code stringlengths 2k 1.04M | repo_path stringlengths 5 517 | parsed_code stringlengths 0 1.04M | quality_prob float64 0.02 0.95 | learning_prob float64 0.02 0.93 |
|---|---|---|---|---|
import numpy as np
import scipy.signal as signal
import matplotlib.pyplot as plt
def create_bassman(low, middle, high):
R1 = 250e3
R2 = 1e6
R3 = 25e3
R4 = 45e3
C1 = 250e-12
C2 = 20e-9
C3 = 20e-9
b = (0, (high*C1*R1 + middle*C3*R3 + low*(C1*R2 + C2*R2) + (C1*R3 + C2*R3)), (high*(C1*C2*R1*R4 + C1*C3*R1... | Examples/EQ/compare_tonestack.py | import numpy as np
import scipy.signal as signal
import matplotlib.pyplot as plt
def create_bassman(low, middle, high):
R1 = 250e3
R2 = 1e6
R3 = 25e3
R4 = 45e3
C1 = 250e-12
C2 = 20e-9
C3 = 20e-9
b = (0, (high*C1*R1 + middle*C3*R3 + low*(C1*R2 + C2*R2) + (C1*R3 + C2*R3)), (high*(C1*C2*R1*R4 + C1*C3*R1... | 0.466603 | 0.61633 |
import pytest
from nornir.core.task import AggregatedResult
from nornir_napalm.plugins import tasks
from nuts.base_tests.napalm_get_vlans import CONTEXT
from tests.utils import create_multi_result, SelfTestData
nornir_raw_result_s1 = {
"vlans": {
"1": {
"name": "default",
"interf... | tests/base_tests/test_napalm_get_vlans.py | import pytest
from nornir.core.task import AggregatedResult
from nornir_napalm.plugins import tasks
from nuts.base_tests.napalm_get_vlans import CONTEXT
from tests.utils import create_multi_result, SelfTestData
nornir_raw_result_s1 = {
"vlans": {
"1": {
"name": "default",
"interf... | 0.516108 | 0.394493 |
import pytest
from dlapp.collection import Element
from dlapp.collection import LookupCls
from dlapp.collection import List
from dlapp.collection import ListIndexError
@pytest.fixture
def dict_data():
obj = {
"widget": {
"debug": "on",
"window": {
"title": "ABC Wid... | tests/unit/test_collection.py | import pytest
from dlapp.collection import Element
from dlapp.collection import LookupCls
from dlapp.collection import List
from dlapp.collection import ListIndexError
@pytest.fixture
def dict_data():
obj = {
"widget": {
"debug": "on",
"window": {
"title": "ABC Wid... | 0.572723 | 0.446977 |
import numpy as np
from steganography.utilities.rand import get_random_sequence
import logging
SIZE_LENGTH = 32
def hide_data_in_LSB(pixels, data, seed):
"""
Hide data in carry and return a numpy array.
:param pixels: an np array image to hide data in
:param data: an array of bits to hide
:param ... | steganography/strategies/lsb.py | import numpy as np
from steganography.utilities.rand import get_random_sequence
import logging
SIZE_LENGTH = 32
def hide_data_in_LSB(pixels, data, seed):
"""
Hide data in carry and return a numpy array.
:param pixels: an np array image to hide data in
:param data: an array of bits to hide
:param ... | 0.417628 | 0.720381 |
# Import PyIOmica
import pyiomica as pio
# Import Extended DataFrame from PyIOmica
from pyiomica.extendedDataFrame import DataFrame
# Create a simple data for testing and demonstration
df_data = DataFrame(data=pio.np.array([[0.5,2,3],
[0,2,6],
... | docs/examples/examplesExtendedDataFrame.py |
# Import PyIOmica
import pyiomica as pio
# Import Extended DataFrame from PyIOmica
from pyiomica.extendedDataFrame import DataFrame
# Create a simple data for testing and demonstration
df_data = DataFrame(data=pio.np.array([[0.5,2,3],
[0,2,6],
... | 0.423339 | 0.54353 |
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.checkpoint
from .activation import MyReLU
from .bone_utils import get_canonical_pose
from .stylegan import EqualLinear, EqualConv1d, NormalizedConv1d
from .model_utils import in_cube
from .utils_3d import SE3
cla... | NARF/models/nerf_model.py | import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.checkpoint
from .activation import MyReLU
from .bone_utils import get_canonical_pose
from .stylegan import EqualLinear, EqualConv1d, NormalizedConv1d
from .model_utils import in_cube
from .utils_3d import SE3
cla... | 0.901405 | 0.346597 |
import re
from collections.abc import Mapping
from functools import reduce
from copy import deepcopy
from arpoc.plugins._lib import Obligation, Optional, deep_dict_update
from arpoc.ac.common import Effects
from typing import Dict
import logging
"""
Obligation Log Module.
The classes here will either
- log every... | arpoc/plugins/obl_loggers.py | import re
from collections.abc import Mapping
from functools import reduce
from copy import deepcopy
from arpoc.plugins._lib import Obligation, Optional, deep_dict_update
from arpoc.ac.common import Effects
from typing import Dict
import logging
"""
Obligation Log Module.
The classes here will either
- log every... | 0.853303 | 0.169922 |
import os
import numpy as np
import pandas as pd
from hyperactive import Hyperactive
from hyperactive.dashboards import ProgressBoard
from hyperactive.dashboards.progress_board.streamlit_backend import StreamlitBackend
from hyperactive.dashboards.progress_board.progress_io import ProgressIO
def test_progress_io_0():
... | tests/test_progress_board.py | import os
import numpy as np
import pandas as pd
from hyperactive import Hyperactive
from hyperactive.dashboards import ProgressBoard
from hyperactive.dashboards.progress_board.streamlit_backend import StreamlitBackend
from hyperactive.dashboards.progress_board.progress_io import ProgressIO
def test_progress_io_0():
... | 0.514644 | 0.360264 |
from __future__ import unicode_literals
from django.contrib.auth.forms import AuthenticationForm
from django.contrib.auth import get_user_model
from django import forms
from django.utils.translation import ugettext_lazy as _
from crispy_forms.helper import FormHelper
from crispy_forms.layout import Layout, Submit, Fi... | src/accounts/forms.py | from __future__ import unicode_literals
from django.contrib.auth.forms import AuthenticationForm
from django.contrib.auth import get_user_model
from django import forms
from django.utils.translation import ugettext_lazy as _
from crispy_forms.helper import FormHelper
from crispy_forms.layout import Layout, Submit, Fi... | 0.621426 | 0.087564 |
from functools import partial
import requests
from waiter import terminal, http_util
from waiter.action import ping_token_on_cluster, process_kill_request
from waiter.querying import get_target_cluster_from_token, get_token
from waiter.token_post import post_failed_message, process_post_result
from waiter.util import... | cli/waiter/subcommands/maintenance.py | from functools import partial
import requests
from waiter import terminal, http_util
from waiter.action import ping_token_on_cluster, process_kill_request
from waiter.querying import get_target_cluster_from_token, get_token
from waiter.token_post import post_failed_message, process_post_result
from waiter.util import... | 0.47658 | 0.071786 |
import pandas as pd
import numpy as np
import cartopy.crs as ccrs
import matplotlib.pyplot as plt
import os, sys
import matplotlib.ticker as mticker
pd.set_option('display.max_rows', 5000)
pd.set_option('display.max_columns', 5000)
import xarray as xr
def get_k_nearest_values_from_vector(arr, k):
idx = np.... | scripts/regridding/IDW_over_xarray.py | import pandas as pd
import numpy as np
import cartopy.crs as ccrs
import matplotlib.pyplot as plt
import os, sys
import matplotlib.ticker as mticker
pd.set_option('display.max_rows', 5000)
pd.set_option('display.max_columns', 5000)
import xarray as xr
def get_k_nearest_values_from_vector(arr, k):
idx = np.... | 0.333503 | 0.605974 |
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
import django_countries.fields
import workshops.fields
def update_contenttypes(apps, schema_editor):
ContentType = apps.get_model('contenttypes', 'ContentType')
# update application for all non-version... | amy/extrequests/migrations/0001_initial.py |
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
import django_countries.fields
import workshops.fields
def update_contenttypes(apps, schema_editor):
ContentType = apps.get_model('contenttypes', 'ContentType')
# update application for all non-version... | 0.469034 | 0.180287 |
from datetime import date
from functools import reduce
import logging
from multiprocessing import cpu_count
from os import chdir, getcwd
from os.path import relpath
from shutil import copy, copytree, rmtree
from pathlib import Path
from platform import system
import sqlite3
from string import Template
from subprocess i... | scripts/manager.py | from datetime import date
from functools import reduce
import logging
from multiprocessing import cpu_count
from os import chdir, getcwd
from os.path import relpath
from shutil import copy, copytree, rmtree
from pathlib import Path
from platform import system
import sqlite3
from string import Template
from subprocess i... | 0.694199 | 0.253728 |
