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 __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
import time
from cleverhans.attacks import MultiModelIterativeMethod
import numpy as np
from PIL import Image
import tensorflow as tf
from tensorflow.contrib.slim.nets import inception
import incep... | winners/nontargeted-attack/teaflow/attack_iter.py |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
import time
from cleverhans.attacks import MultiModelIterativeMethod
import numpy as np
from PIL import Image
import tensorflow as tf
from tensorflow.contrib.slim.nets import inception
import incep... | 0.881417 | 0.361616 |
import bpy
import os
data = bpy.context.active_object.data
name = bpy.context.active_object.name
# Extract vertex color information. Translate color into a bitfield
# so that exact colors do not matter.
vert_colors = {}
for i in range(0, len(data.vertex_colors[0].data)):
r = int(data.vertex_colors[0].data[i].colo... | tools/blend_to_struct.py | import bpy
import os
data = bpy.context.active_object.data
name = bpy.context.active_object.name
# Extract vertex color information. Translate color into a bitfield
# so that exact colors do not matter.
vert_colors = {}
for i in range(0, len(data.vertex_colors[0].data)):
r = int(data.vertex_colors[0].data[i].colo... | 0.429788 | 0.41253 |
from flask import Flask
from decision_tree import DecisionTree
import json
from flask import request
from flask import render_template
import random
import sys
__author__ = "fatRabit"
__version__ = 1.6
app = Flask(__name__)
#The p_tree,which stored in P_TREE.txt, is a decison
#tree which decide how to prevent the... | BetaMeow/ai.py | from flask import Flask
from decision_tree import DecisionTree
import json
from flask import request
from flask import render_template
import random
import sys
__author__ = "fatRabit"
__version__ = 1.6
app = Flask(__name__)
#The p_tree,which stored in P_TREE.txt, is a decison
#tree which decide how to prevent the... | 0.293506 | 0.363845 |
from bs4 import BeautifulSoup
from selenium import webdriver
from selenium.webdriver.chrome.service import Service
from webdriver_manager.chrome import ChromeDriverManager
import time
import logging
logging.basicConfig(filename="/var/log/python-log/rain-read-log", filemode="w", level=logging.DEBUG, format='%(asctime)... | Backend/water_fall.py | from bs4 import BeautifulSoup
from selenium import webdriver
from selenium.webdriver.chrome.service import Service
from webdriver_manager.chrome import ChromeDriverManager
import time
import logging
logging.basicConfig(filename="/var/log/python-log/rain-read-log", filemode="w", level=logging.DEBUG, format='%(asctime)... | 0.28587 | 0.139631 |
import logging
import traceback
from fastapi import APIRouter, Cookie, HTTPException, Request, Response
from httpx import AsyncClient
from starlette.responses import RedirectResponse
from pixels.constants import Discord, Server
from pixels.utils import auth
log = logging.getLogger(__name__)
router = APIRouter(includ... | pixels/endpoints/authorization.py | import logging
import traceback
from fastapi import APIRouter, Cookie, HTTPException, Request, Response
from httpx import AsyncClient
from starlette.responses import RedirectResponse
from pixels.constants import Discord, Server
from pixels.utils import auth
log = logging.getLogger(__name__)
router = APIRouter(includ... | 0.682468 | 0.083516 |
from sqlalchemy import Column, create_engine, orm, types
from sqlalchemy.ext.declarative import declarative_base
from django.http import Http404
from django.test import SimpleTestCase
from rest_framework.test import APIRequestFactory
from rest_witchcraft import serializers, viewsets
factory = APIRequestFactory()
... | tests/test_generics.py | from sqlalchemy import Column, create_engine, orm, types
from sqlalchemy.ext.declarative import declarative_base
from django.http import Http404
from django.test import SimpleTestCase
from rest_framework.test import APIRequestFactory
from rest_witchcraft import serializers, viewsets
factory = APIRequestFactory()
... | 0.562177 | 0.266662 |
import argparse
import numpy as np
import torch
import os
import sys
import IPython
import logging
sys.path.append("..")
import time
import IPython
from rlmamr.my_env.osd_ma_single_room import ObjSearchDelivery_v4 as OSD_S_4
from rlmamr.MA_cen_condi_ddrqn.utils.utils import Linear_Decay, get_conditional_argmax, get_c... | test/test_osd_s_policy.py | import argparse
import numpy as np
import torch
import os
import sys
import IPython
import logging
sys.path.append("..")
import time
import IPython
from rlmamr.my_env.osd_ma_single_room import ObjSearchDelivery_v4 as OSD_S_4
from rlmamr.MA_cen_condi_ddrqn.utils.utils import Linear_Decay, get_conditional_argmax, get_c... | 0.32146 | 0.181844 |
import sys
import code
import re
from typing import Callable
from contextlib import redirect_stdout, redirect_stderr
from PyQt5.QtCore import *
from PyQt5.QtGui import *
from PyQt5.QtWidgets import *
class LineEdit(QLineEdit):
"""QLIneEdit with a history buffer for recalling previous lines.
I also accept tab... | vvs_app/Terminal_Test.py | import sys
import code
import re
from typing import Callable
from contextlib import redirect_stdout, redirect_stderr
from PyQt5.QtCore import *
from PyQt5.QtGui import *
from PyQt5.QtWidgets import *
class LineEdit(QLineEdit):
"""QLIneEdit with a history buffer for recalling previous lines.
I also accept tab... | 0.561215 | 0.155687 |
import requests
import json
import re
from scraper import Scraper
from house import House
from bs4 import BeautifulSoup
class BeumerUtrecht(Scraper):
url = 'https://beumerutrecht.nl/woningen/'
def getPossiblePrices(self) -> list[int]:
return [
75000,
100000,
150000... | scrapers/beumerutrecht.py | import requests
import json
import re
from scraper import Scraper
from house import House
from bs4 import BeautifulSoup
class BeumerUtrecht(Scraper):
url = 'https://beumerutrecht.nl/woningen/'
def getPossiblePrices(self) -> list[int]:
return [
75000,
100000,
150000... | 0.308607 | 0.113555 |
from csv import reader
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import datetime
from collections import Counter
class JobData(object):
"""JobData class for working with data from CSV file."""
def __init__(self, environment=None):
"""Initialize instance of JobData with ne... | src/job_data.py | from csv import reader
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import datetime
from collections import Counter
class JobData(object):
"""JobData class for working with data from CSV file."""
def __init__(self, environment=None):
"""Initialize instance of JobData with ne... | 0.660501 | 0.349089 |
from docsisMon.ipDevices import ipDevice
from docsisMon.mibs import mibs
class Cmts(ipDevice):
""" Represents a CMTS: This is a inheritance from ipDevice
public methods and attributes:
- ipMngmt: Device Ip management
- snmpIf: SNMP InterFace used to get all the infomation
- getCm... | docsisMon/cmtsDevices.py | from docsisMon.ipDevices import ipDevice
from docsisMon.mibs import mibs
class Cmts(ipDevice):
""" Represents a CMTS: This is a inheritance from ipDevice
public methods and attributes:
- ipMngmt: Device Ip management
- snmpIf: SNMP InterFace used to get all the infomation
- getCm... | 0.434101 | 0.155719 |
from itertools import chain
import time
import os
import math
from tornado_sqlalchemy import as_future
from tornado.gen import multi
from PIL import Image, ImageDraw, ImageColor, ImageFont
from models import DotaProPlayer, DotaHeroes, DotaItem, DotaProTeam
from image_generation.helpers import draw_text_outl... | backend/api/image_generation/mixins/post_game.py | from itertools import chain
import time
import os
import math
from tornado_sqlalchemy import as_future
from tornado.gen import multi
from PIL import Image, ImageDraw, ImageColor, ImageFont
from models import DotaProPlayer, DotaHeroes, DotaItem, DotaProTeam
from image_generation.helpers import draw_text_outl... | 0.314471 | 0.064418 |
import os, xml.dom.minidom, unicodedata, shutil, glob
cldrnames = {}
_document = xml.dom.minidom.parse("CLDR/annotations/en.xml")
for _i in _document.getElementsByTagName("annotation"):
if _i.hasAttribute("type") and _i.getAttribute("type") == "tts":
cldrnames[_i.getAttribute("cp")] = _i.firstChild.wholeT... | generate_names.py |
import os, xml.dom.minidom, unicodedata, shutil, glob
cldrnames = {}
_document = xml.dom.minidom.parse("CLDR/annotations/en.xml")
for _i in _document.getElementsByTagName("annotation"):
if _i.hasAttribute("type") and _i.getAttribute("type") == "tts":
cldrnames[_i.getAttribute("cp")] = _i.firstChild.wholeT... | 0.128116 | 0.094177 |
import torch
from torch import nn
class BatchNormConv1d(nn.Module):
r"""A wrapper for Conv1d with BatchNorm. It sets the activation
function between Conv and BatchNorm layers. BatchNorm layer
is initialized with the TF default values for momentum and eps.
