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 pydfs_lineup_optimizer import Site, Sport, get_optimizer, CSVLineupExporter
from pydfs_lineup_optimizer.context import OptimizationContext
from pydfs_lineup_optimizer import db_writer, PlayersGroup, Stack
from azure.cosmos import exceptions, CosmosClient, PartitionKey
import json
FileName = "Golf.csv"
TotalCount... | Golf_Lineups.py | from pydfs_lineup_optimizer import Site, Sport, get_optimizer, CSVLineupExporter
from pydfs_lineup_optimizer.context import OptimizationContext
from pydfs_lineup_optimizer import db_writer, PlayersGroup, Stack
from azure.cosmos import exceptions, CosmosClient, PartitionKey
import json
FileName = "Golf.csv"
TotalCount... | 0.371251 | 0.134179 |
import requests
import time
import json
import sys, os
from bs4 import BeautifulSoup
from selenium import webdriver
from selenium.webdriver.support.ui import Select
from selenium.webdriver.common.keys import Keys
from selenium.common.exceptions import NoSuchElementException
def main():
# driver = webdriver.Firefox(... | dashboard/tasker.py | import requests
import time
import json
import sys, os
from bs4 import BeautifulSoup
from selenium import webdriver
from selenium.webdriver.support.ui import Select
from selenium.webdriver.common.keys import Keys
from selenium.common.exceptions import NoSuchElementException
def main():
# driver = webdriver.Firefox(... | 0.055714 | 0.072834 |
from itertools import combinations
import time
from multiprocessing import Pool
from functools import partial
import numpy as np
def get_partitions(n, k=None, max_depth=None):
partitions = []
def partition(target, max_value, suffix):
if max_depth is not None and len(partitions) > max_depth:
... | tsn/fold.py | from itertools import combinations
import time
from multiprocessing import Pool
from functools import partial
import numpy as np
def get_partitions(n, k=None, max_depth=None):
partitions = []
def partition(target, max_value, suffix):
if max_depth is not None and len(partitions) > max_depth:
... | 0.501953 | 0.412057 |
import argparse
import logging
import os
def log_option(opts, attr):
obj = getattr(opts, attr)
if isinstance(obj, list) or isinstance(obj, tuple):
for i, item in enumerate(obj):
logging.info('%-10s = %s', '{}[{:d}]'.format(attr, i), obj[i])
return
if isinstance(obj, set):
... | pyrename/options.py | import argparse
import logging
import os
def log_option(opts, attr):
obj = getattr(opts, attr)
if isinstance(obj, list) or isinstance(obj, tuple):
for i, item in enumerate(obj):
logging.info('%-10s = %s', '{}[{:d}]'.format(attr, i), obj[i])
return
if isinstance(obj, set):
... | 0.369998 | 0.05328 |
""" Graph all of the features from a single experiment. """
import argparse
import multiprocessing
import os
from os import path
from matplotlib import pyplot as plt
import numpy as np
import cl_args
import features
import utils
def graph_fet(out_dir, dat, fet, bw_share_fair, bw_fair, x_min, x_max, labels):
""... | model/graph_one.py | """ Graph all of the features from a single experiment. """
import argparse
import multiprocessing
import os
from os import path
from matplotlib import pyplot as plt
import numpy as np
import cl_args
import features
import utils
def graph_fet(out_dir, dat, fet, bw_share_fair, bw_fair, x_min, x_max, labels):
""... | 0.587115 | 0.590425 |
import numpy as np
import uncertainties.unumpy as un
from scipy.stats import pearsonr
def nan_pearsonr(x, y):
xy = np.vstack([x, y])
xy = xy[:, ~np.any(np.isnan(xy),0)]
n = len(x)
if xy.shape[-1] < n // 2:
return np.nan, np.nan
return pearsonr(xy[0], xy[1])
def R2calc(meas, model,... | latools/helpers/stat_fns.py | import numpy as np
import uncertainties.unumpy as un
from scipy.stats import pearsonr
def nan_pearsonr(x, y):
xy = np.vstack([x, y])
xy = xy[:, ~np.any(np.isnan(xy),0)]
n = len(x)
if xy.shape[-1] < n // 2:
return np.nan, np.nan
return pearsonr(xy[0], xy[1])
def R2calc(meas, model,... | 0.84075 | 0.747339 |
from __future__ import (absolute_import, division,
print_function, unicode_literals)
__author__ = "<NAME>"
import numpy as np
from upho.structure.structure_analyzer import (
StructureAnalyzer, find_lattice_vectors)
from upho.analysis.mappings_modifier import MappingsModifier
class Transl... | upho/phonon/translational_projector.py | from __future__ import (absolute_import, division,
print_function, unicode_literals)
__author__ = "<NAME>"
import numpy as np
from upho.structure.structure_analyzer import (
StructureAnalyzer, find_lattice_vectors)
from upho.analysis.mappings_modifier import MappingsModifier
class Transl... | 0.827236 | 0.552117 |
from __future__ import print_function
from __future__ import unicode_literals
import argparse
import glob
import logging
import sys
import os
from imagemounter import _util, ImageParser, Unmounter, __version__, FILE_SYSTEM_TYPES, VOLUME_SYSTEM_TYPES, \
DISK_MOUNTERS
from imagemounter.cli import CheckAction, get_... | imagemounter/cli/imount.py |
from __future__ import print_function
from __future__ import unicode_literals
import argparse
import glob
import logging
import sys
import os
from imagemounter import _util, ImageParser, Unmounter, __version__, FILE_SYSTEM_TYPES, VOLUME_SYSTEM_TYPES, \
DISK_MOUNTERS
from imagemounter.cli import CheckAction, get_... | 0.52756 | 0.080105 |
import xml.etree.ElementTree as et
import json
import xml.dom.minidom as minidom
import time
def pretty_print(tree_root):
tree_string = et.tostring(tree_root, "utf-8")
final_string = tree_string
reparsed = minidom.parseString(final_string)
return reparsed.toprettyxml(indent="\t")
with open("coverage... | tests/coverage/cobertura_generator.py | import xml.etree.ElementTree as et
import json
import xml.dom.minidom as minidom
import time
def pretty_print(tree_root):
tree_string = et.tostring(tree_root, "utf-8")
final_string = tree_string
reparsed = minidom.parseString(final_string)
return reparsed.toprettyxml(indent="\t")
with open("coverage... | 0.249264 | 0.180089 |
import os
from src.img2resize import img2resize
from src.img2greyscale import img2greyscale
from src.img2kmeans import img2kmeans
from src.img2edges import img2edges
def main():
settings = {
"img2resize": {"use": True, "ypixels": 100, "xpixels": 100},
"img2greyscale": {"use": True},
"img2... | process_your_images/process_your_images.py | import os
from src.img2resize import img2resize
from src.img2greyscale import img2greyscale
from src.img2kmeans import img2kmeans
from src.img2edges import img2edges
def main():
settings = {
"img2resize": {"use": True, "ypixels": 100, "xpixels": 100},
"img2greyscale": {"use": True},
"img2... | 0.231527 | 0.309532 |
from torch.utils.data import Dataset # 데이터로더
from kogpt2.utils import download, tokenizer, get_tokenizer
from gluonnlp.data import SentencepieceTokenizer
import gluonnlp
import numpy as np
def sentencePieceTokenizer():
tok_path = get_tokenizer()
sentencepieceTokenizer = SentencepieceTokenizer(tok_path)
return ... | util/data.py | from torch.utils.data import Dataset # 데이터로더
from kogpt2.utils import download, tokenizer, get_tokenizer
from gluonnlp.data import SentencepieceTokenizer
import gluonnlp
import numpy as np
def sentencePieceTokenizer():
tok_path = get_tokenizer()
sentencepieceTokenizer = SentencepieceTokenizer(tok_path)
return ... | 0.567098 | 0.363647 |
__all__ = ('Duckybot',)
from .system import sns, dbms, existent, files
class Duckybot:
def __init__(self):
"""
Create Duckybot instance.
"""
self.existent = False
self.files = files.Files
def connect_db(self, dbms_name, dict_config):
"""
Establish db ... | duckybot/core.py | __all__ = ('Duckybot',)
from .system import sns, dbms, existent, files
class Duckybot:
def __init__(self):
"""
Create Duckybot instance.
"""
self.existent = False
self.files = files.Files
def connect_db(self, dbms_name, dict_config):
"""
Establish db ... | 0.847558 | 0.135032 |
def prepare_grid(db):
"""
Return two vectors of coordinates x, y
and measured values in these coordinates.
"""
vec_x = set()
vec_y = set()
dic = {}
for el in db:
dic[(el[1], el[2])] = el[3]
vec_x.add(el[1])
vec_y.add(el[2])
return (sorted(vec_x), sorted(vec... | app/grid.py | def prepare_grid(db):
"""
Return two vectors of coordinates x, y
and measured values in these coordinates.