from kivy.uix.textinput import TextInput
from kivy.properties import NumericProperty
import math
class IntEntry(TextInput):
value = NumericProperty(0.0)
def __init__(self, low=-math.inf, high=math.inf, **kwds):
if low >= 10:
# Because otherwise we couldn't ever type the first digit
... | timedata/ui/int_entry.py | from kivy.uix.textinput import TextInput
from kivy.properties import NumericProperty
import math
class IntEntry(TextInput):
value = NumericProperty(0.0)
def __init__(self, low=-math.inf, high=math.inf, **kwds):
if low >= 10:
# Because otherwise we couldn't ever type the first digit
... | 0.320396 | 0.326781 |
from confiture import Confiture
from .i_command import ICommand
from src.shell.chart.arity import ArityChart
from src.shell.chart.type import TypeChart
from src.shell.chart.couple import CoupleChart
from src.shell.chart.alloc import AllocChart
class ChartCmd(ICommand):
"""
usage: chart <analysis> <parame... | src/shell/command/chart.py |
from confiture import Confiture
from .i_command import ICommand
from src.shell.chart.arity import ArityChart
from src.shell.chart.type import TypeChart
from src.shell.chart.couple import CoupleChart
from src.shell.chart.alloc import AllocChart
class ChartCmd(ICommand):
"""
usage: chart <analysis> <parame... | 0.427636 | 0.273174 |
from infrastructor.Cryptography.CryptoService import CryptoService
from infrastructor.data.ConnectionStrategy import ConnectionStrategy
from infrastructor.data.DatabaseManager import DatabaseManager
from infrastructor.data.OracleConnector import OracleDbConnector
class OracleConnectionStrategy(ConnectionStrategy):
... | domain/imageprocessing/strategies/OracleConnectionStrategy.py | from infrastructor.Cryptography.CryptoService import CryptoService
from infrastructor.data.ConnectionStrategy import ConnectionStrategy
from infrastructor.data.DatabaseManager import DatabaseManager
from infrastructor.data.OracleConnector import OracleDbConnector
class OracleConnectionStrategy(ConnectionStrategy):
... | 0.334046 | 0.074265 |
class TimeBlock:
DAYS = ['M', 'T', 'W', 'R', 'F']
'''
returns a list of time blocks, repeating the start/end times for the given days
ex: time_str = 'MWF:1000-1050'
'''
@classmethod
def get_time_blocks(cls, time_str):
blocks = []
if ':' in time_str:
colon_index = time_str.index(':')
days = time_str[... | Planit/API/TimeBlock.py | class TimeBlock:
DAYS = ['M', 'T', 'W', 'R', 'F']
'''
returns a list of time blocks, repeating the start/end times for the given days
ex: time_str = 'MWF:1000-1050'
'''
@classmethod
def get_time_blocks(cls, time_str):
blocks = []
if ':' in time_str:
colon_index = time_str.index(':')
days = time_str[... | 0.458349 | 0.402099 |
from collections import namedtuple
from datetime import datetime, timedelta
from sqlalchemy import and_
import pandas as pd
from app import db
# ENTSO-E mappings
RENEWABLES = ["wind", "hydro", "solar", "biomass"]
NON_RENEWABLES = ["coal", "fossil", "natgas", "oil", "other", "refuse"]
ModelParameters = namedtuple("M... | app/model.py | from collections import namedtuple
from datetime import datetime, timedelta
from sqlalchemy import and_
import pandas as pd
from app import db
# ENTSO-E mappings
RENEWABLES = ["wind", "hydro", "solar", "biomass"]
NON_RENEWABLES = ["coal", "fossil", "natgas", "oil", "other", "refuse"]
ModelParameters = namedtuple("M... | 0.918667 | 0.294494 |
from typing import Any, Dict, List, Tuple
from overrides import overrides
import numpy as np
import torch # mostly for type annotations
from miso.metrics.metric import Metric
from miso.metrics.srl import compute_srl_f1
class GVDBScores(Metric):
def __init__(self, vocab) -> None:
self._scorer = Scorer()
sel... | miso/metrics/gvdb_scores.py | from typing import Any, Dict, List, Tuple
from overrides import overrides
import numpy as np
import torch # mostly for type annotations
from miso.metrics.metric import Metric
from miso.metrics.srl import compute_srl_f1
class GVDBScores(Metric):
def __init__(self, vocab) -> None:
self._scorer = Scorer()
sel... | 0.688154 | 0.176441 |
import gym, gym_envs
from stable_baselines.common.vec_env import DummyVecEnv, VecNormalize
from stable_baselines.common.env_checker import check_env
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import os
import time
import argparse
def main():
parser = argparse.ArgumentParser()
par... | rl-baselines-zoo/7_run_random_policy.py | import gym, gym_envs
from stable_baselines.common.vec_env import DummyVecEnv, VecNormalize
from stable_baselines.common.env_checker import check_env
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import os
import time
import argparse
def main():
parser = argparse.ArgumentParser()
par... | 0.225672 | 0.305905 |
import slapd
import pytest
def test_nominal_case():
server = slapd.Slapd()
server.start()
server.restart()
server.stop()
def test_context_manager():
with slapd.Slapd() as server:
assert server._proc is not None
assert server._proc is None
server.stop()
def test_context_manager_... | tests/test_slapdobject.py | import slapd
import pytest
def test_nominal_case():
server = slapd.Slapd()
server.start()
server.restart()
server.stop()
def test_context_manager():
with slapd.Slapd() as server:
assert server._proc is not None
assert server._proc is None
server.stop()
def test_context_manager_... | 0.369201 | 0.307423 |
import os
import pytest
from chimera_app.compat_tools import ExternalCompatTool
@pytest.fixture
def fake_data(fs,
monkeypatch):
files_path = os.path.join(os.path.dirname(__file__), 'files')
fs.create_dir(os.path.expanduser('~/.cache'))
fs.create_dir(os.path.expanduser('~/.local/share/chime... | tests/test_compat_tools.py |
import os
import pytest
from chimera_app.compat_tools import ExternalCompatTool
@pytest.fixture
def fake_data(fs,
monkeypatch):
files_path = os.path.join(os.path.dirname(__file__), 'files')
fs.create_dir(os.path.expanduser('~/.cache'))
fs.create_dir(os.path.expanduser('~/.local/share/chime... | 0.33112 | 0.112893 |
import numpy as np
import pandas as pd
from sklearn import metrics
from sklearn import model_selection
from sklearn.preprocessing import MinMaxScaler,StandardScaler
from sklearn.neural_network import MLPClassifier
from sklearn.linear_model import LogisticRegression
from sklearn import svm,tree
from sklearn.ens... | model/eval/evaluation.py | import numpy as np
import pandas as pd
from sklearn import metrics
from sklearn import model_selection
from sklearn.preprocessing import MinMaxScaler,StandardScaler
from sklearn.neural_network import MLPClassifier
from sklearn.linear_model import LogisticRegression
from sklearn import svm,tree
from sklearn.ens... | 0.414188 | 0.250792 |
import time
from data_structures import UnionFind
def load_data(filename, dtype='edges'):
if dtype == 'edges':
f = open(filename)
n = int(f.readline())
nodes = [i+1 for i in range(n)]
data = f.readlines()
f.close()
left, right, length = [], [], []
for line in... | c3-greedy-dp/k_clustering.py | import time
from data_structures import UnionFind
def load_data(filename, dtype='edges'):
if dtype == 'edges':
f = open(filename)
n = int(f.readline())
nodes = [i+1 for i in range(n)]
data = f.readlines()
f.close()
left, right, length = [], [], []
for line in... | 0.441191 | 0.314656 |
from asyncio import Task, get_event_loop, sleep, CancelledError
from dataclasses import dataclass
from enum import Enum
from logging import getLogger
from typing import Callable, Awaitable, Optional, Dict, List
from pydantic import BaseModel
from binp.events import Emitter
class Status(str, Enum):
"""
Servi... | binp/service.py | from asyncio import Task, get_event_loop, sleep, CancelledError
from dataclasses import dataclass
from enum import Enum
from logging import getLogger
from typing import Callable, Awaitable, Optional, Dict, List
from pydantic import BaseModel
from binp.events import Emitter
class Status(str, Enum):
"""
Servi... | 0.775647 | 0.192388 |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
import time
import sys
import math
import numpy as np
import argparse
import functools
import paddle
import paddle.fluid as fluid
from image_classification import reader
from image_classification im... | PaddleCV/image_classification/eval.py |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
import time
import sys
import math
import numpy as np
import argparse
import functools
import paddle
import paddle.fluid as fluid
from image_classification import reader
from image_classification im... | 0.416678 | 0.169853 |
import os
import tflearn
OUTPUT_FOLDER = 'output/buff_bobo'
# Residual blocks
# 32 layers: n=5, 56 layers: n=9, 110 layers: n=18
N = 5
class ClassificationModel(object):
"""
A model for object classification.
