCad's string representation of a part to a dict."""
if not '\nF ' in part:
return None
lines = part.split('\n')
name = None... | 0.701304 | 0.210644 |
# ROSITA
# Licensed under The Apache License 2.0 [see LICENSE for details]
# Written by <NAME> and <NAME>
# --------------------------------------------------------
import numpy as np
import json, re, torch, logging, collections, copy, os, base64
import torch.utils.data as Data
from utils.tokenizer import BertTo... | rosita/data/load_data_rec.py | # ROSITA
# Licensed under The Apache License 2.0 [see LICENSE for details]
# Written by <NAME> and <NAME>
# --------------------------------------------------------
import numpy as np
import json, re, torch, logging, collections, copy, os, base64
import torch.utils.data as Data
from utils.tokenizer import BertTo... | 0.677474 | 0.220426 |
import mesh.boundary as bnd
import mesh.patch as patch
import mesh.array_indexer as ai
import numpy as np
from numpy.testing import assert_array_equal
# Grid2d tests
class TestGrid2d(object):
@classmethod
def setup_class(cls):
""" this is run once for each class before any tests """
pass
... | mesh/tests/test_patch.py | import mesh.boundary as bnd
import mesh.patch as patch
import mesh.array_indexer as ai
import numpy as np
from numpy.testing import assert_array_equal
# Grid2d tests
class TestGrid2d(object):
@classmethod
def setup_class(cls):
""" this is run once for each class before any tests """
pass
... | 0.792946 | 0.622115 |
from rest_framework import serializers
from api.models import Book, Author, BookLoan
from users.serializers import CustomUserSerializer
from django.utils import timezone
class AuthorSerializer(serializers.ModelSerializer):
"""
Basic Serializer for Author Model
"""
class Meta:
model = Author
... | api/serializers.py | from rest_framework import serializers
from api.models import Book, Author, BookLoan
from users.serializers import CustomUserSerializer
from django.utils import timezone
class AuthorSerializer(serializers.ModelSerializer):
"""
Basic Serializer for Author Model
"""
class Meta:
model = Author
... | 0.791096 | 0.235174 |
from __future__ import print_function
import time
import tensorflow as tf
from six.moves import xrange
def model(x, nlogits, train=False):
b = tf.shape(x)[0]
if args.infer_legacy:
window = tf.contrib.signal.hann_window(1024)
windows = []
for i in xrange(0, 16384, 128):
x_window = x[:, i:i+102... | eval/inception/train.py | from __future__ import print_function
import time
import tensorflow as tf
from six.moves import xrange
def model(x, nlogits, train=False):
b = tf.shape(x)[0]
if args.infer_legacy:
window = tf.contrib.signal.hann_window(1024)
windows = []
for i in xrange(0, 16384, 128):
x_window = x[:, i:i+102... | 0.699562 | 0.442757 |
import os
import sys
from keras.utils.data_utils import get_file
ORIGIN = 'https://github.com/dluvizon/deephar/releases/download/'
def check_mpii_dataset():
version = 'v0.1'
try:
mpii_path = os.path.join(os.getcwd(), 'datasets/MPII/')
annot_path = get_file(mpii_path + 'annotations.mat',
... | datasets/annothelper.py | import os
import sys
from keras.utils.data_utils import get_file
ORIGIN = 'https://github.com/dluvizon/deephar/releases/download/'
def check_mpii_dataset():
version = 'v0.1'
try:
mpii_path = os.path.join(os.getcwd(), 'datasets/MPII/')
annot_path = get_file(mpii_path + 'annotations.mat',
... | 0.205854 | 0.167866 |
load("@bazel_tools//tools/build_defs/repo:git.bzl", "git_repository")
load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive")
def maybe(repo_rule, name, **kwargs):
"""Defines a repository if it does not already exist.
"""
if name not in native.existing_rules():
repo_rule(name = name, *... | setup.bzl | load("@bazel_tools//tools/build_defs/repo:git.bzl", "git_repository")
load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive")
def maybe(repo_rule, name, **kwargs):
"""Defines a repository if it does not already exist.