Args:
in_channels: size of each input... | cn_tacotron/cbgh.py | import torch
from torch import nn
class BatchNormConv1d(nn.Module):
r"""A wrapper for Conv1d with BatchNorm. It sets the activation
function between Conv and BatchNorm layers. BatchNorm layer
is initialized with the TF default values for momentum and eps.
Args:
in_channels: size of each input... | 0.838316 | 0.648209 |
import pytest
def test_audit_antibody_mismatched_in_review(testapp,
base_antibody_characterization,
inconsistent_biosample_type):
characterization_review_list = base_antibody_characterization.get('characterization_reviews')
... | src/encoded/tests/test_audit_antibody_characterization.py | import pytest
def test_audit_antibody_mismatched_in_review(testapp,
base_antibody_characterization,
inconsistent_biosample_type):
characterization_review_list = base_antibody_characterization.get('characterization_reviews')
... | 0.389547 | 0.274353 |
# imported necessary library
import tkinter
from tkinter import *
import tkinter as tk
import tkinter.messagebox as mbox
import re
# created main window
window = Tk()
window.geometry("1000x700")
window.title("Credit Card Numbers Authentication")
# ------------------ this is for adding gif image in the main window o... | GUIScripts/Credit Card Numbers Authentication/credit_card_numbers_authentication.py |
# imported necessary library
import tkinter
from tkinter import *
import tkinter as tk
import tkinter.messagebox as mbox
import re
# created main window
window = Tk()
window.geometry("1000x700")
window.title("Credit Card Numbers Authentication")
# ------------------ this is for adding gif image in the main window o... | 0.441191 | 0.15633 |
import inspect
from collections import namedtuple
from operator import attrgetter
import znc
Command = namedtuple("Command", "name func min_args max_args syntax help_msg include_cmd admin")
def command(name, min_args=0, max_args=None, syntax=None, help_msg=None, include_cmd=False, admin=False):
def _decorate(fu... | snoomodule.py | import inspect
from collections import namedtuple
from operator import attrgetter
import znc
Command = namedtuple("Command", "name func min_args max_args syntax help_msg include_cmd admin")
def command(name, min_args=0, max_args=None, syntax=None, help_msg=None, include_cmd=False, admin=False):
def _decorate(fu... | 0.456894 | 0.066782 |
__author__ = '<NAME>'
from pandas import (
concat,
read_csv,
Series
)
from sklearn.tree import DecisionTreeClassifier
class Titanic(object):
titanic_data = None
def __init__(self, titanic_csv):
self.titanic_data = read_csv(titanic_csv, index_col='PassengerId')
def _percents(self, ... | titanic/__init__.py |
__author__ = '<NAME>'
from pandas import (
concat,
read_csv,
Series
)
from sklearn.tree import DecisionTreeClassifier
class Titanic(object):
titanic_data = None
def __init__(self, titanic_csv):
self.titanic_data = read_csv(titanic_csv, index_col='PassengerId')
def _percents(self, ... | 0.725746 | 0.332812 |
import posixpath
import re
import six
import zipfile2
from attr import attr, attributes
from attr.validators import instance_of, optional
from okonomiyaki.errors import (
InvalidRequirementString, InvalidRequirementStringHyphen,
InvalidEggName, InvalidMetadataField,
MissingMetadata, UnsupportedMetadata)
... | okonomiyaki/file_formats/_egg_info.py | import posixpath
import re
import six
import zipfile2
from attr import attr, attributes
from attr.validators import instance_of, optional
from okonomiyaki.errors import (
InvalidRequirementString, InvalidRequirementStringHyphen,
InvalidEggName, InvalidMetadataField,
MissingMetadata, UnsupportedMetadata)
... | 0.540924 | 0.084909 |
import pandas as pd
from datetime import datetime
from datetime import timedelta
ESSENCE = ['EventID', 'TimeWritten']
class EventProc:
def __init__(self):
raw_data = pd.read_csv(r'static/logon_rhythm.csv', header=1, encoding='utf-8')
self.df = pd.DataFrame(raw_data, columns=ESSENCE)
self.... | evt_proc.py |
import pandas as pd
from datetime import datetime
from datetime import timedelta
ESSENCE = ['EventID', 'TimeWritten']
class EventProc:
def __init__(self):
raw_data = pd.read_csv(r'static/logon_rhythm.csv', header=1, encoding='utf-8')
self.df = pd.DataFrame(raw_data, columns=ESSENCE)
self.... | 0.441191 | 0.166472 |
from math import *
import Spheral
import mpi
#-------------------------------------------------------------------------------
# A class for tracking the history of a given set of nodes.
#-------------------------------------------------------------------------------
class NodeHistory:
def __init__(self,
... | src/SimulationControl/NodeHistory.py | from math import *
import Spheral
import mpi
#-------------------------------------------------------------------------------
# A class for tracking the history of a given set of nodes.
#-------------------------------------------------------------------------------
class NodeHistory:
def __init__(self,
... | 0.672547 | 0.314794 |
import copy
import operator
import warnings
import re
from sentinels import NOTHING
from six import (
iteritems,
itervalues,
string_types,
)
from .__version__ import __version__
try:
from bson import ObjectId
except ImportError:
from .object_... | mongomock/__init__.py | import copy
import operator
import warnings
import re
from sentinels import NOTHING
from six import (
iteritems,
itervalues,
string_types,
)
from .__version__ import __version__
try:
from bson import ObjectId
except ImportError:
from .object_... | 0.499756 | 0.118998 |
from datetime import timedelta
from traceback import format_exc
from mesh.exceptions import *
from scheme import current_timestamp
from spire.schema import *
from spire.support.logs import LogHelper
from sqlalchemy.ext.associationproxy import association_proxy
from sqlalchemy.orm.collections import attribute_mapped_co... | platoon/models/process.py | from datetime import timedelta
from traceback import format_exc
from mesh.exceptions import *
from scheme import current_timestamp
from spire.schema import *
from spire.support.logs import LogHelper
from sqlalchemy.ext.associationproxy import association_proxy
from sqlalchemy.orm.collections import attribute_mapped_co... | 0.701406 | 0.118436 |
from absl.testing import parameterized
import tensorflow as tf
import tensorflow_federated as tff
from data_poor_fl import hypcluster_train
def create_dataset():
# Create data satisfying y = x + 1
x = [[1.0], [2.0], [3.0]]
y = [[2.0], [3.0], [4.0]]
return tf.data.Dataset.from_tensor_slices((x, y)).batch(1)
... | data_poor_fl/hypcluster_train_test.py |
from absl.testing import parameterized
import tensorflow as tf
import tensorflow_federated as tff
from data_poor_fl import hypcluster_train
def create_dataset():
# Create data satisfying y = x + 1
x = [[1.0], [2.0], [3.0]]
y = [[2.0], [3.0], [4.0]]
return tf.data.Dataset.from_tensor_slices((x, y)).batch(1)
... | 0.843734 | 0.543469 |
import taichi as ti
import bounds3
from bounds3 import Bounds3
import sphere
from sphere import Sphere
import triangle
from triangle import Triangle
import material
from utils import FMAX
from tqdm import tqdm
import time
BVHNode = ti.types.struct(
bounds=Bounds3,
left=ti.i32,
right=ti.i32,
obj_type=t... | BVH.py | import taichi as ti
import bounds3
from bounds3 import Bounds3
import sphere
from sphere import Sphere
import triangle
from triangle import Triangle
import material
from utils import FMAX
from tqdm import tqdm
import time
BVHNode = ti.types.struct(
bounds=Bounds3,
left=ti.i32,
right=ti.i32,
obj_type=t... | 0.612773 | 0.271057 |
from gui import Animation
from d_star_lite import DStarLite
from grid import OccupancyGridMap, SLAM
OBSTACLE = 255
UNOCCUPIED = 0
if __name__ == '__main__':
"""
set initial values for the map occupancy grid
|----------> y, column
| (x=0,y=2)
|
V (x=2, y=0)
x, row
"""
x_d... | python/python/main.py | from gui import Animation
from d_star_lite import DStarLite
from grid import OccupancyGridMap, SLAM
OBSTACLE = 255
UNOCCUPIED = 0
if __name__ == '__main__':
"""
set initial values for the map occupancy grid
|----------> y, column
| (x=0,y=2)
|
V (x=2, y=0)
x, row
"""
x_d... | 0.513912 | 0.226185 |
import os
from collections import OrderedDict, deque