"""
def __init__(self, image_size, weights):
self.network = self._build_networ... | architectures/buff_bobo/classifier.py |
import os
import tflearn
OUTPUT_FOLDER = 'output/buff_bobo'
# Residual blocks
# 32 layers: n=5, 56 layers: n=9, 110 layers: n=18
N = 5
class ClassificationModel(object):
"""
A model for object classification.
"""
def __init__(self, image_size, weights):
self.network = self._build_networ... | 0.755817 | 0.307696 |
from django.core.cache import caches
def get_slug(node):
"""
Return short URL-able sting to use as identifier for current Node or File.
"""
return node.title.replace(' ', '_')
def get_path_for_node(node):
"""
Returns the requestpath for accessing this node,
e.g. 'topic_1/subtopic_2/conte... | fakolibri/statiksite/helpers.py | from django.core.cache import caches
def get_slug(node):
"""
Return short URL-able sting to use as identifier for current Node or File.
"""
return node.title.replace(' ', '_')
def get_path_for_node(node):
"""
Returns the requestpath for accessing this node,
e.g. 'topic_1/subtopic_2/conte... | 0.513181 | 0.18396 |
import numpy as np
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LogisticRegression
from sklearn.metrics import accuracy_score
sonar_data = pd.read_csv("C:/Users/Sakthi/Desktop/Copy of sonar data.csv",
header=None)
sonar_dat... | sonar.py | import numpy as np
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LogisticRegression
from sklearn.metrics import accuracy_score
sonar_data = pd.read_csv("C:/Users/Sakthi/Desktop/Copy of sonar data.csv",
header=None)
sonar_dat... | 0.235372 | 0.316937 |
from bs4 import BeautifulSoup
from src.model.models import Consulta, TermoConsulta, EntradaRanking
from src.service.StopwordService import StopwordsService
from src.service.IndexadorService import IndexadorService
from src.service.TermoDocumentoService import TermoDocumentoService
from src.service.IndiceInvertidoServi... | src/service/ProcessadorConsultaService.py | from bs4 import BeautifulSoup
from src.model.models import Consulta, TermoConsulta, EntradaRanking
from src.service.StopwordService import StopwordsService
from src.service.IndexadorService import IndexadorService
from src.service.TermoDocumentoService import TermoDocumentoService
from src.service.IndiceInvertidoServi... | 0.28607 | 0.121686 |
# jwc from: ~/01-Jwc/03t-StsPilot-MarkOrion/STS-PiLot
"""
Created on Wed Mar 15 11:56:25 2017
@author: <NAME>
"""
import explorerhat as xhat
explorerhat = True
# Inputs: Digital
def input_one_read():
digital = xhat.input.one.read()
return digital
def input_two_read():
digital = xhat.input.two.read(... | io_Driver_File.py |
# jwc from: ~/01-Jwc/03t-StsPilot-MarkOrion/STS-PiLot
"""
Created on Wed Mar 15 11:56:25 2017
@author: <NAME>
"""
import explorerhat as xhat
explorerhat = True
# Inputs: Digital
def input_one_read():
digital = xhat.input.one.read()
return digital
def input_two_read():
digital = xhat.input.two.read(... | 0.603348 | 0.434041 |
import ast
import json
from distutils.util import strtobool
import click
import six
from tower_cli import models, resources, exceptions as exc
from tower_cli.api import client
from tower_cli.conf import pop_option
from tower_cli.cli import types
from tower_cli.utils.data_structures import OrderedDict
from tower_cli.... | tower_cli/resources/setting.py |
import ast
import json
from distutils.util import strtobool
import click
import six
from tower_cli import models, resources, exceptions as exc
from tower_cli.api import client
from tower_cli.conf import pop_option
from tower_cli.cli import types
from tower_cli.utils.data_structures import OrderedDict
from tower_cli.... | 0.744935 | 0.19349 |
__version__ = '0.10.3'
import matplotlib.pyplot as plt
import tensorflow as tf
import load_data
import optimizers
import data_preprocessing
import keras
from keras import layers
from keras import losses
from keras import backend as K
from keras.models import Sequential, Input, Model
from keras.models import load_mode... | deep learning models/CNN_feature_extractor.py | __version__ = '0.10.3'
import matplotlib.pyplot as plt
import tensorflow as tf
import load_data
import optimizers
import data_preprocessing
import keras
from keras import layers
from keras import losses
from keras import backend as K
from keras.models import Sequential, Input, Model
from keras.models import load_mode... | 0.710729 | 0.374362 |
from datetime import datetime
import logging
import uuid
from django.conf import settings
from django.contrib.auth.models import AbstractUser
from django.core.mail import EmailMessage
from django.db import models
from django.utils.translation import gettext_lazy as _
import numpy as np
from .email_utils import send_m... | backend/apps/accounts/models.py | from datetime import datetime
import logging
import uuid
from django.conf import settings
from django.contrib.auth.models import AbstractUser
from django.core.mail import EmailMessage
from django.db import models
from django.utils.translation import gettext_lazy as _
import numpy as np
from .email_utils import send_m... | 0.393152 | 0.092934 |
while True:
capitalchars = 0
smallchars = 0
notalphanum = 0
spaces = 0
nums = 0
charsinseq = 0
valid = True
password = input('Enter password: ')
for i in range(len(password)):
if i < len(password) - 1:
part1 = chr(ord(password[i]) + 32) if 65 <= ord(pas... | Password Strength Checker/main.py | while True:
capitalchars = 0
smallchars = 0
notalphanum = 0
spaces = 0
nums = 0
charsinseq = 0
valid = True
password = input('Enter password: ')
for i in range(len(password)):
if i < len(password) - 1:
part1 = chr(ord(password[i]) + 32) if 65 <= ord(pas... | 0.095666 | 0.250434 |
import os
import time
from matplotlib.pyplot import show
import numpy as np
from tqdm import tqdm
import pandas as pd
import torch
from torch.cuda import amp
from .checkpoint import Checkpoint
from loggers.loggers import Logger
class Trainer():
def __init__(self,
config,
model,
... | trainer/trainer.py | import os
import time
from matplotlib.pyplot import show
import numpy as np
from tqdm import tqdm
import pandas as pd
import torch
from torch.cuda import amp
from .checkpoint import Checkpoint
from loggers.loggers import Logger
class Trainer():
def __init__(self,
config,
model,
... | 0.568056 | 0.185043 |
from pychain.async_server import AsyncServer
from pychain.util import encodeMsg, decodeMsg, intToBytes
import socket
from struct import pack, unpack
nodeVersion = 1
commandLen = 12
def addr(addrList):
return {
'addrList': addrList
}
def block(addrFrom, block):
return {
'a... | pychain/p2p_interface.py | from pychain.async_server import AsyncServer
from pychain.util import encodeMsg, decodeMsg, intToBytes
import socket
from struct import pack, unpack
nodeVersion = 1
commandLen = 12
def addr(addrList):
return {
'addrList': addrList
}
def block(addrFrom, block):
return {
'a... | 0.329823 | 0.065217 |
import re
import torch
from torch.autograd import Function
from .._ext import libspn
class FunctionBackend(object):
def __init__(self, lib):
self.backends = dict()
self.parse_lib(lib)
self.current_backend = None
def __getattr__(self, name):
func = self.backends[self.current_ba... | spnlib/spn/functions/SPG.py | import re
import torch
from torch.autograd import Function
from .._ext import libspn
class FunctionBackend(object):
def __init__(self, lib):
self.backends = dict()
self.parse_lib(lib)
self.current_backend = None
def __getattr__(self, name):
func = self.backends[self.current_ba... | 0.695855 | 0.132066 |
from keras.models import Sequential
from keras.datasets import boston_housing
from keras.layers import Dense
from keras.optimizers import Adam
from keras.callbacks import EarlyStopping
import numpy as np
import matplotlib.pyplot as plt
from utils import randomize
# Hyper-parameters
EPOCHS = 500