"""
if name not in native.existing_rules():
repo_rule(name = name, *... | 0.400749 | 0.163846 |
import cProfile
import itertools
from itertree import *
max_items = 102
#max_items = 5
root=None
def performance_it_build():
#tag access
global dt_root,max_items
dt = iTree('root')
#dt.pre_alloc_list(max_items)
#append itertree with items
append_item = dt
for i in range(max_items):
... | src/itertree/examples/itree_profile2.py | import cProfile
import itertools
from itertree import *
max_items = 102
#max_items = 5
root=None
def performance_it_build():
#tag access
global dt_root,max_items
dt = iTree('root')
#dt.pre_alloc_list(max_items)
#append itertree with items
append_item = dt
for i in range(max_items):
... | 0.071271 | 0.068506 |
import pyautogui
import tkinter as tk
from tkinter import ttk
from tkinter import *
class MainFrame:
def __init__(self, root):
self.root = root
self.root.rowconfigure(0, weight=0)
self.root.rowconfigure(1, weight=1)
self.root.columnconfigure(0, weight=1)
# 1.按钮区
sel... | core/window.py | import pyautogui
import tkinter as tk
from tkinter import ttk
from tkinter import *
class MainFrame:
def __init__(self, root):
self.root = root
self.root.rowconfigure(0, weight=0)
self.root.rowconfigure(1, weight=1)
self.root.columnconfigure(0, weight=1)
# 1.按钮区
sel... | 0.225502 | 0.074973 |
import scipy
import pandas as pd
from scipy.signal import find_peaks,peak_widths
import scipy.signal
from scipy.signal import savgol_filter
from brian2 import *
from tqdm import tqdm
from sklearn.preprocessing import RobustScaler,StandardScaler
try:
import tensortools as tt
has_tt=True
except:
has_tt = Fals... | brian_utils/postproc.py | import scipy
import pandas as pd
from scipy.signal import find_peaks,peak_widths
import scipy.signal
from scipy.signal import savgol_filter
from brian2 import *
from tqdm import tqdm
from sklearn.preprocessing import RobustScaler,StandardScaler
try:
import tensortools as tt
has_tt=True
except:
has_tt = Fals... | 0.436862 | 0.418519 |
from hat import aio
from hat import json
from hat.event.server import common
import asyncio
import itertools
import logging
mlog = logging.getLogger(__name__)
json_schema_id = 'hat-aimm://module.yaml#'
json_schema_repo = json.SchemaRepository(json.decode("""
---
id: 'hat-aimm://module.yaml#'
type: object
...
""", fo... | examples/0002/src_py/hat/module.py | from hat import aio
from hat import json
from hat.event.server import common
import asyncio
import itertools
import logging
mlog = logging.getLogger(__name__)
json_schema_id = 'hat-aimm://module.yaml#'
json_schema_repo = json.SchemaRepository(json.decode("""
---
id: 'hat-aimm://module.yaml#'
type: object
...