"""
vec_x = set()
vec_y = set()
dic = {}
for el in db:
dic[(el[1], el[2])] = el[3]
vec_x.add(el[1])
vec_y.add(el[2])
return (sorted(vec_x), sorted(vec... | 0.533641 | 0.692694 |
import requests
from multiprocessing import Process, Manager
import time
import sqlite3
import os
import sys
from bs4 import BeautifulSoup
from urllib.parse import urljoin, urlparse
from harvester.lddatabase import LDHarvesterDatabaseConnector
AUTO_PROCESS_OVERFLOW = True
WORK_QUEUE_OVERFLOW_FILE = 'overflow.txt'
DAT... | harvester/__init__.py | import requests
from multiprocessing import Process, Manager
import time
import sqlite3
import os
import sys
from bs4 import BeautifulSoup
from urllib.parse import urljoin, urlparse
from harvester.lddatabase import LDHarvesterDatabaseConnector
AUTO_PROCESS_OVERFLOW = True
WORK_QUEUE_OVERFLOW_FILE = 'overflow.txt'
DAT... | 0.28887 | 0.09187 |
from cement import ex
from xrdsst.api import LocalGroupsApi, ClientsApi
from xrdsst.api_client.api_client import ApiClient
from xrdsst.controllers.base import BaseController
from xrdsst.controllers.client import ClientController
from xrdsst.rest.rest import ApiException
from xrdsst.resources.texts import texts
from xrd... | xrdsst/controllers/local_group.py | from cement import ex
from xrdsst.api import LocalGroupsApi, ClientsApi
from xrdsst.api_client.api_client import ApiClient
from xrdsst.controllers.base import BaseController
from xrdsst.controllers.client import ClientController
from xrdsst.rest.rest import ApiException
from xrdsst.resources.texts import texts
from xrd... | 0.440951 | 0.084795 |
import logging
import click
from codeorigins import VERSION
from codeorigins.utils import Dump, configure_logging
from codeorigins.composer import HtmlComposer
from codeorigins.fetchers import FETCHERS
from codeorigins.settings import COUNTRIES, LANGUAGES
if False: # pragma: nocover
from codeorigins.fetchers.b... | codeorigins/cli.py | import logging
import click
from codeorigins import VERSION
from codeorigins.utils import Dump, configure_logging
from codeorigins.composer import HtmlComposer
from codeorigins.fetchers import FETCHERS
from codeorigins.settings import COUNTRIES, LANGUAGES
if False: # pragma: nocover
from codeorigins.fetchers.b... | 0.469277 | 0.18279 |
import matplotlib.pyplot as plt
import torch
import numpy as np
from sklearn.metrics import confusion_matrix
import itertools
# test accuracy
def get_test_acc(test_loader, model, device):
n_correct = 0.
n_total = 0.
for inputs, targets in test_loader:
inputs, targets = inputs.to(device), target... | CIFAR-10/utils.py | import matplotlib.pyplot as plt
import torch
import numpy as np
from sklearn.metrics import confusion_matrix
import itertools
# test accuracy
def get_test_acc(test_loader, model, device):
n_correct = 0.
n_total = 0.
for inputs, targets in test_loader:
inputs, targets = inputs.to(device), target... | 0.828627 | 0.651202 |
from ...doc import *
cuSPARSE_level1 = [
# 6.1. cusparse<t>axpyi()
func_decl( [ "cusparseSaxpyi", "cusparseDaxpyi", "cusparseCaxpyi", "cusparseZaxpyi" ],
[ parm_def('handle', PASSBYVALUE, INOUT_IN ),
parm_def('nnz', PASSBYVALUE, INOUT_IN ),
parm_def('alpha', [ MEMORY_HoD_CU... | hfcuda_automate/lib/cudaToolkit91/cusparse/level1.py | from ...doc import *
cuSPARSE_level1 = [
# 6.1. cusparse<t>axpyi()
func_decl( [ "cusparseSaxpyi", "cusparseDaxpyi", "cusparseCaxpyi", "cusparseZaxpyi" ],
[ parm_def('handle', PASSBYVALUE, INOUT_IN ),
parm_def('nnz', PASSBYVALUE, INOUT_IN ),
parm_def('alpha', [ MEMORY_HoD_CU... | 0.305386 | 0.179387 |
import os
import geopandas as gpd
import numpy as np
import pandas as pd
import rioxarray
import xarray as xr
from rasterstats import zonal_stats
from src.utils.constants import (
REGIONS,
GRID_RESOLUTION,
GRID_AREA_THRESHOLD,
SAMPLING_PROPORTION,
RANDOM_SEED,
AREA_FACTOR
)
from src.utils.func... | src/06_fuel/04_sample_cwd.py | import os
import geopandas as gpd
import numpy as np
import pandas as pd
import rioxarray
import xarray as xr
from rasterstats import zonal_stats
from src.utils.constants import (
REGIONS,
GRID_RESOLUTION,
GRID_AREA_THRESHOLD,
SAMPLING_PROPORTION,
RANDOM_SEED,
AREA_FACTOR
)
from src.utils.func... | 0.334698 | 0.254058 |
from typing import List
import numpy as np
from open_spiel.python.games.optimal_stopping_game_config import OptimalStoppingGameConfig
from open_spiel.python.games.optimal_stopping_game_observation_type import OptimalStoppingGameObservationType
class OptimalStoppingGameUtil:
@staticmethod
def next_state(state... | open_spiel/python/games/optimal_stopping_game_util.py | from typing import List
import numpy as np
from open_spiel.python.games.optimal_stopping_game_config import OptimalStoppingGameConfig
from open_spiel.python.games.optimal_stopping_game_observation_type import OptimalStoppingGameObservationType
class OptimalStoppingGameUtil:
@staticmethod
def next_state(state... | 0.850577 | 0.682021 |
from sys import argv
from collections import defaultdict as dd
script, gff3, output_cds, output_transcript = argv
cds_h = open(output_cds, 'w')
t_h = open(output_transcript, 'w')
cds_data = dd(lambda: dd(dict))
with open(gff3) as gff3_h:
for line in gff3_h:
if line.startswith("#"):
pass
else:
... | genome/parse_gff3.py | from sys import argv
from collections import defaultdict as dd
script, gff3, output_cds, output_transcript = argv
cds_h = open(output_cds, 'w')
t_h = open(output_transcript, 'w')
cds_data = dd(lambda: dd(dict))
with open(gff3) as gff3_h:
for line in gff3_h:
if line.startswith("#"):
pass
else:
... | 0.028008 | 0.105902 |
from django import forms
from auth_access_admin.forms import FeedingBottleForm, MedicalEventForm
from .models import (
DailyFact,
Sleep,
Meal,
FeedingBottle,
Activity,
MedicalEvent,
)
SleepFormSet = forms.inlineformset_factory(
DailyFact,
Sleep,
fields=("length_minutes",),
widg... | day_to_day/forms.py | from django import forms
from auth_access_admin.forms import FeedingBottleForm, MedicalEventForm
from .models import (
DailyFact,
Sleep,
Meal,
FeedingBottle,
Activity,
MedicalEvent,
)
SleepFormSet = forms.inlineformset_factory(
DailyFact,
Sleep,
fields=("length_minutes",),
widg... | 0.446012 | 0.163279 |
import os
from pathlib import Path
from datetime import datetime
from decouple import config, Csv
import dj_database_url
BASE_DIR = Path(__file__).resolve().parent.parent
SECRET_KEY = config("SECRET_KEY")
DEBUG = config("DEBUG", default=False, cast=bool)
ALLOWED_HOSTS = config("ALLOWED_HOSTS", cast=Csv())
DATABASES = ... | blog_backend/settings.py | import os
from pathlib import Path
from datetime import datetime
from decouple import config, Csv
import dj_database_url
BASE_DIR = Path(__file__).resolve().parent.parent
SECRET_KEY = config("SECRET_KEY")
DEBUG = config("DEBUG", default=False, cast=bool)
ALLOWED_HOSTS = config("ALLOWED_HOSTS", cast=Csv())
DATABASES = ... | 0.281406 | 0.070496 |
# needs Python3
import argparse
import configparser
import logging
import os
import random
import string
import urllib.request
from csv import DictReader
from datetime import datetime
from xml.etree.ElementTree import Element, SubElement, Comment, ElementTree
__license__ = "MIT"
__version__ = '1.6.2'
# define log ou... | csv2cmi.py |
# needs Python3
import argparse
import configparser
import logging
import os
import random
import string
import urllib.request
from csv import DictReader
from datetime import datetime
from xml.etree.ElementTree import Element, SubElement, Comment, ElementTree
__license__ = "MIT"
__version__ = '1.6.2'
# define log ou... | 0.316792 | 0.073364 |
import base64
import json
import logging
import math
import urllib
import uuid
from datetime import datetime
from struct import unpack
from types import NoneType
from babel.dates import format_datetime, get_timezone
from google.appengine.api import memcache, urlfetch
from google.appengine.api.urlfetch import fetch
fr... | src/rogerthat/bizz/location.py |
import base64
import json
import logging
import math
import urllib
import uuid
from datetime import datetime
from struct import unpack
from types import NoneType
from babel.dates import format_datetime, get_timezone
from google.appengine.api import memcache, urlfetch
from google.appengine.api.urlfetch import fetch
fr... | 0.514156 | 0.063251 |
from django.contrib import admin
from import_export.admin import ExportMixin
from import_export.fields import Field
from submissions.models import Submission
from users.mixins import ResourceUsersByEmailsMixin
from .models import Grant
EXPORT_GRANTS_FIELDS = (
"name",
"full_name",
"email",
"age",
... | backend/grants/admin.py | from django.contrib import admin
from import_export.admin import ExportMixin
from import_export.fields import Field
from submissions.models import Submission
from users.mixins import ResourceUsersByEmailsMixin
from .models import Grant
EXPORT_GRANTS_FIELDS = (
"name",
"full_name",
"email",
"age",
... | 0.427158 | 0.115736 |
import torch
import torch.nn as nn
import torch.optim as optim
import os
from numpy import prod
from datetime import datetime
from model import CapsuleNetwork
from loss import CapsuleLoss
from time import time
SAVE_MODEL_PATH = 'checkpoints/'
if not os.path.exists(SAVE_MODEL_PATH):
os.mkdir(SAVE_MODEL_PATH)
class C... | trainer.py |
import torch
import torch.nn as nn
import torch.optim as optim
import os
from numpy import prod
from datetime import datetime
from model import CapsuleNetwork
from loss import CapsuleLoss
from time import time
SAVE_MODEL_PATH = 'checkpoints/'
if not os.path.exists(SAVE_MODEL_PATH):
os.mkdir(SAVE_MODEL_PATH)
class C... | 0.505859 | 0.351784 |
import tensorflow as tf
import random
class CriteoClickLogs(object):
'''Criteo 1TB click logs Dataset.