NUM_HIDDEN_UNITS = 64
L... | 1_Basics/3_basic_regression_keras.py | from keras.models import Sequential
from keras.datasets import boston_housing
from keras.layers import Dense
from keras.optimizers import Adam
from keras.callbacks import EarlyStopping
import numpy as np
import matplotlib.pyplot as plt
from utils import randomize
# Hyper-parameters
EPOCHS = 500
NUM_HIDDEN_UNITS = 64
L... | 0.93922 | 0.678913 |
import os
import sys
import json
import shutil
from argparse import ArgumentParser
import numpy as np
import torch
import utils
from torchvision.models import vgg16
import torch.nn as nn
from config import add_eval_args
from data import PartNetDataset, Tree
from image_encoder import ImageEncoder
# os.environ["CUDA_VIS... | code/eval_part_pc_vst_fea_multi.py | import os
import sys
import json
import shutil
from argparse import ArgumentParser
import numpy as np
import torch
import utils
from torchvision.models import vgg16
import torch.nn as nn
from config import add_eval_args
from data import PartNetDataset, Tree
from image_encoder import ImageEncoder
# os.environ["CUDA_VIS... | 0.392337 | 0.084191 |
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import random
import matplotlib.animation
class Object():
def __init__(self,mass,position,speed,index=None):
self.mass=mass
self.position=position
self.speed=speed
self.index=index
class Qu... | old versions/but2D simulation.py | import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import random
import matplotlib.animation
class Object():
def __init__(self,mass,position,speed,index=None):
self.mass=mass
self.position=position
self.speed=speed
self.index=index
class Qu... | 0.311846 | 0.200812 |
print('Starting with m = 1, n = 1:')
callStack = [{'m': 1, 'n': 1, 'indentation': 0, 'instrPtr': 'start'}]
returnValue = None
while len(callStack) != 0:
m = callStack[-1]['m']
n = callStack[-1]['n']
indentation = callStack[-1]['indentation']
instrPtr = callStack[-1]['instrPtr']
if instrPtr == 'sta... | files/recursion/recursion_examples-master/ackermann_iterative.py | print('Starting with m = 1, n = 1:')
callStack = [{'m': 1, 'n': 1, 'indentation': 0, 'instrPtr': 'start'}]
returnValue = None
while len(callStack) != 0:
m = callStack[-1]['m']
n = callStack[-1]['n']
indentation = callStack[-1]['indentation']
instrPtr = callStack[-1]['instrPtr']
if instrPtr == 'sta... | 0.177241 | 0.184327 |
from mock import patch
from unittest import TestCase
from api.task import TaskSerializer
from logical.models import Database, DatabaseHistory
from logical.tests.factory import DatabaseFactory, DatabaseHistoryFactory
class GetDatabaseTestCase(TestCase):
def setUp(self):
self.serializer = TaskSerializer()
... | dbaas/api/tests/test_taskhistory_serializer.py | from mock import patch
from unittest import TestCase
from api.task import TaskSerializer
from logical.models import Database, DatabaseHistory
from logical.tests.factory import DatabaseFactory, DatabaseHistoryFactory
class GetDatabaseTestCase(TestCase):
def setUp(self):
self.serializer = TaskSerializer()
... | 0.769557 | 0.141934 |
import requests
from ddipy import constants
from ddipy.commons import StatRecord, DomainStats, StatOmicsRecord
from ddipy.ddi_utils import BadRequest
class StatisticsClient:
def __init__(self):
pass
@staticmethod
def get_statistics_organisms(size=20):
res = requests.get(constants.STATIS... | ddipy/statistics_client.py | import requests
from ddipy import constants
from ddipy.commons import StatRecord, DomainStats, StatOmicsRecord
from ddipy.ddi_utils import BadRequest
class StatisticsClient:
def __init__(self):
pass
@staticmethod
def get_statistics_organisms(size=20):
res = requests.get(constants.STATIS... | 0.433622 | 0.135604 |
# Runs on the 'goodimgs' catalog output after matching catalogs and downloading/checking fits
# 'not_gz': these are galaxies which are part of the sdss lost set (and actually are now in gz)
# Not yet clear how to find which galaxies these are - what makes the data file?
import os
import warnings
import numpy as np... | decals/willett/metadata/make_nsa_not_gz_metadata.py |
# Runs on the 'goodimgs' catalog output after matching catalogs and downloading/checking fits
# 'not_gz': these are galaxies which are part of the sdss lost set (and actually are now in gz)
# Not yet clear how to find which galaxies these are - what makes the data file?
import os
import warnings
import numpy as np... | 0.608361 | 0.514156 |
import logging
import zephyr.message
import zephyr.util
class BioHarnessSignalAnalysis:
def __init__(self, signal_callbacks, event_callbacks):
self.signal_callbacks = signal_callbacks
self.event_callbacks = event_callbacks
self.latest_rr_value_sign = 0
def handle_signal(... | src/zephyr/bioharness.py | import logging
import zephyr.message
import zephyr.util
class BioHarnessSignalAnalysis:
def __init__(self, signal_callbacks, event_callbacks):
self.signal_callbacks = signal_callbacks
self.event_callbacks = event_callbacks
self.latest_rr_value_sign = 0
def handle_signal(... | 0.646572 | 0.31777 |
import csv
from datetime import datetime
ESTIMATED_JOURNEY_DURATION = {
'Hammersmith (District, Piccadilly lines)': {
'Hatton Cross': 27,
'Barons Court': 1,
'West Kensington': 3
}
}
MINIMUM_DELAY_REFUND = 15
# CSV Keys
KEY_DATE = "Date"
KEY_START_TIME = "Start Time"
KEY_END_TIME = "En... | utils.py | import csv
from datetime import datetime
ESTIMATED_JOURNEY_DURATION = {
'Hammersmith (District, Piccadilly lines)': {
'Hatton Cross': 27,
'Barons Court': 1,
'West Kensington': 3
}
}
MINIMUM_DELAY_REFUND = 15
# CSV Keys
KEY_DATE = "Date"
KEY_START_TIME = "Start Time"
KEY_END_TIME = "En... | 0.110184 | 0.192274 |
import cv2
from threading import Thread
from imutils import face_utils
import numpy as np
import imutils
import dlib
import math
class Webcam:
def __init__(self):
self.capturador = cv2.VideoCapture('data/obama.mp4')
self.capturador.set(3, 640)
self.capturador.set(4, 480)
self.mod... | EspejoVirtual/EspejoVirtual/webcam.py | import cv2
from threading import Thread
from imutils import face_utils
import numpy as np
import imutils
import dlib
import math
class Webcam:
def __init__(self):
self.capturador = cv2.VideoCapture('data/obama.mp4')
self.capturador.set(3, 640)
self.capturador.set(4, 480)
self.mod... | 0.319227 | 0.185209 |
import os
import sys
from functools import wraps
from base64 import b64decode, b64encode
try:
from jqdatasdk import auth
jq_source = True
except ImportError:
jq_source = False
from xalpha.exceptions import DataSourceNotFound
thismodule = sys.modules[__name__]
providers_list = ["jq"]
b64encode_s = la... | xalpha/provider.py | import os
import sys
from functools import wraps
from base64 import b64decode, b64encode
try:
from jqdatasdk import auth
jq_source = True
except ImportError:
jq_source = False
from xalpha.exceptions import DataSourceNotFound
thismodule = sys.modules[__name__]
providers_list = ["jq"]
b64encode_s = la... | 0.277669 | 0.163312 |
import csv
from PIL import Image
from torch.utils.data import dataset
import torch
class AbstractImageCSVDataset(dataset.Dataset):
def __init__(self, **kwargs):
super(AbstractImageCSVDataset, self).__init__()
self.data = kwargs.get('data')
self.csv_path = kwargs.get('csv_path')
se... | datasets.py | import csv
from PIL import Image
from torch.utils.data import dataset
import torch
class AbstractImageCSVDataset(dataset.Dataset):
def __init__(self, **kwargs):
super(AbstractImageCSVDataset, self).__init__()
self.data = kwargs.get('data')
self.csv_path = kwargs.get('csv_path')
se... | 0.656878 | 0.271632 |
fruit = "banana"
""" the counting for the string character starts from 0 by default. """
letter = fruit[1]
print(letter)
""" to print out the letter 3-1=2 (index value) of the word banana """
x = 3
print(fruit[x - 1])
"""prints the length of the word banana """