from datetime import datetime, date
from enum import Enum, IntEnum
from scripts import SmartJson
class Test:
def __init__(self):
self.name = "test"
self.date = datetime.now()
self.list = ["is list item", 1, datetime.now()]
self.... | example.py | import os
from collections import OrderedDict, deque
from datetime import datetime, date
from enum import Enum, IntEnum
from scripts import SmartJson
class Test:
def __init__(self):
self.name = "test"
self.date = datetime.now()
self.list = ["is list item", 1, datetime.now()]
self.... | 0.436862 | 0.276639 |
import os
from urllib.request import urlretrieve, urlopen
import time
from datetime import datetime, timedelta
import pytz
import tqdm
# Import data science packages
import numpy as np
import pandas as pd
# Import reddit related packages
import praw
import pdb
import re
# Import Google NLP API
from google.cloud impo... | Preprocessing/reddit.py | import os
from urllib.request import urlretrieve, urlopen
import time
from datetime import datetime, timedelta
import pytz
import tqdm
# Import data science packages
import numpy as np
import pandas as pd
# Import reddit related packages
import praw
import pdb
import re
# Import Google NLP API
from google.cloud impo... | 0.426083 | 0.381076 |
import logging
import threading
import os
import json
from time import time, sleep
import cv2
from src.common.timestamp import get_timestamp
from src.shell.shell import Shell
from src.configuration.shell_configuration import LocalShellConfiguration
from src.data_chunks.data_chunk_data import DataChunkImage
from src.co... | src/shell/local_shell.py | import logging
import threading
import os
import json
from time import time, sleep
import cv2
from src.common.timestamp import get_timestamp
from src.shell.shell import Shell
from src.configuration.shell_configuration import LocalShellConfiguration
from src.data_chunks.data_chunk_data import DataChunkImage
from src.co... | 0.555676 | 0.116337 |
import datetime
from ruv_dl.data import Entry, EntrySet, Episode
def test_entry_from_dict():
data = {
'fn': 'some_fn',
'url': 'some_url',
'date': '2017/06/14',
'etag': 'some_etag',
'episode': {'id': 'some_episode'},
}
e = Entry.from_dict(data)
assert e.fn == da... | tests/test_data.py | import datetime
from ruv_dl.data import Entry, EntrySet, Episode
def test_entry_from_dict():
data = {
'fn': 'some_fn',
'url': 'some_url',
'date': '2017/06/14',
'etag': 'some_etag',
'episode': {'id': 'some_episode'},
}
e = Entry.from_dict(data)
assert e.fn == da... | 0.444324 | 0.354014 |
from usermgnt.data import data_adapter as data_adapter
from usermgnt.common import common as common
from usermgnt.common.logs import LOG
# Profile content:
# {
# "device_id": "device/11111111d",
# "service_consumer": boolean,
# "resource_contributor": boolean
# }
# get_user_profile_by_id: Get use... | usermgnt/modules/um_profiling.py | from usermgnt.data import data_adapter as data_adapter
from usermgnt.common import common as common
from usermgnt.common.logs import LOG
# Profile content:
# {
# "device_id": "device/11111111d",
# "service_consumer": boolean,
# "resource_contributor": boolean
# }
# get_user_profile_by_id: Get use... | 0.384334 | 0.179999 |
import numpy as np
import pandas as pd
from scipy.spatial import Voronoi, ConvexHull
import signature.calculations as calc
from functools import partial
class MixedCrystalSignature:
"""Class for calculation of the Mixed Crystal Signature
Description in https://doi.org/10.1103/PhysRevE.96.011301"""
L_VEC ... | mixedcrystalsignature.py | import numpy as np
import pandas as pd
from scipy.spatial import Voronoi, ConvexHull
import signature.calculations as calc
from functools import partial
class MixedCrystalSignature:
"""Class for calculation of the Mixed Crystal Signature
Description in https://doi.org/10.1103/PhysRevE.96.011301"""
L_VEC ... | 0.678859 | 0.306054 |
import socket
class UkbSession:
def __init__(self, port, server = "localhost"):
self.buffer_size = 16384
self.buffer = None
self.a = 0
self.b = 0
try:
self.socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
self.socket.connect((socket.gethost... | src/ukb/contrib/python-server/ukbprotocol.py |
import socket
class UkbSession:
def __init__(self, port, server = "localhost"):
self.buffer_size = 16384
self.buffer = None
self.a = 0
self.b = 0
try:
self.socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
self.socket.connect((socket.gethost... | 0.372163 | 0.165728 |
from __future__ import absolute_import
# Import Salt libs
import salt.config
import salt.exceptions
import salt.utils.http
from salt.exceptions import SaltInvocationError
# Import 3rd-party libs
import salt.ext.six.moves.http_client
from salt.ext import six
from salt.ext.six.moves.urllib.parse import urljoin as _urlj... | gitlab.py | from __future__ import absolute_import
# Import Salt libs
import salt.config
import salt.exceptions
import salt.utils.http
from salt.exceptions import SaltInvocationError
# Import 3rd-party libs
import salt.ext.six.moves.http_client
from salt.ext import six
from salt.ext.six.moves.urllib.parse import urljoin as _urlj... | 0.612541 | 0.066146 |
import asyncio
import dataclasses
import enum
from typing import List, Iterable, Optional
import dataclasses_json
from ... import json_rpc
from . import async_server_connection
class ServerNotInitializedError(json_rpc.JSONRPCException):
def error_code(self) -> int:
return -32002
class RequestCancelle... | client/commands/v2/language_server_protocol.py |
import asyncio
import dataclasses
import enum
from typing import List, Iterable, Optional
import dataclasses_json
from ... import json_rpc
from . import async_server_connection
class ServerNotInitializedError(json_rpc.JSONRPCException):
def error_code(self) -> int:
return -32002
class RequestCancelle... | 0.831109 | 0.13852 |
import tkinter as tk
import webbrowser as wb
from datetime import datetime, timedelta
from logging import getLogger, basicConfig, Formatter, WARNING
from logging.handlers import RotatingFileHandler
from operator import itemgetter
from os import getenv
from time import sleep
from schedule import every, run_pen... | notifReminder.py | import tkinter as tk
import webbrowser as wb
from datetime import datetime, timedelta
from logging import getLogger, basicConfig, Formatter, WARNING
from logging.handlers import RotatingFileHandler
from operator import itemgetter
from os import getenv
from time import sleep
from schedule import every, run_pen... | 0.225076 | 0.058453 |
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.colors import ListedColormap, BoundaryNorm
from collections import OrderedDict
from matplotlib.animation import FuncAnimation
from gym import utils
import sys
from six import StringIO, b
from IPython.display import HTML
COLORS = OrderedDict([
(b"W... | blg604ehw1/env/render.py | import numpy as np
import matplotlib.pyplot as plt
from matplotlib.colors import ListedColormap, BoundaryNorm
from collections import OrderedDict
from matplotlib.animation import FuncAnimation
from gym import utils
import sys
from six import StringIO, b
from IPython.display import HTML
COLORS = OrderedDict([
(b"W... | 0.606149 | 0.606615 |
import tensorflow as tf
import numpy as np
from sklearn.model_selection import train_test_split
import os
import torch
from torch import nn
from torch.utils.data import DataLoader
from torchvision import datasets
from torchvision.transforms import ToTensor, Lambda, Compose
import matplotlib.pyplot as plt
import numpy a... | gavPrj/tf_vs_trch/cv_image_tensorFlow_vs_pytorch.py | import tensorflow as tf
import numpy as np
from sklearn.model_selection import train_test_split
import os
import torch
from torch import nn
from torch.utils.data import DataLoader
from torchvision import datasets
from torchvision.transforms import ToTensor, Lambda, Compose
import matplotlib.pyplot as plt
import numpy a... | 0.406744 | 0.628806 |
import matplotlib.image as mpimg
import matplotlib.pyplot as plt
import numpy as np
from scipy import signal
class CoreFrame:
def __init__(self, core_width=3, core_height=3):
self.width = core_width
self.height = core_height
def random_mat(self):