""", fo... | 0.483161 | 0.088978 |
import gzip
import os
import time
import pandas as pd
def parse(path):
g = gzip.open(path, 'rb')
for e in g:
yield eval(e)
def load_json_gz(path):
i = 0
df = {}
for d in parse(path):
df[i] = d
i += 1
return pd.DataFrame.from_dict(df, orient='index'... | src/scalability/pro_data.py | import gzip
import os
import time
import pandas as pd
def parse(path):
g = gzip.open(path, 'rb')
for e in g:
yield eval(e)
def load_json_gz(path):
i = 0
df = {}
for d in parse(path):
df[i] = d
i += 1
return pd.DataFrame.from_dict(df, orient='index'... | 0.158793 | 0.217275 |
import html
from data_types.commit import Commit
from data_types.repository import Repository
from data_types.user import User
from .base import EventBase
class EventPush(EventBase):
def __init__(self, sdk):
super(EventPush, self).__init__(sdk)
self.repository = None
self.sender = None
... | github/events/push.py | import html
from data_types.commit import Commit
from data_types.repository import Repository
from data_types.user import User
from .base import EventBase
class EventPush(EventBase):
def __init__(self, sdk):
super(EventPush, self).__init__(sdk)
self.repository = None
self.sender = None
... | 0.523177 | 0.192881 |
from rest_framework import serializers
from cctool.graphs.models import models
from cctool.common.enums import *
from cctool.graphs.view_helpers import GraphHelper
from cctool.analysers.view_helpers import AnalyserHelper
class DynamicFieldsModelSerializer(serializers.ModelSerializer):
"""
A ModelSerializer th... | backend/api/serializers.py | from rest_framework import serializers
from cctool.graphs.models import models
from cctool.common.enums import *
from cctool.graphs.view_helpers import GraphHelper
from cctool.analysers.view_helpers import AnalyserHelper
class DynamicFieldsModelSerializer(serializers.ModelSerializer):
"""
A ModelSerializer th... | 0.85067 | 0.250632 |
from packtools.sps.models.article_authors import (
Authors,
)
from unittest import TestCase, skip
from lxml import etree
class AuthorsTest(TestCase):
def setUp(self):
xml = ("""
<article>
<front>
<article-meta>
<contrib-group>
<contrib contri... | tests/sps/test_article_authors.py | from packtools.sps.models.article_authors import (
Authors,
)
from unittest import TestCase, skip
from lxml import etree
class AuthorsTest(TestCase):
def setUp(self):
xml = ("""
<article>
<front>
<article-meta>
<contrib-group>
<contrib contri... | 0.534612 | 0.278465 |
from django.contrib.auth.models import User, Group
from django.db import models
from django import forms
import string
import random
ENG_CHARS = 'abcdefghijklmnopqrstuvwxyz0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ'
HEX_CHARS = 'abcdefabcdef0987654321'
CHARS = HEX_CHARS
def get_upload_path(instance, filename):
print(insta... | fileupload/models.py | from django.contrib.auth.models import User, Group
from django.db import models
from django import forms
import string
import random
ENG_CHARS = 'abcdefghijklmnopqrstuvwxyz0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ'
HEX_CHARS = 'abcdefabcdef0987654321'
CHARS = HEX_CHARS
def get_upload_path(instance, filename):
print(insta... | 0.307254 | 0.09236 |
import itertools, struct
class BinaryObject(object):
_fields_ = []
def __init__(self):
self._total_size = 0
def __len__(self):
return self._total_size
def __repr__(self):
result = ['{']
for slot, fmt in self._fields_:
if slot is None:
conti... | manticore/binary/grr/snapshot.py | import itertools, struct
class BinaryObject(object):
_fields_ = []
def __init__(self):
self._total_size = 0
def __len__(self):
return self._total_size
def __repr__(self):
result = ['{']
for slot, fmt in self._fields_:
if slot is None:
conti... | 0.324985 | 0.201047 |
import re
import datetime
import time
# define SQLITE_OK 0 /* Successful result */
# define SQLITE_ERROR 1 /* SQL error or missing database */
# define SQLITE_INTERNAL 2 /* Internal logic error in SQLite */
# define SQLITE_PERM 3 /* Access permission denied */
# define SQLITE_ABORT... | sqlitespy/utils/query.py | import re
import datetime