print(len(fruit))
""" using while loop to... | Strings.py | fruit = "banana"
""" the counting for the string character starts from 0 by default. """
letter = fruit[1]
print(letter)
""" to print out the letter 3-1=2 (index value) of the word banana """
x = 3
print(fruit[x - 1])
"""prints the length of the word banana """
print(len(fruit))
""" using while loop to... | 0.331552 | 0.439988 |
from kratos import *
from lake.passes.passes import lift_config_reg
from lake.modules.sram_wrapper import SRAMWrapper
from lake.modules.for_loop import ForLoop
from lake.modules.addr_gen import AddrGen
from lake.modules.spec.sched_gen import SchedGen
from lake.utils.util import extract_formal_annotation, safe_wire
from... | lake/modules/spec/tb_formal.py | from kratos import *
from lake.passes.passes import lift_config_reg
from lake.modules.sram_wrapper import SRAMWrapper
from lake.modules.for_loop import ForLoop
from lake.modules.addr_gen import AddrGen
from lake.modules.spec.sched_gen import SchedGen
from lake.utils.util import extract_formal_annotation, safe_wire
from... | 0.524638 | 0.066206 |
from crispy_forms.bootstrap import FormActions
from crispy_forms.helper import FormHelper
from crispy_forms.layout import Layout, Div, Submit, HTML
from dal import autocomplete
from django import forms
from django.urls import reverse
from project_core.forms.utils import cancel_edit_button, cancel_button
from project_c... | ProjectApplication/grant_management/forms/project.py | from crispy_forms.bootstrap import FormActions
from crispy_forms.helper import FormHelper
from crispy_forms.layout import Layout, Div, Submit, HTML
from dal import autocomplete
from django import forms
from django.urls import reverse
from project_core.forms.utils import cancel_edit_button, cancel_button
from project_c... | 0.558447 | 0.088899 |
import os
import requests
from gtts import gTTS
from html import escape
from pyrogram.types import Message
from tronx import app, gen
app.CMD_HELP.update(
{"supertools" : (
"supertools",
{
"ud [query]" : "Get The Meaning Of Any Word In Urban Dictionary.",
"short [link]" : "Shorten a link into da.gd link... | tronx/modules/supertools.py | import os
import requests
from gtts import gTTS
from html import escape
from pyrogram.types import Message
from tronx import app, gen
app.CMD_HELP.update(
{"supertools" : (
"supertools",
{
"ud [query]" : "Get The Meaning Of Any Word In Urban Dictionary.",
"short [link]" : "Shorten a link into da.gd link... | 0.117458 | 0.123577 |
from __future__ import print_function
import socket
from empire.server.common.plugins import Plugin
import empire.server.common.helpers as helpers
class Plugin(Plugin):
description = "Empire reverseshell stager server plugin."
def onLoad(self):
print(helpers.color("[*] Loading Empire reverseshell s... | empire/server/plugins/reverseshell_stager_server.py | from __future__ import print_function
import socket
from empire.server.common.plugins import Plugin
import empire.server.common.helpers as helpers
class Plugin(Plugin):
description = "Empire reverseshell stager server plugin."
def onLoad(self):
print(helpers.color("[*] Loading Empire reverseshell s... | 0.524151 | 0.127002 |
import json
from cafe.engine.models.base \
import AutoMarshallingModel, AutoMarshallingListModel
class VendorMetadata(AutoMarshallingModel):
def __init__(self, network_info=None, region=None,
ip_whitelist=None, roles=None, provider=None):
self.network_info = network_info
sel... | cloudcafe/compute/extensions/config_drive/models/config_drive_vendor_meta.py | import json
from cafe.engine.models.base \
import AutoMarshallingModel, AutoMarshallingListModel
class VendorMetadata(AutoMarshallingModel):
def __init__(self, network_info=None, region=None,
ip_whitelist=None, roles=None, provider=None):
self.network_info = network_info
sel... | 0.516108 | 0.051272 |
import torch
import torch.nn as nn
import torch.nn.functional as F
class _ASPPModule(nn.Module):
def __init__(self, inplanes, planes, kernel_size, padding, dilation):
super(_ASPPModule, self).__init__()
self.atrous_conv = nn.Conv3d(inplanes, planes, kernel_size=kernel_size,
... | models/aspp_3d.py | import torch
import torch.nn as nn
import torch.nn.functional as F
class _ASPPModule(nn.Module):
def __init__(self, inplanes, planes, kernel_size, padding, dilation):
super(_ASPPModule, self).__init__()
self.atrous_conv = nn.Conv3d(inplanes, planes, kernel_size=kernel_size,
... | 0.941975 | 0.478041 |
import pandas as pd
import snowflake.connector
import getpass as pwd
pd.set_option('display.max_rows', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.width', None)
pd.set_option('display.max_colwidth',None)
default_warehouse = 'PROD_ANALYTICS_WH'
ctx = snowflake.connector.connect(
user... | Security/Create_Admin_Roles.py | import pandas as pd
import snowflake.connector
import getpass as pwd
pd.set_option('display.max_rows', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.width', None)
pd.set_option('display.max_colwidth',None)
default_warehouse = 'PROD_ANALYTICS_WH'
ctx = snowflake.connector.connect(
user... | 0.247441 | 0.038322 |
from __future__ import absolute_import, print_function, unicode_literals
from wolframclient.serializers.wxfencoder.constants import (
WXF_HEADER_COMPRESS,
WXF_HEADER_SEPARATOR,
WXF_VERSION,
)
from wolframclient.serializers.wxfencoder.streaming import ZipCompressedWriter
__all__ = ["WXFExprSerializer", "Se... | wolframclient/serializers/wxfencoder/serializer.py | from __future__ import absolute_import, print_function, unicode_literals
from wolframclient.serializers.wxfencoder.constants import (
WXF_HEADER_COMPRESS,
WXF_HEADER_SEPARATOR,
WXF_VERSION,
)
from wolframclient.serializers.wxfencoder.streaming import ZipCompressedWriter
__all__ = ["WXFExprSerializer", "Se... | 0.78695 | 0.351033 |
import numpy as np
from deep_utils.utils.box_utils.boxes import Point
def resize(img, dsize, in_source='Numpy', mode='cv2', interpolation=None):
mode = 'cv2' if mode is None else mode
if mode == 'cv2':
dsize = Point.point2point(dsize, in_source=in_source, to_source=Point.PointSource.CV)
new_im... | deep_utils/utils/resize_utils/main_resize.py | import numpy as np
from deep_utils.utils.box_utils.boxes import Point
def resize(img, dsize, in_source='Numpy', mode='cv2', interpolation=None):
mode = 'cv2' if mode is None else mode
if mode == 'cv2':
dsize = Point.point2point(dsize, in_source=in_source, to_source=Point.PointSource.CV)
new_im... | 0.779741 | 0.400046 |
import re
import json
import PySimpleGUI as GUI
import requests
from time import sleep
from ebooklib import epub
from selenium import webdriver
from selenium.webdriver.firefox.options import Options
from selenium.webdriver.firefox.firefox_binary import FirefoxBinary
# Set the theme for the window
GUI.theme('DarkAmber... | main.py | import re
import json
import PySimpleGUI as GUI
import requests
from time import sleep
from ebooklib import epub
from selenium import webdriver
from selenium.webdriver.firefox.options import Options
from selenium.webdriver.firefox.firefox_binary import FirefoxBinary
# Set the theme for the window
GUI.theme('DarkAmber... | 0.271541 | 0.085633 |
import functools
import hashlib
import hmac
import logging
import os
import random
import string
import time
import msgpack
import base64
import socket
import sys
LOGS_DIR = "logs"
BUFFER_SIZE = 1024
HMAC_PASS_KEY = "<KEY>"
LOG_FORMAT = "%(asctime)s %(levelname)-8s %(message)s"
SOCK_DCCP = 6
IPROTO_DCCP = 33
SOL_D... | checkers/tracker/checker.py | import functools
import hashlib
import hmac
import logging
import os
import random
import string
import time
import msgpack
import base64
import socket
import sys
LOGS_DIR = "logs"
BUFFER_SIZE = 1024
HMAC_PASS_KEY = "<KEY>"
LOG_FORMAT = "%(asctime)s %(levelname)-8s %(message)s"