See: https://ailab.criteo.com/download-criteo-1tb-click-logs-dataset/
- 13 dense features taking integer values (mostly count features)
- 26 sparse features, of which values have been hashed onto 32 bits
... | modelzoo/features/pmem/criteo.py | import tensorflow as tf
import random
class CriteoClickLogs(object):
'''Criteo 1TB click logs Dataset.
See: https://ailab.criteo.com/download-criteo-1tb-click-logs-dataset/
- 13 dense features taking integer values (mostly count features)
- 26 sparse features, of which values have been hashed onto 32 bits
... | 0.76454 | 0.32701 |
from rest_framework.views import APIView
from rest_framework.response import Response
# below import is for POST & PATCH
from rest_framework import status
# below is required for a viewset
from rest_framework import viewsets
from profiles_api import serializers
from profiles_api import models
# All of below code cov... | profiles_api/views.py | from rest_framework.views import APIView
from rest_framework.response import Response
# below import is for POST & PATCH
from rest_framework import status
# below is required for a viewset
from rest_framework import viewsets
from profiles_api import serializers
from profiles_api import models
# All of below code cov... | 0.79158 | 0.170888 |
from itertools import combinations
n = int(input()) # 복도의 크기
graph = [] # 복도 정보
teachers = [] # 모든 선생님 위치 정보
space = [] # 모든 빈 공간 위치 정보
for i in range(n):
graph.append(list(input().split()))
for j in range(n):
if graph[i][j] == 'T':
teachers.append((i, j))
elif graph[i][j] == 'X'... | CodingTestForEmployment/Part3/dfs, bfs/Q20.py | from itertools import combinations
n = int(input()) # 복도의 크기
graph = [] # 복도 정보
teachers = [] # 모든 선생님 위치 정보
space = [] # 모든 빈 공간 위치 정보
for i in range(n):
graph.append(list(input().split()))
for j in range(n):
if graph[i][j] == 'T':
teachers.append((i, j))
elif graph[i][j] == 'X'... | 0.125614 | 0.49823 |
# Copyright 2019-2021 <NAME>-Fitzpatrick
# Licensed under Apache Version 2.0
import ipaddress
import csv
import argparse
from argparse import RawTextHelpFormatter
from cidrize import cidrize
parser = argparse.ArgumentParser(description='IP Subnet Checker',formatter_class=RawTextHelpFormatter)
parser.add_argument('-s... | ipcheck.py |
# Copyright 2019-2021 <NAME>-Fitzpatrick
# Licensed under Apache Version 2.0
import ipaddress
import csv
import argparse
from argparse import RawTextHelpFormatter
from cidrize import cidrize
parser = argparse.ArgumentParser(description='IP Subnet Checker',formatter_class=RawTextHelpFormatter)
parser.add_argument('-s... | 0.435301 | 0.118436 |
from pyomo.environ import *
model = m = ConcreteModel()
m.x1 = Var(within=Reals,bounds=(0,None),initialize=10)
m.x2 = Var(within=Reals,bounds=(0,None),initialize=10)
m.x3 = Var(within=Reals,bounds=(0,None),initialize=10)
m.x4 = Var(within=Reals,bounds=(0,None),initialize=10)
m.x5 = Var(within=Reals,bounds=(0,None)... | tests/examples/minlplib/blendgap.py |
from pyomo.environ import *
model = m = ConcreteModel()
m.x1 = Var(within=Reals,bounds=(0,None),initialize=10)
m.x2 = Var(within=Reals,bounds=(0,None),initialize=10)
m.x3 = Var(within=Reals,bounds=(0,None),initialize=10)
m.x4 = Var(within=Reals,bounds=(0,None),initialize=10)
m.x5 = Var(within=Reals,bounds=(0,None)... | 0.564339 | 0.17006 |
from db.database import conn
class User:
def __init__(self, user_id: int, name: str, color: str):
self.__id = user_id
self.name = name
self.color = color
@property
def id(self):
return self.__id
def serialize(self, with_id=False):
serialized_user = {
... | db/models/user.py | from db.database import conn
class User:
def __init__(self, user_id: int, name: str, color: str):
self.__id = user_id
self.name = name
self.color = color
@property
def id(self):
return self.__id
def serialize(self, with_id=False):
serialized_user = {
... | 0.596903 | 0.088741 |
from core.himesis import Himesis, HimesisPreConditionPatternLHS
import uuid
class HContract06_CompleteLHS(HimesisPreConditionPatternLHS):
def __init__(self):
"""
Creates the himesis graph representing the AToM3 model HContract06_CompleteLHS
"""
# Flag this instance as compiled now
self.is_compiled = True
... | UML2ER/contracts/HContract06_CompleteLHS.py | from core.himesis import Himesis, HimesisPreConditionPatternLHS
import uuid
class HContract06_CompleteLHS(HimesisPreConditionPatternLHS):
def __init__(self):
"""
Creates the himesis graph representing the AToM3 model HContract06_CompleteLHS
"""
# Flag this instance as compiled now
self.is_compiled = True
... | 0.38549 | 0.191914 |
import os
from datetime import datetime, timedelta
from http import HTTPStatus
from typing import Any, List, Tuple
import pandas as pd
import numpy as np
import plotly.graph_objects as go
import tinvest as ti
import edhec_risk_kit as erk
import itertools
class HTTPError(Exception):
pass
class CustomClient(ti.Sync... | all_variants.py | import os
from datetime import datetime, timedelta
from http import HTTPStatus
from typing import Any, List, Tuple
import pandas as pd
import numpy as np
import plotly.graph_objects as go
import tinvest as ti
import edhec_risk_kit as erk
import itertools
class HTTPError(Exception):
pass
class CustomClient(ti.Sync... | 0.240507 | 0.145085 |
from decimal import Decimal
from .constants import *
def convertToSatoshi(strAmount):
return str(int(Decimal(strAmount) * 100000000))
def convertKbToBytes(strAmount):
return str(int(Decimal(strAmount) / 1000))
def getMethodSchemas(name):
return getRequestMethodSchema(name), getResponseMethodSchema(nam... | Connector/bch/utils.py | from decimal import Decimal
from .constants import *
def convertToSatoshi(strAmount):
return str(int(Decimal(strAmount) * 100000000))
def convertKbToBytes(strAmount):
return str(int(Decimal(strAmount) / 1000))
def getMethodSchemas(name):
return getRequestMethodSchema(name), getResponseMethodSchema(nam... | 0.553505 | 0.227899 |
""" convert mri data to mindrecord """
import os
import argparse
import numpy as np
from nibabel import load as load_nii
from mindspore.mindrecord import FileWriter
from mindspore.common import set_seed
set_seed(1)
def norm(image):
"""
the normalization of image
"""
image = np.squeeze(image)
... | research/cv/3dcnn/src/mindrecord_generator.py | """ convert mri data to mindrecord """
import os
import argparse
import numpy as np
from nibabel import load as load_nii
from mindspore.mindrecord import FileWriter
from mindspore.common import set_seed
set_seed(1)
def norm(image):
"""
the normalization of image
"""
image = np.squeeze(image)