import time
# define SQLITE_OK 0 /* Successful result */
# define SQLITE_ERROR 1 /* SQL error or missing database */
# define SQLITE_INTERNAL 2 /* Internal logic error in SQLite */
# define SQLITE_PERM 3 /* Access permission denied */
# define SQLITE_ABORT... | 0.348313 | 0.091099 |
import os
import sys
import string
def is_active():
return True
def get_name():
return "JavaScript"
def can_build():
import os
if (not os.environ.has_key("EMSCRIPTEN_ROOT")):
return False
return True
def get_opts():
return [
['wasm', 'Compile to WebAssembly', 'no'],
... | platform/javascript/detect.py | import os
import sys
import string
def is_active():
return True
def get_name():
return "JavaScript"
def can_build():
import os
if (not os.environ.has_key("EMSCRIPTEN_ROOT")):
return False
return True
def get_opts():
return [
['wasm', 'Compile to WebAssembly', 'no'],
... | 0.119935 | 0.041715 |
from dataclasses import dataclass
from typing import Optional
from .object import Object
@dataclass
class SimpleUser(Object):
"""
Simple User
"""
name: Optional['str']
email: Optional['str']
login: str
id: str
node_id: str
avatar_id: str
gravatar_id: str
url: str
html... | github/types/user.py | from dataclasses import dataclass
from typing import Optional
from .object import Object
@dataclass
class SimpleUser(Object):
"""
Simple User
"""
name: Optional['str']
email: Optional['str']
login: str
id: str
node_id: str
avatar_id: str
gravatar_id: str
url: str
html... | 0.813461 | 0.052814 |
from typing import Any, Callable, Optional, Tuple, Union
import tensorflow as tf
from tensorflow_gnn.graph import graph_constants as const
from tensorflow_gnn.graph import graph_tensor as gt
from tensorflow_gnn.graph import graph_tensor_ops as ops
from tensorflow_gnn.graph import normalization_ops
class GATv2(tf.ker... | tensorflow_gnn/graph/keras/layers/gat/gatv2.py | from typing import Any, Callable, Optional, Tuple, Union
import tensorflow as tf
from tensorflow_gnn.graph import graph_constants as const
from tensorflow_gnn.graph import graph_tensor as gt
from tensorflow_gnn.graph import graph_tensor_ops as ops
from tensorflow_gnn.graph import normalization_ops
class GATv2(tf.ker... | 0.9446 | 0.731706 |
from keras.callbacks import ModelCheckpoint, CSVLogger
from iss.models.Callbacks import DisplayPictureCallback, TensorboardCallback, FloydhubTrainigMetricsCallback
from iss.tools.tools import Tools
import keras
class ModelTrainer:
def __init__(self, model, data_loader, config, callbacks=[]):
self.model = model
... | iss/models/ModelTrainer.py |
from keras.callbacks import ModelCheckpoint, CSVLogger
from iss.models.Callbacks import DisplayPictureCallback, TensorboardCallback, FloydhubTrainigMetricsCallback
from iss.tools.tools import Tools
import keras
class ModelTrainer:
def __init__(self, model, data_loader, config, callbacks=[]):
self.model = model
... | 0.429788 | 0.164852 |
from nose.tools import assert_equal, assert_true, assert_false, assert_raises
import networkx as nx
# Tests for node and edge cutsets
def _generate_no_biconnected(max_attempts=50):
attempts = 0
while True:
G = nx.fast_gnp_random_graph(100,0.0575)
if nx.is_connected(G) and not nx.is_biconnected(... | networkx/algorithms/connectivity/tests/test_cuts.py | from nose.tools import assert_equal, assert_true, assert_false, assert_raises
import networkx as nx
# Tests for node and edge cutsets
def _generate_no_biconnected(max_attempts=50):
attempts = 0
while True:
G = nx.fast_gnp_random_graph(100,0.0575)
if nx.is_connected(G) and not nx.is_biconnected(... | 0.611382 | 0.57529 |
from django.http import HttpResponseRedirect, HttpResponseForbidden
from django.shortcuts import get_object_or_404, render
from cog.models.project import Project, getProjectsForUser
from cog.models.auth import userHasProjectRole
from cog.views.constants import PERMISSION_DENIED_MESSAGE
from cog.models.constants impo... | cog/cog_filebrowser.py |
from django.http import HttpResponseRedirect, HttpResponseForbidden
from django.shortcuts import get_object_or_404, render