return np.random.random((self.height, ... | Convolution_test.py | import matplotlib.image as mpimg
import matplotlib.pyplot as plt
import numpy as np
from scipy import signal
class CoreFrame:
def __init__(self, core_width=3, core_height=3):
self.width = core_width
self.height = core_height
def random_mat(self):
return np.random.random((self.height, ... | 0.532425 | 0.418519 |
import pygame, sys, random, math, time
import constants
from buttons import draw_rect
from buttons import button_hover
from buttons import button_press
from buttons import text
# Randomly generates obstacles - draws them red and returns the coordinates of them
def random_fill(x, y, w, p):
obstacle = (... | visualization.py |
import pygame, sys, random, math, time
import constants
from buttons import draw_rect
from buttons import button_hover
from buttons import button_press
from buttons import text
# Randomly generates obstacles - draws them red and returns the coordinates of them
def random_fill(x, y, w, p):
obstacle = (... | 0.278257 | 0.38578 |
from django.db import models
from django.db import models
from django.contrib.auth.models import User
from django.db.models.signals import post_save
from django.dispatch import receiver
import datetime as dt
class Hood(models.Model):
name = models.CharField(max_length=200)
location = models.CharField(max_lengt... | app/models.py | from django.db import models
from django.db import models
from django.contrib.auth.models import User
from django.db.models.signals import post_save
from django.dispatch import receiver
import datetime as dt
class Hood(models.Model):
name = models.CharField(max_length=200)
location = models.CharField(max_lengt... | 0.526343 | 0.108095 |
from __future__ import annotations
import enum
import logging
import ssl
from collections.abc import Sequence
from dataclasses import dataclass, field
from datetime import datetime
from pathlib import Path
from types import TracebackType
from typing import Any
import aiohttp
from dateutil.parser import parse
from neu... | platform_reports/kube_client.py | from __future__ import annotations
import enum
import logging
import ssl
from collections.abc import Sequence
from dataclasses import dataclass, field
from datetime import datetime
from pathlib import Path
from types import TracebackType
from typing import Any
import aiohttp
from dateutil.parser import parse
from neu... | 0.801625 | 0.129788 |
import os
from os.path import join as pjoin
import collections
import glob
import numpy as np
import scipy.io as io
import matplotlib.pyplot as plt
from PIL import Image
from tqdm import tqdm
from torch.utils import data
from pysmg.data.transforms import default_transforms
class PascalVOC(data.Dataset):
"""Dat... | pysmg/data/pascal_voc.py | import os
from os.path import join as pjoin
import collections
import glob
import numpy as np
import scipy.io as io
import matplotlib.pyplot as plt
from PIL import Image
from tqdm import tqdm
from torch.utils import data
from pysmg.data.transforms import default_transforms
class PascalVOC(data.Dataset):
"""Dat... | 0.785555 | 0.599397 |
import os
import json
import argparse
from dateutil.parser import parse
from datetime import date, datetime, timedelta
from github import Github, BadCredentialsException
SCRIPT_FOLDER = 'git-tools'
CONFIG_FILENAME = 'daily-report.json'
parser = argparse.ArgumentParser(
description="Show daily activity on GitHub... | daily-report.py | import os
import json
import argparse
from dateutil.parser import parse
from datetime import date, datetime, timedelta
from github import Github, BadCredentialsException
SCRIPT_FOLDER = 'git-tools'
CONFIG_FILENAME = 'daily-report.json'
parser = argparse.ArgumentParser(
description="Show daily activity on GitHub... | 0.140189 | 0.05744 |
import torch
import argparse
import torchvision
import torch.nn as nn
from torch.autograd import Function
from model.base_model import Base_Model
class CIBHash(Base_Model):
def __init__(self, hparams):
super().__init__(hparams=hparams)
def define_parameters(self):
self.vgg = torc... | model/CIBHash.py | import torch
import argparse
import torchvision
import torch.nn as nn
from torch.autograd import Function
from model.base_model import Base_Model
class CIBHash(Base_Model):
def __init__(self, hparams):
super().__init__(hparams=hparams)
def define_parameters(self):
self.vgg = torc... | 0.891386 | 0.277085 |
from __future__ import with_statement
from __future__ import absolute_import
from __future__ import print_function
from collections import defaultdict
#typing
import pytest
import numpy
from allennlp.data import Token, Vocabulary
from allennlp.data.fields import TextField
from allennlp.data.token_indexers import Si... | pymagnitude/third_party/allennlp/tests/data/fields/text_field_test.py |
from __future__ import with_statement
from __future__ import absolute_import
from __future__ import print_function
from collections import defaultdict
#typing
import pytest
import numpy
from allennlp.data import Token, Vocabulary
from allennlp.data.fields import TextField
from allennlp.data.token_indexers import Si... | 0.713232 | 0.292693 |
import os
import sys
import shutil
import errno
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import glob
import scipy as sp
import scipy.stats
import csv
import logging
sns.set(style="darkgrid")
def delete_dirs(path_to_dir):
_logger = logging.getLogger(__name__)
... | helper.py | import os
import sys
import shutil
import errno
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import glob
import scipy as sp
import scipy.stats
import csv
import logging
sns.set(style="darkgrid")
def delete_dirs(path_to_dir):
_logger = logging.getLogger(__name__)
... | 0.228931 | 0.164483 |
from time import sleep
import logging
from flaky import flaky
import pytest
from swimpy.routes import ROUTES
from swimpy.model.message import Ping, Ack, PingReq, Alive
from swimpy.model.node import Node
from swimpy.runtime import Runtime
from swimpy.util import send_message
LOGGER = logging.getLogger(__name__)
@py... | test/test_integ.py | from time import sleep
import logging
from flaky import flaky
import pytest
from swimpy.routes import ROUTES
from swimpy.model.message import Ping, Ack, PingReq, Alive
from swimpy.model.node import Node
from swimpy.runtime import Runtime
from swimpy.util import send_message
LOGGER = logging.getLogger(__name__)
@py... | 0.418697 | 0.33482 |
from ....core.log.log import Log
from ....core.comm.comm_utils import CommUtils
from ....applications.garrus.image_control.image_control_messages import ImageData
from ....applications.garrus.image_control.image_control_messages import ImageModeSelect
from ...garrus.image_control.image_control_messages import COLOR
fro... | python/robot_controller/applications/gui/workspace/ws_image.py | from ....core.log.log import Log
from ....core.comm.comm_utils import CommUtils
from ....applications.garrus.image_control.image_control_messages import ImageData
from ....applications.garrus.image_control.image_control_messages import ImageModeSelect
from ...garrus.image_control.image_control_messages import COLOR
fro... | 0.486088 | 0.107531 |
"""test resolution of dotted names
"""
import unittest
class Test_resolve(unittest.TestCase):
def _callFUT(self, *args, **kw):
from zope.dottedname.resolve import resolve
return resolve(*args, **kw)
def test_no_dots_non_importable(self):
self.assertRaises(ImportError,
... | ven2/lib/python2.7/site-packages/zope/dottedname/tests.py | """test resolution of dotted names
"""
import unittest
class Test_resolve(unittest.TestCase):
def _callFUT(self, *args, **kw):
from zope.dottedname.resolve import resolve
return resolve(*args, **kw)
def test_no_dots_non_importable(self):
self.assertRaises(ImportError,
... | 0.516839 | 0.576363 |
import torch
import os
import numpy as np
import cv2
from PIL import Image
from csr_model import csr_network
import torchvision.transforms.functional as TF
import matplotlib.pyplot as plt
def csr_retouch(path_to_model_state, path_to_old_images, path_to_new_images):
cuda = torch.cuda.is_available()
Tensor = to... | image_retouching/csrnet/csr_eval.py | import torch
import os
import numpy as np
import cv2
from PIL import Image
from csr_model import csr_network