SOCK_DCCP = 6
IPROTO_DCCP = 33
SOL_D... | 0.354992 | 0.112649 |
import logging
import os
import pprint
import gspread
import pandas
from oauth2client.service_account import ServiceAccountCredentials
# Remove all handlers associated with the root logger object.
for handler in logging.root.handlers[:]:
logging.root.removeHandler(handler)
logging.basicConfig(
level=logging.D... | curation_utils/google/sheets.py | import logging
import os
import pprint
import gspread
import pandas
from oauth2client.service_account import ServiceAccountCredentials
# Remove all handlers associated with the root logger object.
for handler in logging.root.handlers[:]:
logging.root.removeHandler(handler)
logging.basicConfig(
level=logging.D... | 0.447219 | 0.147095 |
__author__ = 'mnowotka'
import StringIO
from chembl_beaker.beaker.draw import cairoCanvas
from chembl_beaker.beaker import draw
from collections import defaultdict
try:
from rdkit import Chem
from rdkit.Chem import AllChem
except ImportError:
Chem = None
Draw = None
AllChem = None
try:
from c... | chembl_webservices/core/utils.py | __author__ = 'mnowotka'
import StringIO
from chembl_beaker.beaker.draw import cairoCanvas
from chembl_beaker.beaker import draw
from collections import defaultdict
try:
from rdkit import Chem
from rdkit.Chem import AllChem
except ImportError:
Chem = None
Draw = None
AllChem = None
try:
from c... | 0.276007 | 0.14445 |
from django.contrib.auth import get_user_model
from django.urls import reverse
from django.test import TestCase
from rest_framework import status
from rest_framework.test import APIClient
from core.models import Tag, Montagem
from montagem.serializers import TagSerializer
TAGS_URL = reverse('montagem:tag-list')
... | app/montagem/tests/test_tags_api.py | from django.contrib.auth import get_user_model
from django.urls import reverse
from django.test import TestCase
from rest_framework import status
from rest_framework.test import APIClient
from core.models import Tag, Montagem
from montagem.serializers import TagSerializer
TAGS_URL = reverse('montagem:tag-list')
... | 0.520009 | 0.255512 |
import numpy as np
import shutil
import urllib
import urlparse
from os.path import splitext, basename
import os
from os import sys, path
import re
from gp import *
from core import *
import math
from IPython.core.debugger import Tracer
from myutils import MyUtils
class DefaultSpecies(object):
def ge... | database/task_class/defaultspecies.py | import numpy as np
import shutil
import urllib
import urlparse
from os.path import splitext, basename
import os
from os import sys, path
import re
from gp import *
from core import *
import math
from IPython.core.debugger import Tracer
from myutils import MyUtils
class DefaultSpecies(object):
def ge... | 0.076533 | 0.071397 |
import time
import uuid
import asyncio
import functools
from typing import *
import datetime
def daterange(start_date: datetime.date, end_date: Optional[datetime.date] = None, end_inclusive: bool = True):
"""Iterate each day between two dates, yielding each found day.
If end_date is None, use current date.
... | twitterscraper/utils.py | import time
import uuid
import asyncio
import functools
from typing import *
import datetime
def daterange(start_date: datetime.date, end_date: Optional[datetime.date] = None, end_inclusive: bool = True):
"""Iterate each day between two dates, yielding each found day.
If end_date is None, use current date.
... | 0.757166 | 0.448668 |
import pytest
import numpy as np
import scipy.linalg
import scipy.sparse
import qutip
if qutip.settings.has_mkl:
from qutip._mkl.spsolve import mkl_splu, mkl_spsolve
pytestmark = [
pytest.mark.skipif(not qutip.settings.has_mkl,
reason='MKL extensions not found.'),
]
class Test_spsolve... | qutip/tests/test_mkl.py | import pytest
import numpy as np
import scipy.linalg
import scipy.sparse
import qutip
if qutip.settings.has_mkl:
from qutip._mkl.spsolve import mkl_splu, mkl_spsolve
pytestmark = [
pytest.mark.skipif(not qutip.settings.has_mkl,
reason='MKL extensions not found.'),
]
class Test_spsolve... | 0.433022 | 0.654315 |
import tensorflow as tf # type: ignore
import tensorflow.keras.layers as L # type: ignore
from board import BOARD_SIZE, BOARD_SQUARES
def residual_block(
x: tf.Tensor, filters: int, separable_convs: bool = False, prefix: str = ""
) -> tf.Tensor:
"""
Make a residual block of layers.
Parameters
... | src/alphazero/model.py | import tensorflow as tf # type: ignore
import tensorflow.keras.layers as L # type: ignore
from board import BOARD_SIZE, BOARD_SQUARES
def residual_block(
x: tf.Tensor, filters: int, separable_convs: bool = False, prefix: str = ""
) -> tf.Tensor:
"""
Make a residual block of layers.
Parameters
... | 0.951818 | 0.694782 |
from functools import wraps
import time
import os
import numpy as np
import logging
from scipy.interpolate import griddata
import xarray as xr
import dask
from dask.distributed import get_client, secede, rejoin
from functools import wraps, partial
import rasterio
import shutil
import glob
import gc
logger = logging.g... | src/xsar/utils.py |
from functools import wraps
import time
import os
import numpy as np
import logging
from scipy.interpolate import griddata
import xarray as xr
import dask
from dask.distributed import get_client, secede, rejoin
from functools import wraps, partial
import rasterio
import shutil
import glob
import gc
logger = logging.g... | 0.796015 | 0.354796 |
import asyncio
import collections
import json
import os
from typing import Dict, List
import click
import humanfriendly
import tabulate
from cobras.client.client import subscribeClient, unsafeSubcribeClient
from cobras.client.connection import ActionFlow
from cobras.common.algorithm import transpose
from cobras.common... | cobras/client/monitor.py | import asyncio
import collections
import json
import os
from typing import Dict, List
import click
import humanfriendly
import tabulate
from cobras.client.client import subscribeClient, unsafeSubcribeClient
from cobras.client.connection import ActionFlow
from cobras.common.algorithm import transpose
from cobras.common... | 0.584153 | 0.119254 |
from trac.core import Component, implements, TracError
from trac.web.chrome import add_stylesheet
from announcer.api import IAnnouncementSubscriber
from announcer.api import IAnnouncementPreferenceProvider
from announcer.api import _
from announcer.query import *
class RuleBasedTicketSubscriber(Component):
... | announcer/subscribers/rulefilters.py |
from trac.core import Component, implements, TracError
from trac.web.chrome import add_stylesheet
from announcer.api import IAnnouncementSubscriber
from announcer.api import IAnnouncementPreferenceProvider
from announcer.api import _
from announcer.query import *
class RuleBasedTicketSubscriber(Component):
... | 0.307774 | 0.096877 |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
from warnings import warn
from iminuit.iminuit_warnings import InitialParamWarning
from iminuit import util as mutil
import numpy as np
def pedantic(self, parameters, kwds, errordef):
def w(msg):
w... | iminuit/_minuit_methods.py | from __future__ import (absolute_import, division, print_function,
unicode_literals)
from warnings import warn
from iminuit.iminuit_warnings import InitialParamWarning
from iminuit import util as mutil
import numpy as np
def pedantic(self, parameters, kwds, errordef):
def w(msg):
w... | 0.591723 | 0.539347 |
from time import perf_counter_ns
import pytest
from didcomm.pack_encrypted import PackEncryptedConfig, pack_encrypted
from didcomm.unpack import unpack, UnpackConfig
from tests.test_vectors.common import BOB_DID, ALICE_DID
from tests.test_vectors.didcomm_messages.messages import TEST_MESSAGE
RECIPIENT_KEYS_COUNT = [... | tests/performance/test_performance.py | from time import perf_counter_ns
import pytest
from didcomm.pack_encrypted import PackEncryptedConfig, pack_encrypted
from didcomm.unpack import unpack, UnpackConfig
from tests.test_vectors.common import BOB_DID, ALICE_DID
from tests.test_vectors.didcomm_messages.messages import TEST_MESSAGE
RECIPIENT_KEYS_COUNT = [... | 0.41324 | 0.230313 |
from tkinter import messagebox
from os import path
from tkinter.constants import DISABLED, NORMAL
from babel.localedata import load
import simplejson as json
from threading import Thread
from multiprocessing.dummy import Process
import requests
import pyodbc
from datetime import datetime
from tkinter import messagebox... | dev/export-service-sale-py/utils.py | from tkinter import messagebox
from os import path
from tkinter.constants import DISABLED, NORMAL
from babel.localedata import load
import simplejson as json
from threading import Thread
from multiprocessing.dummy import Process
import requests
import pyodbc
from datetime import datetime
from tkinter import messagebox... | 0.394084 | 0.124479 |
from django.shortcuts import render, get_object_or_404