from cog.models.project import Project, getProjectsForUser
from cog.models.auth import userHasProjectRole
from cog.views.constants import PERMISSION_DENIED_MESSAGE
from cog.models.constants impo... | 0.410638 | 0.054249 |
# to use this example, you need to change keras backend to theano AND also revert back to an older environment shimon_herokeras, change model
from keras.models import Sequential
from keras.layers.core import Flatten, Dense, Dropout
from keras.layers.convolutional import Convolution2D, MaxPooling2D, ZeroPadding2D
fro... | extract_image_features/old_code/VGG16_features3.py |
# to use this example, you need to change keras backend to theano AND also revert back to an older environment shimon_herokeras, change model
from keras.models import Sequential
from keras.layers.core import Flatten, Dense, Dropout
from keras.layers.convolutional import Convolution2D, MaxPooling2D, ZeroPadding2D
fro... | 0.821903 | 0.641942 |
import time
import sys
import subprocess
import psycopg2
import argparse
#Start time for processing file
def start_time():
starttime = time.asctime(time.localtime(time.time()))
print starttime
return starttime
#First Line
def first_line(filename):
firstline = subprocess.check_output(['head', '-1', fil... | server/before_streamsets.py | import time
import sys
import subprocess
import psycopg2
import argparse
#Start time for processing file
def start_time():
starttime = time.asctime(time.localtime(time.time()))
print starttime
return starttime
#First Line
def first_line(filename):
firstline = subprocess.check_output(['head', '-1', fil... | 0.094453 | 0.188305 |
from __future__ import unicode_literals
from django.db import models, migrations
class Migration(migrations.Migration):
dependencies = [
]
operations = [
migrations.CreateModel(
name='Form',
fields=[
('id', models.AutoField(primary_key=True, serialize=Fal... | envlive/lib/python2.7/site-packages/form_designer/migrations/0001_initial.py | from __future__ import unicode_literals
from django.db import models, migrations
class Migration(migrations.Migration):
dependencies = [
]
operations = [
migrations.CreateModel(
name='Form',
fields=[
('id', models.AutoField(primary_key=True, serialize=Fal... | 0.671686 | 0.128881 |
import pymc
import numpy as np
import argparse
import pickle
parser = argparse.ArgumentParser()
parser.add_argument("in_file", type=str, help="Input files")
parser.add_argument("out_file", type=str, help="Output files")
args = parser.parse_args()
with open(args.in_file,'r') as f:
hmm_models = pickle.load(f)['air1... | proto/pymc_models/build_appliance_model.py | import pymc
import numpy as np
import argparse
import pickle
parser = argparse.ArgumentParser()
parser.add_argument("in_file", type=str, help="Input files")
parser.add_argument("out_file", type=str, help="Output files")
args = parser.parse_args()
with open(args.in_file,'r') as f:
hmm_models = pickle.load(f)['air1... | 0.258888 | 0.270673 |
import random
from copy import deepcopy
import numpy as np
from sklearn.datasets import make_classification
from sklearn.metrics import roc_auc_score as roc_auc
from core.composer.chain import Chain
from core.composer.composer import DummyComposer, DummyChainTypeEnum, ComposerRequirements
from core.models.da... | fedot/test/test_split_train_test.py | import random
from copy import deepcopy
import numpy as np
from sklearn.datasets import make_classification
from sklearn.metrics import roc_auc_score as roc_auc
from core.composer.chain import Chain
from core.composer.composer import DummyComposer, DummyChainTypeEnum, ComposerRequirements
from core.models.da... | 0.713232 | 0.366391 |
import numpy as _np
def StdOutlier(df, columns, strategy='replace'):
'''
This method removes all outliers and replace it with 3rd standard
deviation value.
Parameters
--------------------
df: rectangular dataset
2D dataset that can be coerced into an ndarray. If a Pandas DataFram... | codeless/olr.py | import numpy as _np
def StdOutlier(df, columns, strategy='replace'):
'''
This method removes all outliers and replace it with 3rd standard
deviation value.