import torchvision.transforms.functional as TF
import matplotlib.pyplot as plt
def csr_retouch(path_to_model_state, path_to_old_images, path_to_new_images):
cuda = torch.cuda.is_available()
Tensor = to... | 0.42656 | 0.471162 |
from .. import db, flask_bcryp
from ..config import key
from app.main.model.tokens import Token
import jwt
import datetime
class User(db.Model):
"""User Model for storing user related details consider user as LMS"""
__tablename__ = 'user'
id = db.Column(db.Integer, primary_key=True, autoincrement=True)
... | app/main/model/user.py |
from .. import db, flask_bcryp
from ..config import key
from app.main.model.tokens import Token
import jwt
import datetime
class User(db.Model):
"""User Model for storing user related details consider user as LMS"""
__tablename__ = 'user'
id = db.Column(db.Integer, primary_key=True, autoincrement=True)
... | 0.569972 | 0.060335 |
from enum import Enum
from typing import Tuple, Union
import geopandas as gpd
import triangle
from .common import (
FloatArray,
IntArray,
check_geodataframe,
invalid_option,
repr,
separate,
to_ugrid,
)
from .triangle_geometry import collect_geometry, polygon_holes
class DelaunayAlgorithm... | pandamesh/triangle_mesher.py | from enum import Enum
from typing import Tuple, Union
import geopandas as gpd
import triangle
from .common import (
FloatArray,
IntArray,
check_geodataframe,
invalid_option,
repr,
separate,
to_ugrid,
)
from .triangle_geometry import collect_geometry, polygon_holes
class DelaunayAlgorithm... | 0.940415 | 0.513303 |
import torch
import torch.nn as nn
from torch.autograd import Variable
from torch.utils.data.dataset import Dataset
from torch.utils.data import DataLoader
import numpy as np
import utils
def format_data(data):
try:
return data.reshape((data.shape[0], 1)) if len(data.shape) == 1 else data
except At... | custom_dataset.py | import torch
import torch.nn as nn
from torch.autograd import Variable
from torch.utils.data.dataset import Dataset
from torch.utils.data import DataLoader
import numpy as np
import utils
def format_data(data):
try:
return data.reshape((data.shape[0], 1)) if len(data.shape) == 1 else data
except At... | 0.649134 | 0.430267 |
import os
import sys
from collections import OrderedDict
import ProbabilisticParser.common.tokens as tok
import pycrfsuite
try:
TAGGER = pycrfsuite.Tagger()
TAGGER.open(tok.MODEL_PATH + tok.MODEL_FILE)
print('Using model from', tok.MODEL_PATH + tok.MODEL_FILE)
except IOError:
print('ERROR: cannot find... | DataScience/ProbabilisticParser/parser.py | import os
import sys
from collections import OrderedDict
import ProbabilisticParser.common.tokens as tok
import pycrfsuite
try:
TAGGER = pycrfsuite.Tagger()
TAGGER.open(tok.MODEL_PATH + tok.MODEL_FILE)
print('Using model from', tok.MODEL_PATH + tok.MODEL_FILE)
except IOError:
print('ERROR: cannot find... | 0.624064 | 0.677167 |
import re
import pandas as pd
import numpy as np
# When running this script first time
# Uncomment these two lines
import nltk
nltk.download('stopwords')
from nltk.tokenize import word_tokenize
from nltk.corpus import stopwords
stop_words = set(stopwords.words('english'))
from nltk.stem import PorterStemmer
pst = Po... | preprocessing/Preprocessing.py | import re
import pandas as pd
import numpy as np
# When running this script first time
# Uncomment these two lines
import nltk
nltk.download('stopwords')
from nltk.tokenize import word_tokenize
from nltk.corpus import stopwords
stop_words = set(stopwords.words('english'))
from nltk.stem import PorterStemmer
pst = Po... | 0.380989 | 0.173603 |
from flask import redirect, url_for, g, current_app, render_template, request
from maintain_frontend.decorators import requires_permission
from maintain_frontend.constants.permissions import Permissions
from maintain_frontend.send_payment_link.validation.payment_reason_validator import PaymentReasonValidator
def regi... | maintain_frontend/send_payment_link/payment_for.py | from flask import redirect, url_for, g, current_app, render_template, request
from maintain_frontend.decorators import requires_permission
from maintain_frontend.constants.permissions import Permissions
from maintain_frontend.send_payment_link.validation.payment_reason_validator import PaymentReasonValidator
def regi... | 0.474875 | 0.046313 |
import json
import os
import pickle
from ._utils import (
check_file,
load_graph,
check_available,
generate_session,
sentencepiece_tokenizer_bert,
sentencepiece_tokenizer_xlnet,
)
from .._models._sklearn_model import BINARY_BAYES, MULTICLASS_BAYES
from .._models._bert_model import MULTICLASS_BER... | malaya/_utils/_softmax_class.py | import json
import os
import pickle
from ._utils import (
check_file,
load_graph,
check_available,
generate_session,
sentencepiece_tokenizer_bert,
sentencepiece_tokenizer_xlnet,
)
from .._models._sklearn_model import BINARY_BAYES, MULTICLASS_BAYES
from .._models._bert_model import MULTICLASS_BER... | 0.361165 | 0.131814 |
import sys
import argparse
import logging
import time
from contextlib import closing
from dae.gpf_instance.gpf_instance import GPFInstance
from dae.backends.impala.impala_variants import ImpalaVariants
logger = logging.getLogger("impala_tables_stats")
def parse_cli_arguments(argv, gpf_instance):
parser = arg... | dae/dae/tools/impala_tables_stats.py | import sys
import argparse
import logging
import time
from contextlib import closing
from dae.gpf_instance.gpf_instance import GPFInstance
from dae.backends.impala.impala_variants import ImpalaVariants
logger = logging.getLogger("impala_tables_stats")
def parse_cli_arguments(argv, gpf_instance):
parser = arg... | 0.321141 | 0.125146 |
import sqlite3
import datetime
import logging
from typing import Union
from sqlite3 import Error
logger = logging.getLogger('marble_match.' + __name__)
def replace_char_list(_old: str, _replacement: list, _replace: str = '?') -> str:
for i in _replacement:
_old = _old.replace(_replace, str(i), 1)
... | marble_match/database/database_operation.py | import sqlite3
import datetime
import logging
from typing import Union
from sqlite3 import Error
logger = logging.getLogger('marble_match.' + __name__)
def replace_char_list(_old: str, _replacement: list, _replace: str = '?') -> str:
for i in _replacement:
_old = _old.replace(_replace, str(i), 1)
... | 0.389082 | 0.189352 |
from django.urls import path
from django.conf.urls import url
from . import views
urlpatterns = [
# ONBOARDING
path('', views.splash, name='splash'),
# location bot
path('location_bot', views.location_bot, name='location_bot'),
path('bot_api', views.bot_api, name='bot_api'),
# email collector ... | mvp/urls.py | from django.urls import path
from django.conf.urls import url
from . import views
urlpatterns = [
# ONBOARDING
path('', views.splash, name='splash'),
# location bot
path('location_bot', views.location_bot, name='location_bot'),
path('bot_api', views.bot_api, name='bot_api'),
# email collector ... | 0.315525 | 0.080864 |
import os
import re
from glob import glob
from typing import Callable, Iterable
from uuid import uuid4
from dotenv import load_dotenv
from orgparse import loads
from orgparse.node import OrgBaseNode
load_dotenv()
ORG_DIRECTORY = os.getenv("ORG_DIRECTORY")
ORGZLY_CUSTOM_ID_FILE = os.getenv("ORGZLY_CUSTOM_ID_FILE")
#... | link_translation.py | import os
import re
from glob import glob
from typing import Callable, Iterable
from uuid import uuid4
from dotenv import load_dotenv
from orgparse import loads
from orgparse.node import OrgBaseNode
load_dotenv()
ORG_DIRECTORY = os.getenv("ORG_DIRECTORY")
ORGZLY_CUSTOM_ID_FILE = os.getenv("ORGZLY_CUSTOM_ID_FILE")
#... | 0.655226 | 0.192122 |
__author__ = "ivallesp"
import os
import json
def _norm_path(path):
"""
Decorator function intended for using it to normalize a the output of a path retrieval function. Useful for
fixing the slash/backslash windows cases.
"""
def normalize_path(*args):
return os.path.normpath(path(*args))
... | src/common_paths.py | __author__ = "ivallesp"
import os
import json
def _norm_path(path):
"""
Decorator function intended for using it to normalize a the output of a path retrieval function. Useful for
fixing the slash/backslash windows cases.