... | 0.729712 | 0.599514 |
import os, sys, itertools, pickle
# disable terminal warning tf
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
## general tools
import numpy as np
import tensorflow as tf
import matplotlib.pyplot as plt
import cirq
from scipy.optimize import minimize
## vqe/qml tools.
import openfermion
import tensorflow_quantum as tfq
from ... | vqe-surrogate/vqe.py | import os, sys, itertools, pickle
# disable terminal warning tf
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
## general tools
import numpy as np
import tensorflow as tf
import matplotlib.pyplot as plt
import cirq
from scipy.optimize import minimize
## vqe/qml tools.
import openfermion
import tensorflow_quantum as tfq
from ... | 0.430147 | 0.318525 |
from __future__ import print_function
from ctypes import c_void_p, cast, POINTER
from mbientlab.metawear import MetaWear, libmetawear, parse_value, cbindings
from time import sleep
from threading import Event
from sys import argv
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
... | plot_AccGyro.py |
from __future__ import print_function
from ctypes import c_void_p, cast, POINTER
from mbientlab.metawear import MetaWear, libmetawear, parse_value, cbindings
from time import sleep
from threading import Event
from sys import argv
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
... | 0.272508 | 0.176583 |
from django.test import TestCase, RequestFactory
from .mixins import OneUserMixin, ProposalMixin, TemplateViewMixin
from django.utils import timezone
from consensus_engine.views import ProposalView
from consensus_engine.models import ChoiceTicket, ConsensusHistory
from consensus_engine.converters import DateConverter
... | consensus_engine/tests/test_view_proposal.py | from django.test import TestCase, RequestFactory
from .mixins import OneUserMixin, ProposalMixin, TemplateViewMixin
from django.utils import timezone
from consensus_engine.views import ProposalView
from consensus_engine.models import ChoiceTicket, ConsensusHistory
from consensus_engine.converters import DateConverter
... | 0.496338 | 0.334739 |
import json
import os
import boto3
import pytest
from modelstore.storage.aws import AWSStorage
from moto import mock_s3
# pylint: disable=unused-import
from tests.storage.test_utils import (
TEST_FILE_CONTENTS,
TEST_FILE_NAME,
file_contains_expected_contents,
remote_file_path,
remote_path,
tem... | tests/storage/test_aws.py | import json
import os
import boto3
import pytest
from modelstore.storage.aws import AWSStorage
from moto import mock_s3
# pylint: disable=unused-import
from tests.storage.test_utils import (
TEST_FILE_CONTENTS,
TEST_FILE_NAME,
file_contains_expected_contents,
remote_file_path,
remote_path,
tem... | 0.410638 | 0.265743 |
try:
import matplotlib.pyplot as plt
from matplotlib import cm
import palettable as pal
palette = pal.wesanderson.Moonrise1_5.mpl_colormap
except:
pass
import numpy as np
import random
from visualize import plotNode
from visualize import plotTileBoundaries
class Particles:
xs = []
ys ... | bindings/old/visualize_pic.py | try:
import matplotlib.pyplot as plt
from matplotlib import cm
import palettable as pal
palette = pal.wesanderson.Moonrise1_5.mpl_colormap
except:
pass
import numpy as np
import random
from visualize import plotNode
from visualize import plotTileBoundaries
class Particles:
xs = []
ys ... | 0.279337 | 0.343287 |
from __future__ import absolute_import, division, print_function, unicode_literals
import numpy as np
import os
from pathlib import Path, PosixPath
import math as math
import sqlite3
import pandas as pd
from datetime import datetime
import pickle
from joblib import Parallel, delayed
import multiprocessing
import argpar... | ensemble_5_runs.py | from __future__ import absolute_import, division, print_function, unicode_literals
import numpy as np
import os
from pathlib import Path, PosixPath
import math as math
import sqlite3
import pandas as pd
from datetime import datetime
import pickle
from joblib import Parallel, delayed
import multiprocessing
import argpar... | 0.576542 | 0.097777 |
import pandas as pd
df = pd.DataFrame({'a': [1, 2, 3],
'b': [0.1, 0.2, 0.3],
'c': ['X', 'Y', 'Z'],
'd': [[0, 0], [1, 1], [2, 2]],
'e': [True, True, False]})
df['f'] = pd.to_datetime(['2018-01-01', '2018-02-01', '2018-03-01'])
print(df)
# ... | notebook/pandas_select_dtypes.py | import pandas as pd
df = pd.DataFrame({'a': [1, 2, 3],
'b': [0.1, 0.2, 0.3],
'c': ['X', 'Y', 'Z'],
'd': [[0, 0], [1, 1], [2, 2]],
'e': [True, True, False]})
df['f'] = pd.to_datetime(['2018-01-01', '2018-02-01', '2018-03-01'])
print(df)
# ... | 0.087443 | 0.370453 |
from avl import AVLNode, AVL
class RangeNode(AVLNode):
"""Implementation of a RangeNode
A RangeNode is also a node in an order
statistics tree
"""
def __init__(self, key):
AVLNode.__init__(self, key)
self.tree_size = 1
def update_subtree_info(self):
AVLNode.update_subtree_info(self)
self.tree_size = se... | pset3/rangetree.py | from avl import AVLNode, AVL
class RangeNode(AVLNode):
"""Implementation of a RangeNode
A RangeNode is also a node in an order
statistics tree
"""
def __init__(self, key):
AVLNode.__init__(self, key)
self.tree_size = 1
def update_subtree_info(self):
AVLNode.update_subtree_info(self)
self.tree_size = se... | 0.711732 | 0.459258 |
import os
import sys
import time
import traceback
import requests
from requests.adapters import HTTPAdapter
from urllib3.util.retry import Retry
from ctools.utils import read_file, save_file
from .base_comm_actor import BaseCommActor
class FlaskFileSystemActor(BaseCommActor):
def __init__(self, cfg: dict) -> N... | ctools/worker/actor/comm/flask_fs_actor.py | import os
import sys
import time
import traceback
import requests
from requests.adapters import HTTPAdapter
from urllib3.util.retry import Retry
from ctools.utils import read_file, save_file
from .base_comm_actor import BaseCommActor
class FlaskFileSystemActor(BaseCommActor):
def __init__(self, cfg: dict) -> N... | 0.206894 | 0.08318 |
import pyaisnmea.binary as binary
import pyaisnmea.messages.aismessage
class Type21AidToNavigation(pyaisnmea.messages.aismessage.AISMessage):
"""
Type 21 message for Aids to Navigation
sent out by navigations aids such as buoys and lighthouses to report their
position
Attributes:
aidtyp... | pyaisnmea/messages/t21.py | import pyaisnmea.binary as binary
import pyaisnmea.messages.aismessage
class Type21AidToNavigation(pyaisnmea.messages.aismessage.AISMessage):
"""
Type 21 message for Aids to Navigation
sent out by navigations aids such as buoys and lighthouses to report their
position
Attributes:
aidtyp... | 0.799325 | 0.504211 |
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence
import numpy as np
class Model(nn.Module):
def __init__(self, args):
super(Model, self).__init__()
if args['embedding_pretrained'] is not None:
se... | textgo/classifier/TextRNN_Att.py |
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence
import numpy as np
class Model(nn.Module):
def __init__(self, args):
super(Model, self).__init__()
if args['embedding_pretrained'] is not None:
se... | 0.92976 | 0.380068 |
from unittest.mock import patch
from glances_api import Glances
from homeassistant.components.glances import config_flow
from homeassistant.components.glances.const import DOMAIN
from homeassistant.const import CONF_SCAN_INTERVAL
from tests.common import MockConfigEntry, mock_coro
NAME = "Glances"
HOST = "0.0.0.0"
... | tests/components/glances/test_config_flow.py | from unittest.mock import patch
from glances_api import Glances
from homeassistant.components.glances import config_flow
from homeassistant.components.glances.const import DOMAIN
from homeassistant.const import CONF_SCAN_INTERVAL
from tests.common import MockConfigEntry, mock_coro
NAME = "Glances"
HOST = "0.0.0.0"
... | 0.758511 | 0.336781 |
import maya.cmds as cmds
#most of the companies use classes to utilize as namespace
class SJ_OptionWindow(object): #object: fundamental object in python
def __init__(self): #initalize #self를 지정하지 않게 되면, 지역변수화가 된다.
self.window="optionWindow"
self.title="First Window"
self.size=(540,320)
... | Chapter 04. GUI/GUI_class.py | import maya.cmds as cmds
#most of the companies use classes to utilize as namespace
class SJ_OptionWindow(object): #object: fundamental object in python
def __init__(self): #initalize #self를 지정하지 않게 되면, 지역변수화가 된다.