from django.contrib.auth.decorators import login_required
from django.http import HttpResponseRedirect
from products.models import Product
from django.contrib import messages
from .models import UserFavoriteslist
from profiles.models import UserProfile
# Function... | favorites/views.py | from django.shortcuts import render, get_object_or_404
from django.contrib.auth.decorators import login_required
from django.http import HttpResponseRedirect
from products.models import Product
from django.contrib import messages
from .models import UserFavoriteslist
from profiles.models import UserProfile
# Function... | 0.487063 | 0.08152 |
from .image import subimage_by_roi
import astimp
class Antibiotic():
"an antibiotic tested in an AST"
def __init__(self, short_name, pellet_circle, inhibition, image, roi, px_per_mm):
self.short_name = short_name
self.pellet_circle = pellet_circle
self.inhibition = inhibition
s... | python-module/astimp_tools/datamodels.py | from .image import subimage_by_roi
import astimp
class Antibiotic():
"an antibiotic tested in an AST"
def __init__(self, short_name, pellet_circle, inhibition, image, roi, px_per_mm):
self.short_name = short_name
self.pellet_circle = pellet_circle
self.inhibition = inhibition
s... | 0.656878 | 0.219693 |
from Actors import Teacher, Opening
import random
class Matcher:
# TODO this shouldn't take teachers and openings, but preferences
def __init__(self, teachers, openings):
# TODO comment
self.teachers = teachers
self.openings = openings
self.actors = teachers + openings
... | Matching Algo/Matching Algorithm/Matching Algorithm/match.py | from Actors import Teacher, Opening
import random
class Matcher:
# TODO this shouldn't take teachers and openings, but preferences
def __init__(self, teachers, openings):
# TODO comment
self.teachers = teachers
self.openings = openings
self.actors = teachers + openings
... | 0.291989 | 0.339089 |
from marshmallow import Schema, fields, post_dump
from sqlalchemy.sql import expression
from app import db
class AIModel(db.Model):
__tablename__ = 'model'
id = db.Column(db.Integer, primary_key=True)
category = db.Column(db.String)
uuid = db.Column(db.String)
author = db.Column(db.String)
upd... | web/models/AIModel.py | from marshmallow import Schema, fields, post_dump
from sqlalchemy.sql import expression
from app import db
class AIModel(db.Model):
__tablename__ = 'model'
id = db.Column(db.Integer, primary_key=True)
category = db.Column(db.String)
uuid = db.Column(db.String)
author = db.Column(db.String)
upd... | 0.629091 | 0.065485 |
from rest_framework import exceptions, status
from rest_framework.views import APIView
from magpie.apps.files.versions.v1.services.consumer import ConsumerService
from magpie.core.permissions import AdminAPIUserPermission
from magpie.core.response import response
class ConsumersAPIView(APIView):
permission_class... | magpie/apps/files/versions/v1/api/consumer.py | from rest_framework import exceptions, status
from rest_framework.views import APIView
from magpie.apps.files.versions.v1.services.consumer import ConsumerService
from magpie.core.permissions import AdminAPIUserPermission
from magpie.core.response import response
class ConsumersAPIView(APIView):
permission_class... | 0.519278 | 0.062103 |
try:
from numpy import array, transpose
import pandas as pd
from sklearn.model_selection import cross_val_score, cross_validate
from time import time
from sklearn.svm import SVC
except Exception as e:
print(e)
raise Exception('Alguns módulos não foram instalados...')
class MyGridSearch:
... | utils/myGridSearch.py | try:
from numpy import array, transpose
import pandas as pd
from sklearn.model_selection import cross_val_score, cross_validate
from time import time
from sklearn.svm import SVC
except Exception as e:
print(e)
raise Exception('Alguns módulos não foram instalados...')
class MyGridSearch:
... | 0.698946 | 0.325092 |
import os
import time
import threading
import random
import gevent
import uuid
import sha
import logging
import functools
import contextlib
from sqlalchemy import event
from sqlalchemy import create_engine as sqlalchemy_create_engine
from sqlalchemy.ext.declarative import declarative_base, DeclarativeMeta
from sqlalc... | rest_arch/db.py |
import os
import time
import threading
import random
import gevent
import uuid
import sha
import logging
import functools
import contextlib
from sqlalchemy import event
from sqlalchemy import create_engine as sqlalchemy_create_engine
from sqlalchemy.ext.declarative import declarative_base, DeclarativeMeta
from sqlalc... | 0.403214 | 0.09277 |
import tensorflow as tf
import logging
def flip_left_right():
return lambda x: tf.image.random_flip_left_right(x)
def random_brightness(args_dict):
max_delta = args_dict['max_delta']
assert (max_delta >= 0), logging.fatal("'max_delta' argument to "
"tf.image.ra... | data/preprocessing.py | import tensorflow as tf
import logging
def flip_left_right():
return lambda x: tf.image.random_flip_left_right(x)
def random_brightness(args_dict):
max_delta = args_dict['max_delta']
assert (max_delta >= 0), logging.fatal("'max_delta' argument to "
"tf.image.ra... | 0.874654 | 0.503235 |
import cv2
from matplotlib.pyplot import spring
import tqdm
import math
import numpy as np
from linalg import get_center_of_mass, get_line_equation, get_perpendicular_line_equation3d, get_plane_equation, point2line_vector, rotate3d, signed_plane_point_distance, normalize
from utils import load_points_and_faces_and_spri... | engine.py | import cv2
from matplotlib.pyplot import spring
import tqdm
import math
import numpy as np
from linalg import get_center_of_mass, get_line_equation, get_perpendicular_line_equation3d, get_plane_equation, point2line_vector, rotate3d, signed_plane_point_distance, normalize
from utils import load_points_and_faces_and_spri... | 0.439026 | 0.319453 |
import configparser
import pyautogui
import cv2
import time
import winsound
import playsound
import random
import numpy
import win32gui
import win32con
import wmi
import tkinter
import multiprocessing
import os
import win32file
import struct
import requests
import re
from datetime import datetime
from multiprocessing i... | cl.py | import configparser
import pyautogui
import cv2
import time
import winsound
import playsound
import random
import numpy
import win32gui
import win32con
import wmi
import tkinter
import multiprocessing
import os
import win32file
import struct
import requests
import re
from datetime import datetime
from multiprocessing i... | 0.143038 | 0.069479 |
import base64
import os
import cryptography
from cryptography.fernet import Fernet
from cryptography.hazmat.backends import default_backend
from cryptography.hazmat.primitives import hashes
from cryptography.hazmat.primitives.kdf.pbkdf2 import PBKDF2HMAC
from . import config
class Remindme:
'''A user's single rem... | remindme/Remindme.py | import base64
import os
import cryptography
from cryptography.fernet import Fernet
from cryptography.hazmat.backends import default_backend
from cryptography.hazmat.primitives import hashes
from cryptography.hazmat.primitives.kdf.pbkdf2 import PBKDF2HMAC
from . import config
class Remindme:
'''A user's single rem... | 0.576661 | 0.050705 |
import datetime as dt
import pytest
from rest_framework.reverse import reverse
from rest_framework import status
from appointments import models as m
@pytest.mark.django_db
def test_licence_plate_normalization(appointment_client, appointment):
rv = appointment_client.patch(
reverse("appointment-detail",... | code/backend/appointments/tests/test_appointments.py | import datetime as dt
import pytest
from rest_framework.reverse import reverse
from rest_framework import status
from appointments import models as m
@pytest.mark.django_db
def test_licence_plate_normalization(appointment_client, appointment):
rv = appointment_client.patch(
reverse("appointment-detail",... | 0.582729 | 0.338856 |
# Force Python 2 to use float division even for ints
from __future__ import division
from __future__ import print_function
import importlib
import logging
import os
import re
import time
import stacktrain.config.general as conf
import stacktrain.kvm.vm_create as vm
import stacktrain.core.iso_image as iso_image
impo... | labs/stacktrain/kvm/install_base.py |
# Force Python 2 to use float division even for ints
from __future__ import division
from __future__ import print_function
import importlib
import logging
import os
import re
import time
import stacktrain.config.general as conf
import stacktrain.kvm.vm_create as vm
import stacktrain.core.iso_image as iso_image
impo... | 0.531453 | 0.092852 |
__all__ = ['pnsequence', 'zcsequence']
import numpy as np
from numpy import empty, exp, pi, arange, int8, fromiter, sum
def pnsequence(pn_order, pn_seed, pn_mask, seq_length):
"""
Generate a PN (Pseudo-Noise) sequence using a Linear Feedback Shift Register (LFSR).