Parameters
--------------------
df: rectangular dataset
2D dataset that can be coerced into an ndarray. If a Pandas DataFram... | 0.730963 | 0.740268 |
import asyncio
import configparser
import logging
import os
import shutil
import time
from pathlib import Path
from typing import Dict, Callable, Union
from aioquic.asyncio import QuicConnectionProtocol
from aioquic.quic import events
from aioquic.quic.connection import QuicConnection
from aioquic.quic.events import S... | src/VideoStreamServerProtocol.py | import asyncio
import configparser
import logging
import os
import shutil
import time
from pathlib import Path
from typing import Dict, Callable, Union
from aioquic.asyncio import QuicConnectionProtocol
from aioquic.quic import events
from aioquic.quic.connection import QuicConnection
from aioquic.quic.events import S... | 0.546254 | 0.129375 |
from abc import ABC
from abc import abstractmethod
from multiprocessing import Process
from multiprocessing import Pipe
class ProcessMaster(ABC):
r"""Base class for all masters implemented with Python multiprocessing.Process.
It creates a number of workers each with an individual Process. The communic... | lagom/multiprocessing/process_master.py |
from abc import ABC
from abc import abstractmethod
from multiprocessing import Process
from multiprocessing import Pipe
class ProcessMaster(ABC):
r"""Base class for all masters implemented with Python multiprocessing.Process.
It creates a number of workers each with an individual Process. The communic... | 0.717012 | 0.33181 |
import json
import subprocess
PLUGIN_VERSION=1
HEARTBEAT="true"
port=""
master_name=""
metric_units={"sentinel_masters":"count","sentinel_running_scripts":"count","sentinel_scripts_queue_length":"count","link_pending_commands":"count","num_slaves":"count","num_other_sentinels":"count","role_reported_time":"ms"}
req... | redis_sentinel/redis_sentinel.py | import json
import subprocess
PLUGIN_VERSION=1
HEARTBEAT="true"
port=""
master_name=""
metric_units={"sentinel_masters":"count","sentinel_running_scripts":"count","sentinel_scripts_queue_length":"count","link_pending_commands":"count","num_slaves":"count","num_other_sentinels":"count","role_reported_time":"ms"}
req... | 0.09061 | 0.068226 |
import argparse
import os
from pprint import pprint
import yaml
from autogluon.vision import ImagePredictor
def get_input_path(path):
file = os.listdir(path)[0]
if len(os.listdir(path)) > 1:
print(f'WARN: more than one file is found in {path} directory')
print(f'Using {file}')
filename = f'{p... | test/sagemaker_tests/autogluon/training/resources/scripts/train_cv.py | import argparse
import os
from pprint import pprint
import yaml
from autogluon.vision import ImagePredictor
def get_input_path(path):
file = os.listdir(path)[0]
if len(os.listdir(path)) > 1:
print(f'WARN: more than one file is found in {path} directory')
print(f'Using {file}')
filename = f'{p... | 0.427994 | 0.07921 |
from pyPdf import PdfFileWriter, PdfFileReader
import sys
import json
import os
class pdf_metadata():
page_height = 0
def load_pdf_metadata(filename):
metadata = filename + "_data/pdfbox_output/pdf_metadata.txt"
#print metadata
with open(metadata) as fn:
for line in fn:
tmp = line.split(",")
pdf_metadata... | img_creation.py | from pyPdf import PdfFileWriter, PdfFileReader
import sys
import json
import os
class pdf_metadata():
page_height = 0
def load_pdf_metadata(filename):
metadata = filename + "_data/pdfbox_output/pdf_metadata.txt"
#print metadata
with open(metadata) as fn:
for line in fn:
tmp = line.split(",")
pdf_metadata... | 0.042583 | 0.099908 |
from knack.log import get_logger
from knack.util import CLIError
from azext_devops.devops_sdk.exceptions import AzureDevOpsClientRequestError
from azext_devops.devops_sdk.v5_0.graph.models import (JsonPatchOperation,
GraphSubjectLookup,
... | azure-devops/azext_devops/dev/team/security_group.py |
from knack.log import get_logger
from knack.util import CLIError
from azext_devops.devops_sdk.exceptions import AzureDevOpsClientRequestError