self.window="optionWindow"
self.title="First Window"
self.size=(540,320)
... | 0.24899 | 0.144692 |
from fastapi import APIRouter, Depends
from apps.climsoft.services import stationlocationhistory_service
from apps.climsoft.schemas import stationlocationhistory_schema
from utils.response import get_success_response, get_error_response
from apps.climsoft.db.engine import SessionLocal
from sqlalchemy.orm.session import... | src/apps/climsoft/controllers/stationlocationhistory_controller.py | from fastapi import APIRouter, Depends
from apps.climsoft.services import stationlocationhistory_service
from apps.climsoft.schemas import stationlocationhistory_schema
from utils.response import get_success_response, get_error_response
from apps.climsoft.db.engine import SessionLocal
from sqlalchemy.orm.session import... | 0.393385 | 0.138258 |
from cement.core import controller
from decanter import app, cli
from decanter.admin import create_app
from decanter.cli import InstallDBController, CreateRoleController, CreateUserController
class RootController(cli.RootController):
class Meta:
label = 'base'
description = "Management tools for ... | data/test/python/e5c82175e7f7e4a3b681b68a9bd072092e2f3b20manage.py | from cement.core import controller
from decanter import app, cli
from decanter.admin import create_app
from decanter.cli import InstallDBController, CreateRoleController, CreateUserController
class RootController(cli.RootController):
class Meta:
label = 'base'
description = "Management tools for ... | 0.591133 | 0.07946 |
from multiprocessing import cpu_count
from sys import exit
from os import remove
def exiter():
print('INVALID ANSWER...')
exit(1)
return
def intro():
mssg_0 = """
--------------------------------------------------------------------------------------------------------------------
...Hi. Welcome to Peat, the I... | peat/setup.py | from multiprocessing import cpu_count
from sys import exit
from os import remove
def exiter():
print('INVALID ANSWER...')
exit(1)
return
def intro():
mssg_0 = """
--------------------------------------------------------------------------------------------------------------------
...Hi. Welcome to Peat, the I... | 0.239527 | 0.295382 |
import msgpack
import numpy as np
from warnings import warn
from . types import Channel, Camera
from . codecs import create_decoder, StreamPacket, Packet, PacketFlags
class FTLStreamReader:
""" FTL file reader. """
def __init__(self, file, max_buffer_size=64*2**20):
self._file = open(file, "br")
... | SDK/Python/ftl/streamreader.py | import msgpack
import numpy as np
from warnings import warn
from . types import Channel, Camera
from . codecs import create_decoder, StreamPacket, Packet, PacketFlags
class FTLStreamReader:
""" FTL file reader. """
def __init__(self, file, max_buffer_size=64*2**20):
self._file = open(file, "br")
... | 0.519278 | 0.110735 |
import os
import sys
import time
import socket
import datetime
from pandajedi.jedicore import Interaction
from pandajedi.jedicore import JediCoreUtils
from pandajedi.jedicore.MsgWrapper import MsgWrapper
from pandajedi.jedicore.FactoryBase import FactoryBase
from .JediKnight import JediKnight
from pandajedi.jediconfig... | pandajedi/jediorder/WatchDog.py | import os
import sys
import time
import socket
import datetime
from pandajedi.jedicore import Interaction
from pandajedi.jedicore import JediCoreUtils
from pandajedi.jedicore.MsgWrapper import MsgWrapper
from pandajedi.jedicore.FactoryBase import FactoryBase
from .JediKnight import JediKnight
from pandajedi.jediconfig... | 0.201106 | 0.050847 |
#类和对象
#系统类型多态
from random import choice
x = choice(['Hello, world', [1, 2, 'e', 'e', 4]])
print x
print x.count('e')
def lenth_message(x):
print 'The lenth of %s is %s' % (repr(x), len(x))
lenth_message('Fnord')
lenth_message([1, 2, 3])
#类
#新式类
__metaclass__ = type
class Person:
def setName(self, name):
... | python-7.py |
#类和对象
#系统类型多态
from random import choice
x = choice(['Hello, world', [1, 2, 'e', 'e', 4]])
print x
print x.count('e')
def lenth_message(x):
print 'The lenth of %s is %s' % (repr(x), len(x))
lenth_message('Fnord')
lenth_message([1, 2, 3])
#类
#新式类
__metaclass__ = type
class Person:
def setName(self, name):
... | 0.209066 | 0.276025 |
import numpy as np
import scipy.signal
import scipy.ndimage.morphology
def ipol_nearest(src, trg, data):
tree = scipy.spatial.cKDTree(src)
dists, ix = tree.query(trg, k=1)
return data[ix]
def compute_spinchange(data, window=(11, 21)):
spin = np.abs(np.diff(data, axis=1)) > 2
spin = np.column_stack... | steiner_smith.py | import numpy as np
import scipy.signal
import scipy.ndimage.morphology
def ipol_nearest(src, trg, data):
tree = scipy.spatial.cKDTree(src)
dists, ix = tree.query(trg, k=1)
return data[ix]
def compute_spinchange(data, window=(11, 21)):
spin = np.abs(np.diff(data, axis=1)) > 2
spin = np.column_stack... | 0.607547 | 0.512327 |
import os
import subprocess
from flask.helpers import locked_cached_property
class Git(object):
def __init__(self, base_path, payload, git_cmd=None):
self.base_path = base_path
self.payload = payload
self.git_cmd = git_cmd
if self.git_cmd is None:
try:
... | github_repo_mirror/git.py | import os
import subprocess
from flask.helpers import locked_cached_property
class Git(object):
def __init__(self, base_path, payload, git_cmd=None):
self.base_path = base_path
self.payload = payload
self.git_cmd = git_cmd
if self.git_cmd is None:
try:
... | 0.182717 | 0.043467 |
import pylewm.commands
import pylewm.window
import pylewm.monitors
import pythoncom
import win32gui, win32com.client
import win32api
import traceback
import ctypes
from pylewm.commands import PyleCommand
FocusQueue = pylewm.commands.CommandQueue()
FocusSpace = None
FocusWindow = None
LastFocusWindow = None
WindowFoc... | pylewm/focus.py | import pylewm.commands
import pylewm.window
import pylewm.monitors
import pythoncom
import win32gui, win32com.client
import win32api
import traceback
import ctypes
from pylewm.commands import PyleCommand
FocusQueue = pylewm.commands.CommandQueue()
FocusSpace = None
FocusWindow = None
LastFocusWindow = None
WindowFoc... | 0.265119 | 0.089733 |
from math import nan, inf
from pathlib import Path
from sqlite3 import Connection
import networkx as nx
import numpy as np
import pandas as pd
import pytest
from cascade.model import (
Session, Model, DismodGroups, SmoothGrid, Var, Covariate,
Uniform, Gaussian
)
from cascade.stats.compartmental import siler_d... | tests/model/test_model.py | from math import nan, inf
from pathlib import Path
from sqlite3 import Connection
import networkx as nx
import numpy as np
import pandas as pd
import pytest
from cascade.model import (
Session, Model, DismodGroups, SmoothGrid, Var, Covariate,
Uniform, Gaussian
)
from cascade.stats.compartmental import siler_d... | 0.768473 | 0.512327 |
from floodsystem.utils import sorted_by_key
def stations_level_over_threshold(stations,tol):
over_threshold_list=[] #empty list
for station in stations:
if station.relative_water_level() is not None:
if station.relative_water_level() >= tol:
over_threshold_list.append... | floodsystem/flood.py | from floodsystem.utils import sorted_by_key
def stations_level_over_threshold(stations,tol):
over_threshold_list=[] #empty list
for station in stations:
if station.relative_water_level() is not None:
if station.relative_water_level() >= tol:
over_threshold_list.append... | 0.593138 | 0.484258 |
import subprocess
import time
def get_proxy_ip():
bash_command = "bash ../cluster/get-node-ip.sh proxy"
process = subprocess.Popen(bash_command.split(), stdout=subprocess.PIPE)
output, error = process.communicate()
ip = output.decode('ascii').replace('\n', '')
return ip
def get_topic_owner(topic):... | Pulsar/automated/gather_info_functions.py | import subprocess
import time
def get_proxy_ip():
bash_command = "bash ../cluster/get-node-ip.sh proxy"
process = subprocess.Popen(bash_command.split(), stdout=subprocess.PIPE)
output, error = process.communicate()
ip = output.decode('ascii').replace('\n', '')
return ip
def get_topic_owner(topic):... | 0.267313 | 0.093347 |
"""Validate all integrations have manifests and that they are valid."""