"""
def normalize_path(*args):
return os.path.normpath(path(*args))
... | 0.624408 | 0.44734 |
from const import RACE_ID, HUM
from game import INF
import numpy as np
def evaluate_inf(board, race, race_ennemi):
'''heuristic function'''
sum_ = np.sum(board.grid, axis=(0, 1))
if sum_[RACE_ID[race]] == 0:
return -INF
elif sum_[RACE_ID[race_ennemi]] == 0:
return INF
else:
... | src/evaluation.py | from const import RACE_ID, HUM
from game import INF
import numpy as np
def evaluate_inf(board, race, race_ennemi):
'''heuristic function'''
sum_ = np.sum(board.grid, axis=(0, 1))
if sum_[RACE_ID[race]] == 0:
return -INF
elif sum_[RACE_ID[race_ennemi]] == 0:
return INF
else:
... | 0.640186 | 0.605158 |
import uuid
import django.db.models.deletion
from django.conf import settings
from django.db import migrations, models
class Migration(migrations.Migration):
initial = True
dependencies = [
("auth", "0012_alter_user_first_name_max_length"),
]
operations = [
migrations.CreateModel(... | dateflix_api/migrations/0001_initial.py |
import uuid
import django.db.models.deletion
from django.conf import settings
from django.db import migrations, models
class Migration(migrations.Migration):
initial = True
dependencies = [
("auth", "0012_alter_user_first_name_max_length"),
]
operations = [
migrations.CreateModel(... | 0.49292 | 0.157428 |
from collections import deque
def bfs(graph, start = None):
if(graph):
if(not start):
start = next(iter(graph))
explored_nodes = {}
dq = deque([start])
while(dq):
current_node = dq.popleft()
print(current_node)
if(current_node in explo... | Graph/graphSearch.py | from collections import deque
def bfs(graph, start = None):
if(graph):
if(not start):
start = next(iter(graph))
explored_nodes = {}
dq = deque([start])
while(dq):
current_node = dq.popleft()
print(current_node)
if(current_node in explo... | 0.324985 | 0.240931 |
import numpy as np
import sncosmo
import matplotlib.pyplot as plt
# read in spectrum from snfit, created with phase=0
wave, flux1 = np.loadtxt("src/snfit-2.4.2/src/testspec.dat", unpack=True)
z = 0.05
# adjust flux by a^2 for some reason. Why? What is the definition of
# "rest frame flux" in snfit?
flux1 *= 1. / (1... | compare_model_spec.py |
import numpy as np
import sncosmo
import matplotlib.pyplot as plt
# read in spectrum from snfit, created with phase=0
wave, flux1 = np.loadtxt("src/snfit-2.4.2/src/testspec.dat", unpack=True)
z = 0.05
# adjust flux by a^2 for some reason. Why? What is the definition of
# "rest frame flux" in snfit?
flux1 *= 1. / (1... | 0.547464 | 0.485539 |
import django.test
from snapshotServer.models import Snapshot, Application, Version, TestStep, \
TestSession, TestEnvironment, TestCase, TestCaseInSession, StepResult
import datetime
import pytz
from django.db.utils import IntegrityError
from snapshotServer.tests import SnapshotTestCase
class TestSnaps... | snapshotServer/tests/model/test_Snapshots.py | import django.test
from snapshotServer.models import Snapshot, Application, Version, TestStep, \
TestSession, TestEnvironment, TestCase, TestCaseInSession, StepResult
import datetime
import pytz
from django.db.utils import IntegrityError
from snapshotServer.tests import SnapshotTestCase
class TestSnaps... | 0.453988 | 0.224969 |
import scipy.io as sio
import numpy.linalg as LA
from utils import mse
import numpy as np
from utils_rbf import *
import warnings
warnings.filterwarnings("ignore")
result = np.array([]).reshape(0,1)
phi = "Gauss"
method = "RJSA"
for year in [2010, 2011, 2012, 2013, 2014]:
print(">>>>>")
data_name = "data{}"... | HW2/scripts/RBF.py |
import scipy.io as sio
import numpy.linalg as LA
from utils import mse
import numpy as np
from utils_rbf import *
import warnings
warnings.filterwarnings("ignore")
result = np.array([]).reshape(0,1)
phi = "Gauss"
method = "RJSA"
for year in [2010, 2011, 2012, 2013, 2014]:
print(">>>>>")
data_name = "data{}"... | 0.275422 | 0.358465 |
from saflow_params import FS_SUBJDIR, FOLDERPATH, SUBJ_LIST, BLOCS_LIST
import numpy as np
import os
import os.path as op
import mne
import scipy.io as sio
import h5py
from ephypype.import_data import write_hdf5
fwd_template = FOLDERPATH + '/sub-{subj}/ses-recording/meg/sub-{subj}_ses-recording_task-gradCPT_run-0{bloc... | scripts/saflow_morph.py | from saflow_params import FS_SUBJDIR, FOLDERPATH, SUBJ_LIST, BLOCS_LIST
import numpy as np
import os
import os.path as op
import mne
import scipy.io as sio
import h5py
from ephypype.import_data import write_hdf5
fwd_template = FOLDERPATH + '/sub-{subj}/ses-recording/meg/sub-{subj}_ses-recording_task-gradCPT_run-0{bloc... | 0.21036 | 0.099514 |
import csv
import os
from collections import Counter
from DemoV1 import get_txt_from_file_name
from age_gender_detect import age_gender_detect
Dic_Name = ["shot_1", "shot_2", "shot_3", "shot_4", "shot_5", "shot_6", "shot_7", "shot_8"]
All_shot_infor = []
uid_set = set()
for dic in Dic_Name:
shot_infor = []
di... | DemoV3_part1.py | import csv
import os
from collections import Counter
from DemoV1 import get_txt_from_file_name
from age_gender_detect import age_gender_detect
Dic_Name = ["shot_1", "shot_2", "shot_3", "shot_4", "shot_5", "shot_6", "shot_7", "shot_8"]
All_shot_infor = []
uid_set = set()
for dic in Dic_Name:
shot_infor = []
di... | 0.107087 | 0.106226 |
from Stream import *
from Operators import *
from examples_element_wrapper import print_stream
import numpy as np
from collections import namedtuple
from missing_data_multiple import *
from types import *
class Message():
def __init__(self, id, timestamp, content, category):
self.id = id
self.time... | Missing_Data_Section/missing_data_multiplestreams.py | from Stream import *
from Operators import *
from examples_element_wrapper import print_stream
import numpy as np
from collections import namedtuple
from missing_data_multiple import *
from types import *
class Message():
def __init__(self, id, timestamp, content, category):
self.id = id
self.time... | 0.498535 | 0.162347 |
import math
import torch
import torch.nn.functional as F
import numpy as np
import cv2
from timm.data.constants import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
import matplotlib.pyplot as plt
from torch_scatter import scatter_mean
imgs = torch.load('attns/images0.pt', map_location='cpu')
attns = torch.load('attns/... | attn_distribution.py | import math
import torch
import torch.nn.functional as F
import numpy as np
import cv2
from timm.data.constants import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
import matplotlib.pyplot as plt
from torch_scatter import scatter_mean
imgs = torch.load('attns/images0.pt', map_location='cpu')
attns = torch.load('attns/... | 0.426322 | 0.441071 |
from manga_py.provider import Provider
from .helpers.std import Std
class MangaPandaCom(Provider, Std):
_cdn = 'https://img.mghubcdn.com/file/imghub'
_api_url = 'https://api.mghubcdn.com/graphql'
def get_chapter_index(self) -> str:
return self.chapter_for_json()
def get_content(self):
... | manga_py/providers/mangapanda_onl.py | from manga_py.provider import Provider
from .helpers.std import Std
class MangaPandaCom(Provider, Std):
_cdn = 'https://img.mghubcdn.com/file/imghub'
_api_url = 'https://api.mghubcdn.com/graphql'
def get_chapter_index(self) -> str:
return self.chapter_for_json()
def get_content(self):
... | 0.434581 | 0.222288 |
import re
from discord import Member
from typing import Union, List, Dict, Pattern # Type hints
"""
Constants split into classes. Admin roles have extra information for rank comparison. Channels are combined into
lists in the Section class.
"""
class RePattern:
RP_NAME = re.compile("^[A-Z][a-z]+_[A-Z]{1,2}([a-z... | server/cmds/constants.py | import re
from discord import Member
from typing import Union, List, Dict, Pattern # Type hints
"""
Constants split into classes. Admin roles have extra information for rank comparison. Channels are combined into
lists in the Section class.