from azext_devops.devops_sdk.v5_0.graph.models import (JsonPatchOperation,
GraphSubjectLookup,
... | 0.756447 | 0.096748 |
from modularodm import Q
from nose.tools import * # flake8: noqa
from api.search.serializers import SearchSerializer
from api_tests import utils
from tests.base import DbTestCase
from osf_tests.factories import (
AuthUserFactory,
NodeFactory,
ProjectFactory,
)
from tests.utils import make_drf_request_wit... | api_tests/search/serializers/test_serializers.py | from modularodm import Q
from nose.tools import * # flake8: noqa
from api.search.serializers import SearchSerializer
from api_tests import utils
from tests.base import DbTestCase
from osf_tests.factories import (
AuthUserFactory,
NodeFactory,
ProjectFactory,
)
from tests.utils import make_drf_request_wit... | 0.6488 | 0.153708 |
from __future__ import unicode_literals
from __future__ import absolute_import, division, print_function
__author__ = "<NAME> (<EMAIL>)"
__copyright__ = "Copyright 2016, <NAME>"
__license__ = "MIT (http://opensource.org/licenses/MIT)"
import logging
log = logging.getLogger(__name__)
import os
import re
im... | src/annalist_root/login/login_views.py | from __future__ import unicode_literals
from __future__ import absolute_import, division, print_function
__author__ = "<NAME> (<EMAIL>)"
__copyright__ = "Copyright 2016, <NAME>"
__license__ = "MIT (http://opensource.org/licenses/MIT)"
import logging
log = logging.getLogger(__name__)
import os
import re
im... | 0.393735 | 0.037257 |
import os
import panda3d.core as p3d
from direct.filter.FilterManager import FilterManager
from .version import __version__
__all__ = [
'init',
]
def _add_shader_defines(shaderstr, defines):
shaderlines = shaderstr.split('\n')
for line in shaderlines:
if '#version' in line:
vers... | simplepbr/__init__.py | import os
import panda3d.core as p3d
from direct.filter.FilterManager import FilterManager
from .version import __version__
__all__ = [
'init',
]
def _add_shader_defines(shaderstr, defines):
shaderlines = shaderstr.split('\n')
for line in shaderlines:
if '#version' in line:
vers... | 0.519521 | 0.194502 |
from django.conf import settings
from django.utils.html import format_html
from django import template
register = template.Library()
def _tracking_script(setting_name, script):
tag_id = getattr(settings, setting_name, None)
if not tag_id:
return ''
return format_html(script, tag_id)
@register... | eti_marketing/templatetags/marketing.py | from django.conf import settings
from django.utils.html import format_html
from django import template
register = template.Library()
def _tracking_script(setting_name, script):
tag_id = getattr(settings, setting_name, None)
if not tag_id:
return ''
return format_html(script, tag_id)
@register... | 0.23014 | 0.073297 |
import abc
from datetime import datetime
from crawling_gocd.calculate_domain import CalculateStrategyHandler, Result
class CalculateStrategyHandlerBase(CalculateStrategyHandler):
def calculate(self, pipelines, results):
for pipeline in pipelines:
self.calculateSingle(pipeline, results)
... | crawling_gocd/four_key_metrics.py | import abc
from datetime import datetime
from crawling_gocd.calculate_domain import CalculateStrategyHandler, Result
class CalculateStrategyHandlerBase(CalculateStrategyHandler):
def calculate(self, pipelines, results):
for pipeline in pipelines:
self.calculateSingle(pipeline, results)
... | 0.663996 | 0.331093 |
import cv2, os, sys
import numpy as np
from keras import backend as kb
sys.path.append("C:/ChestXray_DL/MyCheXnet")
from utility import get_PILimage, process_PILimage
def heatmap(model, activated_class, image_fp, output_fp, activated_threshold=0):
def get_output_layer(model, layer_name):
la... | heatmap.py | import cv2, os, sys
import numpy as np
from keras import backend as kb
sys.path.append("C:/ChestXray_DL/MyCheXnet")
from utility import get_PILimage, process_PILimage
def heatmap(model, activated_class, image_fp, output_fp, activated_threshold=0):
def get_output_layer(model, layer_name):
la... | 0.381565 | 0.259239 |