import json
import pathlib
import sys
import voluptuous as vol
from voluptuous.humanize import humanize_error
MANIFEST_SCHEMA = vol.Schema({
vol.Required('domain'): str,
vol.Required('name'): str,
vol.Required('documentation'): str,
... | script/manifest/validate.py | """Validate all integrations have manifests and that they are valid."""
import json
import pathlib
import sys
import voluptuous as vol
from voluptuous.humanize import humanize_error
MANIFEST_SCHEMA = vol.Schema({
vol.Required('domain'): str,
vol.Required('name'): str,
vol.Required('documentation'): str,
... | 0.479991 | 0.241199 |
from ._debitnote import DebitNote as _DebitNote
from ._decimal import create_decimal as _create_decimal
__all__ = ["CreditNote"]
class CreditNote:
"""This class holds all of the information about a completed credit. This
is combined with a debit note of equal value to form a transaction
record
... | Acquire/Accounting/_creditnote.py | from ._debitnote import DebitNote as _DebitNote
from ._decimal import create_decimal as _create_decimal
__all__ = ["CreditNote"]
class CreditNote:
"""This class holds all of the information about a completed credit. This
is combined with a debit note of equal value to form a transaction
record
... | 0.753013 | 0.445349 |
from csclient import EventingCSClient
import json
def ping(host, **kwargs):
"""
:param host: string
destination IP address to ping
:param kwargs:
"num": number of pings to send. Default is 4
"srcaddr": source IP address. If blank NCOS uses primary WAN.
:return:
dict {... | ping_sample/ping_sample.py |
from csclient import EventingCSClient
import json
def ping(host, **kwargs):
"""
:param host: string
destination IP address to ping
:param kwargs:
"num": number of pings to send. Default is 4
"srcaddr": source IP address. If blank NCOS uses primary WAN.
:return:
dict {... | 0.54577 | 0.245209 |
import argparse
from parser_table import *
from lex import LexScanner
class LRParser(object):
def __init__(self, scanner):
self.FINISH = True
self.NONE = "NONE"
self.GOAL_RULE = GOAL_RULE
self.EOF = "EOF"
self.parsing_table = ParsingTable
self.left_symbol = LeftSy... | parser.py | import argparse
from parser_table import *
from lex import LexScanner
class LRParser(object):
def __init__(self, scanner):
self.FINISH = True
self.NONE = "NONE"
self.GOAL_RULE = GOAL_RULE
self.EOF = "EOF"
self.parsing_table = ParsingTable
self.left_symbol = LeftSy... | 0.371137 | 0.159283 |
from PyQt5 import QtCore, QtGui, QtWidgets
from TreeChildren import *
scanned = []
class Ui_MainWindow(object):
def setupUi(self, MainWindow):
MainWindow.setObjectName("MainWindow")
MainWindow.resize(800, 675)
self.centralwidget = QtWidgets.QWidget(MainWindow)
self.centralwidget.se... | Node Children Getter (GUI)/TreeChildrenGUI.pyw | from PyQt5 import QtCore, QtGui, QtWidgets
from TreeChildren import *
scanned = []
class Ui_MainWindow(object):
def setupUi(self, MainWindow):
MainWindow.setObjectName("MainWindow")
MainWindow.resize(800, 675)
self.centralwidget = QtWidgets.QWidget(MainWindow)
self.centralwidget.se... | 0.401453 | 0.090374 |
import math
import pprint
import random
import logging
import numpy as np
from typing import *
from tqdm import tqdm
from functools import partial
from collections import defaultdict
from abc import abstractmethod, ABCMeta
from ..utils import *
from ...misc import *
from ..param_utils import *
from ...dist import Pa... | cftool/ml/hpo/base.py | import math
import pprint
import random
import logging
import numpy as np
from typing import *
from tqdm import tqdm
from functools import partial
from collections import defaultdict
from abc import abstractmethod, ABCMeta
from ..utils import *
from ...misc import *
from ..param_utils import *
from ...dist import Pa... | 0.757436 | 0.193948 |
load("//fuzzing/private:binary.bzl", "FuzzingBinaryInfo")
load("//fuzzing/private:util.bzl", "runfile_path")
def _oss_fuzz_package_impl(ctx):
output_archive = ctx.actions.declare_file(ctx.label.name + ".tar")
binary_info = ctx.attr.binary[FuzzingBinaryInfo]
binary_runfiles = binary_info.binary_runfiles.fi... | fuzzing/private/oss_fuzz/package.bzl | load("//fuzzing/private:binary.bzl", "FuzzingBinaryInfo")
load("//fuzzing/private:util.bzl", "runfile_path")
def _oss_fuzz_package_impl(ctx):
output_archive = ctx.actions.declare_file(ctx.label.name + ".tar")
binary_info = ctx.attr.binary[FuzzingBinaryInfo]
binary_runfiles = binary_info.binary_runfiles.fi... | 0.347094 | 0.112162 |
from pathlib import Path
from smarts.sstudio import types as t
from smarts.sstudio import gen_scenario
import argparse
import sys
def get_args(args):
parser = argparse.ArgumentParser(description='smarts', formatter_class=argparse.RawDescriptionHelpFormatter)
parser.add_argument('--num_agents', type=int, defa... | onpolicy/envs/smarts/SMARTS/scenarios/straight/scenario.py | from pathlib import Path
from smarts.sstudio import types as t
from smarts.sstudio import gen_scenario
import argparse
import sys
def get_args(args):
parser = argparse.ArgumentParser(description='smarts', formatter_class=argparse.RawDescriptionHelpFormatter)
parser.add_argument('--num_agents', type=int, defa... | 0.572125 | 0.297476 |
__author__ = "Hua777"
__copyright__ = "Copyright 2018, Hua777"
__version__ = "2.0"
__email__ = "<EMAIL>"
from flask import Flask, jsonify, request, make_response, render_template, redirect, url_for
import traceback as TB
import os as OS
import requests as REQ
import time
from Agent import Agent
from Schedule import ... | Web.py |
__author__ = "Hua777"
__copyright__ = "Copyright 2018, Hua777"
__version__ = "2.0"
__email__ = "<EMAIL>"
from flask import Flask, jsonify, request, make_response, render_template, redirect, url_for
import traceback as TB
import os as OS
import requests as REQ
import time
from Agent import Agent
from Schedule import ... | 0.25174 | 0.054752 |
import numpy as np
import torch
import matplotlib.pyplot as plt
def run_runtime_seg(model, test_set, exp_name, S):
X_test = list(test_set)[0][0].cuda()
model.eval()
#First forward pass, ignore
time_list = []
for _ in range(100 + 1):
end = model.predict_runtime(X_test, S)
time_list.append(end)
time_list = np.... | isic2018_segmentation/lib/utils/fvi_seg_utils.py | import numpy as np
import torch
import matplotlib.pyplot as plt
def run_runtime_seg(model, test_set, exp_name, S):
X_test = list(test_set)[0][0].cuda()
model.eval()
#First forward pass, ignore
time_list = []
for _ in range(100 + 1):
end = model.predict_runtime(X_test, S)
time_list.append(end)
time_list = np.... | 0.436622 | 0.411909 |
import numpy as np
from matplotlib.figure import Figure
from .c_bilayer import F2FiveGaussSymmetricHeadBilayer
from ..core import FitFunction
class FiveGaussianSymmetricHeadBilayer(FitFunction):
name = 'Bilayer with guests'
description = 'Symmetric head bilayer with inner and outer bilayers'
arguments ... | src/saxsfittool/fitfunction/bilayer/bilayer.py | import numpy as np
from matplotlib.figure import Figure
from .c_bilayer import F2FiveGaussSymmetricHeadBilayer
from ..core import FitFunction
class FiveGaussianSymmetricHeadBilayer(FitFunction):
name = 'Bilayer with guests'
description = 'Symmetric head bilayer with inner and outer bilayers'
arguments ... | 0.842637 | 0.658802 |
"""Client and server classes corresponding to protobuf-defined services."""
import grpc
import middleware_pb2 as middleware__pb2
class MiddlewareStub(object):
"""This extends the Fred client for more convenient functions.
"""
def __init__(self, channel):
"""Constructor.
Args:
... | proto/middleware/middleware_pb2_grpc.py | """Client and server classes corresponding to protobuf-defined services."""
import grpc
import middleware_pb2 as middleware__pb2
class MiddlewareStub(object):
"""This extends the Fred client for more convenient functions.
"""
def __init__(self, channel):
"""Constructor.