"""
class RePattern:
RP_NAME = re.compile("^[A-Z][a-z]+_[A-Z]{1,2}([a-z... | 0.636805 | 0.215702 |
from Utils.log_handler import log_to_console
from Application.Frame.port import Port
"""
Module handles the manipulation of transfer ports for the APPL block
"""
# Dictionaries to hold the transfer ports for each waves
portsDict = []
NR_WAVES = 0
ACTIVE_WAVE = 0
def create_ports_dict(nr_waves: int) -> ... | Application/Frame/transferJobPorts.py | from Utils.log_handler import log_to_console
from Application.Frame.port import Port
"""
Module handles the manipulation of transfer ports for the APPL block
"""
# Dictionaries to hold the transfer ports for each waves
portsDict = []
NR_WAVES = 0
ACTIVE_WAVE = 0
def create_ports_dict(nr_waves: int) -> ... | 0.473901 | 0.41324 |
import asyncio
import json
from prompt_toolkit.auto_suggest import AutoSuggestFromHistory
from prompt_toolkit.completion import WordCompleter
from prompt_toolkit.eventloop.defaults import use_asyncio_event_loop
from prompt_toolkit.patch_stdout import patch_stdout
from prompt_toolkit.shortcuts.prompt import PromptSessio... | app/console/console_client.py | import asyncio
import json
from prompt_toolkit.auto_suggest import AutoSuggestFromHistory
from prompt_toolkit.completion import WordCompleter
from prompt_toolkit.eventloop.defaults import use_asyncio_event_loop
from prompt_toolkit.patch_stdout import patch_stdout
from prompt_toolkit.shortcuts.prompt import PromptSessio... | 0.172416 | 0.04879 |
"""Tests for `schedule.py`."""
from absl.testing import absltest
from absl.testing import parameterized
import chex
import numpy as np
from optax._src import schedule
class ConstantTest(chex.TestCase):
@chex.all_variants()
def test_constant(self):
"""Check constant schedule."""
# Get schedule function... | optax/_src/schedule_test.py | """Tests for `schedule.py`."""
from absl.testing import absltest
from absl.testing import parameterized
import chex
import numpy as np
from optax._src import schedule
class ConstantTest(chex.TestCase):
@chex.all_variants()
def test_constant(self):
"""Check constant schedule."""
# Get schedule function... | 0.92029 | 0.817137 |
import numpy as np
import tensorflow as tf
def NLL(y_true, y_pred):
'''
Negative Log-Likelihood, see Section IV.B in the TCAN paper.
Parameters:
__________________________________
y_true: tf.Tensor.
Actual values of target time series, a tensor with shape (n_samples, n_targets) where n_sa... | tcan_tensorflow/losses.py | import numpy as np
import tensorflow as tf
def NLL(y_true, y_pred):
'''
Negative Log-Likelihood, see Section IV.B in the TCAN paper.
Parameters:
__________________________________
y_true: tf.Tensor.
Actual values of target time series, a tensor with shape (n_samples, n_targets) where n_sa... | 0.957447 | 0.670244 |
import warnings as wn
def gen_regdf(df):
"""Function to create the relevant dummy variables and interaction terms for the probit models.
Args:
dataFrame containing the categorial variables
Returns:
-------
A data frame containing the dummy variables a... | auxiliary/gen_regdf.py | import warnings as wn
def gen_regdf(df):
"""Function to create the relevant dummy variables and interaction terms for the probit models.
Args:
dataFrame containing the categorial variables
Returns:
-------
A data frame containing the dummy variables a... | 0.307878 | 0.358129 |
# ugly path patching
import sys
import os
sys.path.append(os.path.abspath(os.path.join(__file__, '..', 'lib')))
import base64
from proto.ved_pb2 import Ved
'''
The type of link encoded in the ved message. If you find out, what other values mean,
please either send me a pull request or comment in the article
(http... | ved.py |
# ugly path patching
import sys
import os
sys.path.append(os.path.abspath(os.path.join(__file__, '..', 'lib')))
import base64
from proto.ved_pb2 import Ved
'''
The type of link encoded in the ved message. If you find out, what other values mean,
please either send me a pull request or comment in the article
(http... | 0.253676 | 0.194406 |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import sys
import BTrees
from BTrees.Interfaces import IBTreeFamily
from BTrees.Interfaces import IBTreeModule
from zope import interface
__all__ = (
'MAX_LEAF_SIZE',
'MAX_INTERNAL_SIZE',
'family... | src/nti/zodb/btrees.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import sys
import BTrees
from BTrees.Interfaces import IBTreeFamily
from BTrees.Interfaces import IBTreeModule
from zope import interface
__all__ = (
'MAX_LEAF_SIZE',
'MAX_INTERNAL_SIZE',
'family... | 0.591605 | 0.076373 |
from models.cbba import CBBA
from models.ccbba import CCBBA
import logging
import time
from numpy.random import randint, choice, seed
from numpy import exp
from math import sqrt
import numpy as np
num_bases = 5
num_agents = 3
num_deliveries = 20
# seed(10)
bases_pos = randint(1, 10, [num_bases, 2]).tolist()
agents_p... | test/compare_test.py | from models.cbba import CBBA
from models.ccbba import CCBBA
import logging
import time
from numpy.random import randint, choice, seed
from numpy import exp
from math import sqrt
import numpy as np
num_bases = 5
num_agents = 3
num_deliveries = 20
# seed(10)
bases_pos = randint(1, 10, [num_bases, 2]).tolist()
agents_p... | 0.107093 | 0.309011 |
import random
#===exercício 01===
num= int(input("Seu palpite:"))
sor= random.randint(1,5)
if (num == sor):
print("O número sorteado foi {}.\nVocê é o bichão mesmo hein".format(sor))
else:
print("O número sorteado foi {}.\nTente novamente".format(sor))
#===exercício02===
vel= float(input("velocidade do automóv... | pacote download/aula10.py | import random
#===exercício 01===
num= int(input("Seu palpite:"))
sor= random.randint(1,5)
if (num == sor):
print("O número sorteado foi {}.\nVocê é o bichão mesmo hein".format(sor))
else:
print("O número sorteado foi {}.\nTente novamente".format(sor))
#===exercício02===
vel= float(input("velocidade do automóv... | 0.131507 | 0.357287 |
import origen, _origen, pytest # pylint: disable=import-error
from tests.shared import clean_falcon, clean_eagle # pylint: disable=import-error
from tests.pins import pins, is_pin_group # pylint: disable=import-error
class TestPinsInDUTHierarchy:
def test_pins_in_subblocks(self, clean_falcon, pins):
# ... | test_apps/python_app/tests/pins/test_pin_misc.py | import origen, _origen, pytest # pylint: disable=import-error
from tests.shared import clean_falcon, clean_eagle # pylint: disable=import-error
from tests.pins import pins, is_pin_group # pylint: disable=import-error
class TestPinsInDUTHierarchy:
def test_pins_in_subblocks(self, clean_falcon, pins):
# ... | 0.587943 | 0.443118 |
import plotly.graph_objs as go
from numpy import (
arctanh,
corrcoef,
isnan,
NaN,
percentile,
zeros,
)
from ..fingers.max_activity import FINGERS
from .utils import TICKFONT
def plot_finger_chan(v, chans):
fig = go.Figure(
go.Heatmap(
x=chans,
y=FINGERS... | fima/viz/finger_channels.py | import plotly.graph_objs as go
from numpy import (
arctanh,
corrcoef,
isnan,
NaN,
percentile,
zeros,
)
from ..fingers.max_activity import FINGERS
from .utils import TICKFONT
def plot_finger_chan(v, chans):
fig = go.Figure(
go.Heatmap(
x=chans,
y=FINGERS... | 0.624294 | 0.230443 |
import csv
CSV_FILE = '/home/lemon/Documents/bcompiler/source/master_transposed.csv'
def get_approval_dates_for_project(project: str, csv_file: str) -> tuple:
reader = csv.DictReader(csv_file)
with open(csv_file, 'r') as f:
reader = csv.DictReader(f)
d = {}
for line in reader:
... | xldigest/analysis/milestones.py | import csv
CSV_FILE = '/home/lemon/Documents/bcompiler/source/master_transposed.csv'
def get_approval_dates_for_project(project: str, csv_file: str) -> tuple:
reader = csv.DictReader(csv_file)
with open(csv_file, 'r') as f:
reader = csv.DictReader(f)
d = {}
for line in reader:
... | 0.188249 | 0.102484 |
from __future__ import annotations
from typing import Any
import numpy as np
import pytest
from bqskit.ir.circuit import Circuit
from bqskit.ir.gate import Gate
from bqskit.ir.gates import CNOTGate
from bqskit.ir.gates import ConstantUnitaryGate
from bqskit.ir.gates import CSUMGate
from bqskit.ir.gates import HGate
... | tests/ir/circuit/test_properties.py | from __future__ import annotations
from typing import Any
import numpy as np
import pytest