Seed and mask are ordered so that:
... | commpy/sequences.py | __all__ = ['pnsequence', 'zcsequence']
import numpy as np
from numpy import empty, exp, pi, arange, int8, fromiter, sum
def pnsequence(pn_order, pn_seed, pn_mask, seq_length):
"""
Generate a PN (Pseudo-Noise) sequence using a Linear Feedback Shift Register (LFSR).
Seed and mask are ordered so that:
... | 0.906424 | 0.68225 |
from __future__ import (
unicode_literals,
absolute_import,
print_function,
division,
)
str = type('')
import sys
import io
import mmap
import compoundfiles.mmap as fake_mmap
import pytest
@pytest.fixture(scope='session')
def source():
return io.open('tests/mmap.dat', 'rb')
@pytest.fixture... | tests/test_mmap.py |
from __future__ import (
unicode_literals,
absolute_import,
print_function,
division,
)
str = type('')
import sys
import io
import mmap
import compoundfiles.mmap as fake_mmap
import pytest
@pytest.fixture(scope='session')
def source():
return io.open('tests/mmap.dat', 'rb')
@pytest.fixture... | 0.522689 | 0.637405 |
from asyncio import sleep
import os
import discord
from replit import db
from keep_alive import keep_alive
from discord.ext import commands
from pretty_help import DefaultMenu, PrettyHelp
def get_prefix(bot, message):
"""A callable Prefix for our bot. This could be edited to allow per server prefixes."""
pref... | bot/main.py | from asyncio import sleep
import os
import discord
from replit import db
from keep_alive import keep_alive
from discord.ext import commands
from pretty_help import DefaultMenu, PrettyHelp
def get_prefix(bot, message):
"""A callable Prefix for our bot. This could be edited to allow per server prefixes."""
pref... | 0.379378 | 0.092442 |
import copy
import os
import time
import sys
import pandas as pd
import pytest
from unittest.mock import patch, PropertyMock, MagicMock
import geopandas as gpd
import numpy as np
from osgeo import ogr
from plio.io import io_gdal
from autocnet.examples import get_path
from .. import network
from .. import edge
from... | autocnet/graph/tests/test_network.py | import copy
import os
import time
import sys
import pandas as pd
import pytest
from unittest.mock import patch, PropertyMock, MagicMock
import geopandas as gpd
import numpy as np
from osgeo import ogr
from plio.io import io_gdal
from autocnet.examples import get_path
from .. import network
from .. import edge
from... | 0.2522 | 0.3219 |
import csv
import os
import yaml
from box import Box
class Config():
_cfg = None
def __init__(self, src):
self.src = src
@property
def config(self):
if self._cfg is None:
with open(self.src) as f:
self._cfg = Box(yaml.load(f))
return self._cfg
... | src/main.py | import csv
import os
import yaml
from box import Box
class Config():
_cfg = None
def __init__(self, src):
self.src = src
@property
def config(self):
if self._cfg is None:
with open(self.src) as f:
self._cfg = Box(yaml.load(f))
return self._cfg
... | 0.219254 | 0.07208 |
import cv2
import numpy as np
import os
import csv
import sys
from PIL import Image
import random
minValue = 70
skinkernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5, 5))
low_range = np.array([0, 70, 100])
upper_range = np.array([20, 200, 255])
# cv2.imshow("final",img)
# cv2.waitKey(0)
kernel = np.ones((5, 5... | data_loader.py | import cv2
import numpy as np
import os
import csv
import sys
from PIL import Image
import random
minValue = 70
skinkernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5, 5))
low_range = np.array([0, 70, 100])
upper_range = np.array([20, 200, 255])
# cv2.imshow("final",img)
# cv2.waitKey(0)
kernel = np.ones((5, 5... | 0.203312 | 0.182244 |
import sys
import threading
import types
from abc import abstractmethod, ABCMeta
from collections import Container, Iterable, Mapping, defaultdict, OrderedDict
import mock
import six
from future.utils import iteritems
from ducktest.base import PlainTypeWrapper, ContainerTypeWrapper, MappingTypeWrapper, Processor, cha... | ducktest/typing.py | import sys
import threading
import types
from abc import abstractmethod, ABCMeta
from collections import Container, Iterable, Mapping, defaultdict, OrderedDict
import mock
import six
from future.utils import iteritems
from ducktest.base import PlainTypeWrapper, ContainerTypeWrapper, MappingTypeWrapper, Processor, cha... | 0.44553 | 0.121895 |
import json
from wsgi_basic import exception
from wsgi_basic.tests.base import BaseTestCase
import wsgi_basic.tests.config as config
class UserSingleAPITest(BaseTestCase):
def create_user(self, username, password, role):
url = "{s}/v1/users".format(s=config.TARGET_SERVICE_ADDRESS)
payload = dict... | wsgi_basic/tests/api/v1/user/test_single_api.py | import json
from wsgi_basic import exception
from wsgi_basic.tests.base import BaseTestCase
import wsgi_basic.tests.config as config
class UserSingleAPITest(BaseTestCase):
def create_user(self, username, password, role):
url = "{s}/v1/users".format(s=config.TARGET_SERVICE_ADDRESS)
payload = dict... | 0.294824 | 0.088072 |
from json import loads as json_loads
from typing import List
# 3rd party
from pytest import fixture
from flask.testing import FlaskClient
from sqlalchemy.orm import scoped_session
# custom
from test_system.models import Token, Test
from test_system.routes.tests import ROUTE
from test_system.constants import PRE_COLLECT... | test/test_test_system/test_routes/test_tests.py | from json import loads as json_loads
from typing import List
# 3rd party
from pytest import fixture
from flask.testing import FlaskClient
from sqlalchemy.orm import scoped_session
# custom
from test_system.models import Token, Test
from test_system.routes.tests import ROUTE
from test_system.constants import PRE_COLLECT... | 0.669529 | 0.475727 |
import tensorflow as tf
import tensorflow.keras as ks
from kgcnn.layers.base import GraphBaseLayer
from kgcnn.ops.partition import partition_row_indexing
from kgcnn.ops.segment import segment_ops_by_name, segment_softmax
@tf.keras.utils.register_keras_serializable(package='kgcnn', name='PoolingLocalEdges')
class Poo... | kgcnn/layers/pool/pooling.py | import tensorflow as tf
import tensorflow.keras as ks
from kgcnn.layers.base import GraphBaseLayer
from kgcnn.ops.partition import partition_row_indexing
from kgcnn.ops.segment import segment_ops_by_name, segment_softmax
@tf.keras.utils.register_keras_serializable(package='kgcnn', name='PoolingLocalEdges')
class Poo... | 0.949623 | 0.456955 |
import numpy as np
import pandas as pd
import statsmodels.api as sm
import statsmodels.formula.api as smf
from stargazer.stargazer import Stargazer
from IPython.core.display import HTML
from IPython.core.interactiveshell import InteractiveShell
from statsmodels.sandbox.regression.gmm import IV2SLS
def create_table1... | auxiliary/Tables.py | import numpy as np
import pandas as pd
import statsmodels.api as sm
import statsmodels.formula.api as smf
from stargazer.stargazer import Stargazer
from IPython.core.display import HTML
from IPython.core.interactiveshell import InteractiveShell
from statsmodels.sandbox.regression.gmm import IV2SLS
def create_table1... | 0.207696 | 0.499512 |
import dearpygui.dearpygui as dpg
import dearpygui.demo as demo
from cartoon_wnd import CartoonWindow
class MainWindow:
MIN_SIZE = (1320, 800)
def __init__(self):
self._cartoon_wnd = CartoonWindow()
self._client_size = (MainWindow.MIN_SIZE[0] - 16, MainWindow.MIN_SIZE[1] - 39)
self._... | main.py |
import dearpygui.dearpygui as dpg
import dearpygui.demo as demo
from cartoon_wnd import CartoonWindow
class MainWindow:
MIN_SIZE = (1320, 800)
def __init__(self):
self._cartoon_wnd = CartoonWindow()
self._client_size = (MainWindow.MIN_SIZE[0] - 16, MainWindow.MIN_SIZE[1] - 39)
self._... | 0.319015 | 0.057414 |