Args:
... | 0.82386 | 0.106784 |
import os
import argparse
here = os.path.dirname(os.path.abspath(__file__))
dataset = 'small'
default_pretrained_model_path = os.path.join(here, '../pretrained_models/bert-base-chinese')
default_train_file = os.path.join(here, '../datasets/{}/train.jsonl'.format(dataset))
default_validation_file = os.path.join(here,... | relation_extraction/hparams.py | import os
import argparse
here = os.path.dirname(os.path.abspath(__file__))
dataset = 'small'
default_pretrained_model_path = os.path.join(here, '../pretrained_models/bert-base-chinese')
default_train_file = os.path.join(here, '../datasets/{}/train.jsonl'.format(dataset))
default_validation_file = os.path.join(here,... | 0.279632 | 0.068787 |
from fractions import Fraction
import numpy as np
import cypari # pylint: disable=import-error
from .base_algebraic import BaseRealNumberField, BaseRealAlgebraic
cp = cypari.pari
cp_x = cp('x')
def cp_polynomial(coefficients):
''' Return a cypari polynomial from its coefficients. '''
return cp(' + '.join('{... | realalg/cypari_algebraic.py |
from fractions import Fraction
import numpy as np
import cypari # pylint: disable=import-error
from .base_algebraic import BaseRealNumberField, BaseRealAlgebraic
cp = cypari.pari
cp_x = cp('x')
def cp_polynomial(coefficients):
''' Return a cypari polynomial from its coefficients. '''
return cp(' + '.join('{... | 0.810028 | 0.406067 |
from __future__ import unicode_literals
import datetime
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='Item',
fields=[
... | poll/migrations/0001_initial.py | from __future__ import unicode_literals
import datetime
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='Item',
fields=[
... | 0.585931 | 0.128936 |
from setup import *
def get_general_ts_all(test_type):
"""
A generic function used to get all the rows of a specific general touchscreen test. After the csv is generated, it
will ask for the user to save the file in a directory. Used for Habituation 1 and 2, Initial Touch, Must Touch,
and Mus... | general_touchscreen.py | from setup import *
def get_general_ts_all(test_type):
"""
A generic function used to get all the rows of a specific general touchscreen test. After the csv is generated, it
will ask for the user to save the file in a directory. Used for Habituation 1 and 2, Initial Touch, Must Touch,
and Mus... | 0.608827 | 0.482002 |
import enum
import re
import shlex
import string
import typing
from src import EventManager, IRCLine, ModuleManager, utils
from . import outs
COMMAND_METHOD = "command-method"
COMMAND_METHODS = ["PRIVMSG", "NOTICE"]
STR_MORE = " (more...)"
STR_MORE_LEN = len(STR_MORE.encode("utf8"))
STR_CONTINUED = "(...continued)... | src/core_modules/commands/__init__.py |
import enum
import re
import shlex
import string
import typing
from src import EventManager, IRCLine, ModuleManager, utils
from . import outs
COMMAND_METHOD = "command-method"
COMMAND_METHODS = ["PRIVMSG", "NOTICE"]
STR_MORE = " (more...)"
STR_MORE_LEN = len(STR_MORE.encode("utf8"))
STR_CONTINUED = "(...continued)... | 0.479504 | 0.090133 |
from typing import List
import backend.database_wrapper as dbw
from backend.communication_utils import *
from backend.models import Clip
from .serialization import *
from django.utils.timezone import utc
def modify_filter(data: dict) -> (int, dict):
"""
Modifies a given filter based on the given parameters, ... | backend/filter_module.py | from typing import List
import backend.database_wrapper as dbw
from backend.communication_utils import *
from backend.models import Clip
from .serialization import *
from django.utils.timezone import utc
def modify_filter(data: dict) -> (int, dict):
"""
Modifies a given filter based on the given parameters, ... | 0.725065 | 0.417568 |
"""Wrappers on TensorFlow initializers, to ease object serialization."""
import math
import six
import tensorflow as tf
from madoka import config
__all__ = [
'Initializer', 'Constant', 'Uniform', 'Normal', 'TruncatedNormal',
'XavierNormal', 'XavierUniform',
]
class Initializer(object):
"""Base class f... | madoka/nn/init.py | """Wrappers on TensorFlow initializers, to ease object serialization."""
import math
import six
import tensorflow as tf
from madoka import config
__all__ = [
'Initializer', 'Constant', 'Uniform', 'Normal', 'TruncatedNormal',
'XavierNormal', 'XavierUniform',
]
class Initializer(object):
"""Base class f... | 0.956644 | 0.434341 |
from _pytest.monkeypatch import resolve
import pytest
import json
from dotenv import load_dotenv
from pathlib import Path
from requests.models import Response
from src.common.dns_creator import DNSCreator
from ibm_cloud_networking_services.dns_records_v1 import DnsRecordsV1
from ibm_cloud_sdk_core.detailed_response imp... | tests/test_dns_creator.py | from _pytest.monkeypatch import resolve
import pytest
import json
from dotenv import load_dotenv
from pathlib import Path
from requests.models import Response
from src.common.dns_creator import DNSCreator
from ibm_cloud_networking_services.dns_records_v1 import DnsRecordsV1
from ibm_cloud_sdk_core.detailed_response imp... | 0.655005 | 0.23709 |
import csv
import os
import cv2
import sklearn
import numpy as np
from sklearn.utils import shuffle
#Read the data file and append each row
lines = []
with open('data/driving_log.csv', 'r') as csvfile:
reader = csv.reader(csvfile)
for line in reader:
lines.append(line)
#Split data into t... | model.py | import csv
import os
import cv2
import sklearn
import numpy as np
from sklearn.utils import shuffle
#Read the data file and append each row
lines = []
with open('data/driving_log.csv', 'r') as csvfile:
reader = csv.reader(csvfile)
for line in reader:
lines.append(line)
#Split data into t... | 0.524395 | 0.472257 |
from src.raid.raid_controller import RaidController
from src.disk import Disk
from src.galois_field import GaloisField
import numpy as np
import concurrent.futures
from src.util import Logger
import math
from copy import deepcopy
class RAID_6(RaidController):
"""
RADI 6 controller, inherited from Raid Contro... | src/raid/raid_6.py |
from src.raid.raid_controller import RaidController
from src.disk import Disk
from src.galois_field import GaloisField
import numpy as np
import concurrent.futures
from src.util import Logger
import math
from copy import deepcopy
class RAID_6(RaidController):
"""
RADI 6 controller, inherited from Raid Contro... | 0.695338 | 0.334644 |
import os
import re
import time
import socket
import inspect
import threading
import subprocess
import logger
gsmThreadName = 'gsmReceptor'
gprsThreadName = 'gprsReceptor'
wifiThreadName = 'wifiReceptor'
emailThreadName = 'emailReceptor'
ethernetThreadName = 'ethernetReceptor'
bluetoothThreadName = 'bluetoothRecepto... | controllerClass.py |
import os
import re
import time
import socket
import inspect
import threading
import subprocess
import logger
gsmThreadName = 'gsmReceptor'
gprsThreadName = 'gprsReceptor'
wifiThreadName = 'wifiReceptor'
emailThreadName = 'emailReceptor'
ethernetThreadName = 'ethernetReceptor'
bluetoothThreadName = 'bluetoothRecepto... | 0.214609 | 0.078113 |
from pathlib import Path
import optuna
import torch
from torch import nn, optim
from torch.utils.data import random_split
from src.models.Classifier import Classifier
from src.models.Hyperparameters import Hyperparameters as hp
def objective(trial):
LEARNING_RATE = trial.suggest_loguniform("LEARNING_RATE", low=... | src/models/Optuna_tuning.py | from pathlib import Path
import optuna
import torch
from torch import nn, optim
from torch.utils.data import random_split
from src.models.Classifier import Classifier
from src.models.Hyperparameters import Hyperparameters as hp
def objective(trial):
LEARNING_RATE = trial.suggest_loguniform("LEARNING_RATE", low=... | 0.841011 | 0.41182 |
from logging import warning
from multiprocessing import Process
from dashserve.serializer import DashAppSerializer
def runner(serialized_app, host, port, **kwargs):
serializer = DashAppSerializer()
app = serializer.deserialize(serialized_app)
app.run_server(host=host, port=port, **kwargs)
class Jupyter... | dashserve/server.py | from logging import warning
from multiprocessing import Process
from dashserve.serializer import DashAppSerializer
def runner(serialized_app, host, port, **kwargs):
serializer = DashAppSerializer()
app = serializer.deserialize(serialized_app)
app.run_server(host=host, port=port, **kwargs)
class Jupyter... | 0.787196 | 0.059401 |
import FWCore.ParameterSet.Config as cms
process = cms.Process("tester")
process.load("FWCore.MessageLogger.MessageLogger_cfi")
process.MessageLogger.cout.enable = cms.untracked.bool(True)