from bqskit.ir.circuit import Circuit
from bqskit.ir.gate import Gate
from bqskit.ir.gates import CNOTGate
from bqskit.ir.gates import ConstantUnitaryGate
from bqskit.ir.gates import CSUMGate
from bqskit.ir.gates import HGate
... | 0.928991 | 0.719223 |
import os
import json
from pkg_resources import resource_filename
from docutils import nodes
from docutils.utils import new_document
from sphinx.transforms import SphinxTransform
from sphinx.util.docutils import LoggingReporter
from sphinx.util.fileutil import copy_asset
from . import __version__
emoji_styles = {
... | sphinxemoji/sphinxemoji.py | import os
import json
from pkg_resources import resource_filename
from docutils import nodes
from docutils.utils import new_document
from sphinx.transforms import SphinxTransform
from sphinx.util.docutils import LoggingReporter
from sphinx.util.fileutil import copy_asset
from . import __version__
emoji_styles = {
... | 0.439988 | 0.089773 |
import pyspark
import json
import nltk
from nltk import word_tokenize
def _init_line(line):
name = line.lower().split()[0]
return (name,line.lower().split())
def _init_list(sc):
results = {}
companyRDD = sc.textFile("gs://group688/companylist")
coms = companyRDD.map(_init_line).collect()
for com in coms:
... | etl/rawfilter/etl.py | import pyspark
import json
import nltk
from nltk import word_tokenize
def _init_line(line):
name = line.lower().split()[0]
return (name,line.lower().split())
def _init_list(sc):
results = {}
companyRDD = sc.textFile("gs://group688/companylist")
coms = companyRDD.map(_init_line).collect()
for com in coms:
... | 0.155848 | 0.137677 |
from logging import StreamHandler
from unittest import TestCase, main
from expects import expect, contain, equal
from twin_sister import open_dependency_context
from questions_three.constants import TestEvent
from questions_three.event_broker import EventBroker, subscribe_event_handlers
from questions_three.exception... | tests/scaffolds/xunit/test_skip_all_tests.py | from logging import StreamHandler
from unittest import TestCase, main
from expects import expect, contain, equal
from twin_sister import open_dependency_context
from questions_three.constants import TestEvent
from questions_three.event_broker import EventBroker, subscribe_event_handlers
from questions_three.exception... | 0.739705 | 0.432183 |
import json
from datetime import datetime
from werkzeug.security import generate_password_hash, check_password_hash
from flask import json, jsonify, make_response, g, current_app as app
from flask.ext.sqlalchemy import SQLAlchemy
from sqlalchemy.types import TypeDecorator, Text
from utils import *
class JSONEncodedDi... | gerblook/models.py | import json
from datetime import datetime
from werkzeug.security import generate_password_hash, check_password_hash
from flask import json, jsonify, make_response, g, current_app as app
from flask.ext.sqlalchemy import SQLAlchemy
from sqlalchemy.types import TypeDecorator, Text
from utils import *
class JSONEncodedDi... | 0.381335 | 0.066146 |
from __future__ import division, print_function
import os
import sys
import time
from collections import defaultdict, deque
from functools import partial
from builtins import map, range
import re
import six
import pandas as pd
from tgirt_map.trim_function import fastp_trimming, atropos_trimming
class sample_object():
... | tgirt_map/mapping_tools.py | from __future__ import division, print_function
import os
import sys
import time
from collections import defaultdict, deque
from functools import partial
from builtins import map, range
import re
import six
import pandas as pd
from tgirt_map.trim_function import fastp_trimming, atropos_trimming
class sample_object():
... | 0.144752 | 0.078325 |
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('image_info', '0001_initial'),
]
operations = [
migrations.AlterModelOptions(
name='customerimage',
options={'verbose_name': ... | apps/image_info/migrations/0002_auto_20190305_1247.py | from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('image_info', '0001_initial'),
]
operations = [
migrations.AlterModelOptions(
name='customerimage',
options={'verbose_name': ... | 0.694821 | 0.121634 |
import random
import string
import requests
import urllib3
from pprint import pprint
import json
import getpass
urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
log_file="fwbackuplog.log"
link_log_file="lnk.log"
user_log="user.log"
headers = {'Content-Type': 'application/json', 'User... | CiscoASARESTAPI-BlogPost.py |
import random
import string
import requests
import urllib3
from pprint import pprint
import json
import getpass
urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
log_file="fwbackuplog.log"
link_log_file="lnk.log"
user_log="user.log"
headers = {'Content-Type': 'application/json', 'User... | 0.076604 | 0.037538 |
import os
import csv
import json
from unet3d.data import write_data_to_file, open_data_file
from unet3d.generator import get_training_and_validation_generators
from unet3d.prediction import run_validation_cases
os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID"
os.environ["CUDA_VISIBLE_DEVICES"] = "0"
cur_dir = os.path... | run_test_cases.py | import os
import csv
import json
from unet3d.data import write_data_to_file, open_data_file
from unet3d.generator import get_training_and_validation_generators
from unet3d.prediction import run_validation_cases
os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID"
os.environ["CUDA_VISIBLE_DEVICES"] = "0"
cur_dir = os.path... | 0.196595 | 0.16388 |
import requests
from requests_oauthlib import OAuth2Session
from urllib.parse import urljoin
from .models import DayliteData, Contact, Thin_Contact, Company, Opportunity
USER_AUTHORISE_URL="https://www.marketcircle.com/account/oauth/authorize"
OAUTH_TOKEN_URL="https://www.marketcircle.com/account/oauth/token"
AUTH_UR... | daylite/__init__.py | import requests
from requests_oauthlib import OAuth2Session
from urllib.parse import urljoin
from .models import DayliteData, Contact, Thin_Contact, Company, Opportunity
USER_AUTHORISE_URL="https://www.marketcircle.com/account/oauth/authorize"
OAUTH_TOKEN_URL="https://www.marketcircle.com/account/oauth/token"
AUTH_UR... | 0.277277 | 0.143638 |
from django.db import models
from django.conf import settings
from django.utils.functional import cached_property
from django.urls import reverse
from django.utils import timezone
from django.utils.translation import ugettext_lazy as _
from ..utils import EnhancedTextField
from tagging.fields import TagField
from tag... | rotv_apps/blog/models.py | from django.db import models
from django.conf import settings
from django.utils.functional import cached_property
from django.urls import reverse
from django.utils import timezone
from django.utils.translation import ugettext_lazy as _
from ..utils import EnhancedTextField
from tagging.fields import TagField
from tag... | 0.515376 | 0.116663 |
__author__ = '<EMAIL> (<NAME>)'
import re
from base_parser import BaseParser, Identity
class HttpOutgoingParser(BaseParser):
DPORTS = [80, 8000, 8080]
PROTOCOL = 'HTTP'
GMAIL_CHAT_RE = re.compile('\; gmailchat=(%s)\/')
GRAVATAR_RE = re.compile('Cookie: gravatar=([\w]+)%7C')
AGENT_RE = re.compile('User-Agent... | parsers/http_outgoing.py | __author__ = '<EMAIL> (<NAME>)'
import re
from base_parser import BaseParser, Identity
class HttpOutgoingParser(BaseParser):
DPORTS = [80, 8000, 8080]
PROTOCOL = 'HTTP'
GMAIL_CHAT_RE = re.compile('\; gmailchat=(%s)\/')
GRAVATAR_RE = re.compile('Cookie: gravatar=([\w]+)%7C')
AGENT_RE = re.compile('User-Agent... | 0.296451 | 0.085327 |
from skimage.metrics import structural_similarity
from skimage.metrics import peak_signal_noise_ratio as psnr
from skimage import img_as_float32
import numpy as np
def normalize(x, pmin=3, pmax=99.8, axis=None, clip=False, eps=1e-20, dtype=np.float32):
"""This function is adapted from Martin Weigert"""
"""Per... | ZS4Mic/load_functions/quality_metrics_estimation.py | from skimage.metrics import structural_similarity
from skimage.metrics import peak_signal_noise_ratio as psnr
from skimage import img_as_float32
import numpy as np
def normalize(x, pmin=3, pmax=99.8, axis=None, clip=False, eps=1e-20, dtype=np.float32):
"""This function is adapted from Martin Weigert"""
"""Per... | 0.865679 | 0.472379 |