process.MessageLogger.cout.threshold = cms.untracked.string('DEBUG')
process.MessageLogger.debugModules = cms.untracked.vstring('*... | L1TriggerConfig/Utilities/test/uploadBmtfParams.py | import FWCore.ParameterSet.Config as cms
process = cms.Process("tester")
process.load("FWCore.MessageLogger.MessageLogger_cfi")
process.MessageLogger.cout.enable = cms.untracked.bool(True)
process.MessageLogger.cout.threshold = cms.untracked.string('DEBUG')
process.MessageLogger.debugModules = cms.untracked.vstring('*... | 0.308086 | 0.080864 |
''' mapper of pangerank algorithm'''
import sys
import numpy as np
import os
sys.path.append('/home/dsjxtjc/2018211149/')
from mapreduce.map_reduce import partition, combine, finish
def map(string_data_path, reduce_num, map_id):
id1 = id2 = None
heros = value = None
count1 = count2 = 0
result = []... | job_statistic/pagerank.py |
''' mapper of pangerank algorithm'''
import sys
import numpy as np
import os
sys.path.append('/home/dsjxtjc/2018211149/')
from mapreduce.map_reduce import partition, combine, finish
def map(string_data_path, reduce_num, map_id):
id1 = id2 = None
heros = value = None
count1 = count2 = 0
result = []... | 0.128635 | 0.263525 |
from rest_framework import serializers
from django.contrib.auth import get_user_model
from .models import (Document, Category, Author, Download, DocumentDetail,
Subscription, Payment, UserSubscription)
class UserSerializer(serializers.ModelSerializer):
class Meta:
model = get_user_mod... | app/documents/serializers.py | from rest_framework import serializers
from django.contrib.auth import get_user_model
from .models import (Document, Category, Author, Download, DocumentDetail,
Subscription, Payment, UserSubscription)
class UserSerializer(serializers.ModelSerializer):
class Meta:
model = get_user_mod... | 0.663996 | 0.151624 |
import george
import numpy as np
import scipy.optimize as spo
from justice.affine_xform import Aff, transform
from justice.lightcurve import LC, merge
def lineup(lca, lcb):
# optimize the lining up for GP and arclen
# do this on coarse grid, then refine
pass
def connect_the_dots(lc):
# ignores err... | justice/summarize.py |
import george
import numpy as np
import scipy.optimize as spo
from justice.affine_xform import Aff, transform
from justice.lightcurve import LC, merge
def lineup(lca, lcb):
# optimize the lining up for GP and arclen
# do this on coarse grid, then refine
pass
def connect_the_dots(lc):
# ignores err... | 0.46952 | 0.39563 |
import uos
import uarray
import errno
import ffilib
R_OK = const(4)
W_OK = const(2)
X_OK = const(1)
F_OK = const(0)
O_ACCMODE = const(0o0000003)
O_RDONLY = const(0o0000000)
O_WRONLY = const(0o0000001)
O_RDWR = const(0o0000002)
O_CREAT = const(0o0000100)
O_EXCL = const(0o0000200)
O_NOCTTY = const(0... | uos2/uos2.py |
import uos
import uarray
import errno
import ffilib
R_OK = const(4)
W_OK = const(2)
X_OK = const(1)
F_OK = const(0)
O_ACCMODE = const(0o0000003)
O_RDONLY = const(0o0000000)
O_WRONLY = const(0o0000001)
O_RDWR = const(0o0000002)
O_CREAT = const(0o0000100)
O_EXCL = const(0o0000200)
O_NOCTTY = const(0... | 0.302185 | 0.095814 |
import uuid
from django.conf import settings
from django.core.validators import RegexValidator
from django.db import models
from django.utils.translation import gettext_lazy as _
from pinkle.utils.utility_func import wsi_confidence
# Create your models here.
# https://github.com/EatEmAll/django-djeddit/blob/d5b988c... | pinkle/models.py | import uuid
from django.conf import settings
from django.core.validators import RegexValidator
from django.db import models
from django.utils.translation import gettext_lazy as _
from pinkle.utils.utility_func import wsi_confidence
# Create your models here.
# https://github.com/EatEmAll/django-djeddit/blob/d5b988c... | 0.697712 | 0.14817 |
import pygame
from pygame.locals import *
import os
class zFilter:
def __init__(self,hair,eye,nose,foot):
self.features={"hair":hair,"eye":eye,"nose":nose,"foot":foot}
for feature in self.features.keys():
trait=self.features[feature]
if trait == "blank" or trait=="rotator" o... | Zoombinis/mirror_machine_analyzer.py | import pygame
from pygame.locals import *
import os
class zFilter:
def __init__(self,hair,eye,nose,foot):
self.features={"hair":hair,"eye":eye,"nose":nose,"foot":foot}
for feature in self.features.keys():
trait=self.features[feature]
if trait == "blank" or trait=="rotator" o... | 0.191177 | 0.206314 |
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LogisticRegression
from sklearn.metrics import f1_score
from batchmanager import BatchManager
from joblib import Parallel, delayed
import scipy
import numpy as np
def n_labeled_data(x_set, y_set, sample_size, dataset_names):
me... | src/evaluate_n_labeled.py | from sklearn.model_selection import train_test_split
from sklearn.linear_model import LogisticRegression
from sklearn.metrics import f1_score
from batchmanager import BatchManager
from joblib import Parallel, delayed
import scipy
import numpy as np
def n_labeled_data(x_set, y_set, sample_size, dataset_names):
me... | 0.502686 | 0.535584 |
import random
import re
from math import pi
gate_set_cirq = ["cirq.H","cirq.X","cirq.Y","cirq.Z","cirq.rx","cirq.CNOT","cirq.SWAP"]
gate_set_qiskit = ["prog.h","prog.x","prog.y","prog.z","prog.rx","prog.cx","prog.swap"]
gate_set_pyquil = ["prog += H(", "prog += X(","prog += Y(", "prog += Z(","prog += RX(", "prog += ... | mutation/Mutation_diff.py |
import random
import re
from math import pi
gate_set_cirq = ["cirq.H","cirq.X","cirq.Y","cirq.Z","cirq.rx","cirq.CNOT","cirq.SWAP"]
gate_set_qiskit = ["prog.h","prog.x","prog.y","prog.z","prog.rx","prog.cx","prog.swap"]
gate_set_pyquil = ["prog += H(", "prog += X(","prog += Y(", "prog += Z(","prog += RX(", "prog += ... | 0.223801 | 0.212314 |
import pygame
import time
import random
import numpy as np
import re
# initializing the game
pygame.init()
# size of the display window
display_width = 800
display_height = 600
# to change the speed of the blocks
speed = 7
# setting up the game window size
gameDisplay = pygame.display.set_mode((disp... | automation.py | import pygame
import time
import random
import numpy as np
import re
# initializing the game
pygame.init()
# size of the display window
display_width = 800
display_height = 600
# to change the speed of the blocks
speed = 7
# setting up the game window size
gameDisplay = pygame.display.set_mode((disp... | 0.057098 | 0.126569 |
import os
from sgtk.platform.qt import QtCore, QtGui
class ShotgunSearchWidget(QtGui.QLineEdit):
"""
A QT Widget deriving from :class:`~PySide.QtGui.QLineEdit` that creates
a search input box with auto completion.
The derived classes are expected to provide a :class:`PySide.QtGui.QCompleter`
dur... | install/app_store/tk-framework-qtwidgets/v2.6.6/python/shotgun_search_widget/shotgun_search_widget.py |
import os
from sgtk.platform.qt import QtCore, QtGui
class ShotgunSearchWidget(QtGui.QLineEdit):
"""
A QT Widget deriving from :class:`~PySide.QtGui.QLineEdit` that creates
a search input box with auto completion.
The derived classes are expected to provide a :class:`PySide.QtGui.QCompleter`
dur... | 0.621771 | 0.248375 |
import base64
import copy
import json
import random
import time
from textwrap import dedent
import netaddr
import requests
from jumpscale.clients.explorer.models import DeployedReservation, NextAction
from jumpscale.clients.stellar import TRANSACTION_FEES
from jumpscale.clients.stellar.stellar import Network as Stella... | jumpscale/sals/reservation_chatflow/reservation_chatflow.py | import base64
import copy
import json
import random
import time
from textwrap import dedent
import netaddr
import requests
from jumpscale.clients.explorer.models import DeployedReservation, NextAction
from jumpscale.clients.stellar import TRANSACTION_FEES
from jumpscale.clients.stellar.stellar import Network as Stella... | 0.720663 | 0.123128 |
import math
import os
import magnum as mn
import numpy as np
import habitat_sim
from habitat_sim.utils import viz_utils as vut
dir_path = os.path.dirname(os.path.realpath(__file__))
data_path = os.path.join(dir_path, "../../data")
output_path = os.path.join(dir_path, "VHACD_tutorial_output/")
if not os.path.exists(... | examples/tutorials/VHACD_tutorial.py | import math
import os
import magnum as mn
import numpy as np
import habitat_sim
from habitat_sim.utils import viz_utils as vut
dir_path = os.path.dirname(os.path.realpath(__file__))
data_path = os.path.join(dir_path, "../../data")
output_path = os.path.join(dir_path, "VHACD_tutorial_output/")
if not os.path.exists(... | 0.562177 | 0.280167 |