sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
342af4fb0b401f8de47ec45273fa37634bdd6529934c7c85e221c7a328d0b04b | Python | 1,316 | 51 | """
Invent a better (truly unique) GUID system
"""
import glob
import os
import sys
import matplotlib.pyplot as plt
import uuid
import datetime
import time
import hashlib
try:
PATH_HERE = os.path.abspath(os.path.dirname(__file__))
PATH_DATA = os.path.abspath(PATH_HERE+"../../../data/abfs/")
PATH_SRC = os.... |
42dde0be297b279948cf50a1496b4ca1f3e22052a2792d81fe081a36f0388998 | Python | 1,316 | 36 | import torch
import torch.nn as nn
import numpy as np
import torch.distributed as dist
# define the strategy of weight decay
class Save_Scheduler():
def __init__(self,init_weight,final_weight,start_lr,end_lr,scheduler,optim,Prop_class,PES_Normal,PES_Lammps):
self.init_weight = init_weight
self.fina... |
b90ac608f1c41844f1fb46ab239b98a9b38ddf9ccc969d897af59e51db175253 | Python | 1,316 | 36 | import pytest
from rpy2 import rinterface
from rpy2.rinterface import embedded
from rpy2.rinterface_lib import sexp
@pytest.mark.skipif(embedded.rpy2_embeddedR_isinitialized,
reason='Can only be tested before R is initialized.')
def test_set_initoptions():
options = ('--foo', '--bar')
defa... |
ce11e1895781362960a0cc52882da84bfd30f1d583d7029b19b8a17da88a5f36 | Python | 1,316 | 49 | #!/usr/bin/env python
import sys
from pathlib import Path
def get_column_names(file_path, indices):
"""
Get column names based on multiple indices from a tabular file.
"""
file_ext = Path(file_path).suffix.lower()
sep = "," if file_ext == ".csv" else "\t"
with open(file_path) as fh:
... |
db8ad01bba1cffec3ab8a28b73ca6db41e45374a83251cf4347677d7298418c0 | Python | 1,316 | 42 | import json
import statistics
import numpy as np
from matplotlib import pyplot as plt
from angorapy.common.const import PATH_TO_EXPERIMENTS
ids = ['1667916362968118', '1667916362368835', '1667916362351224', '1667916362238643', '1667830229410560',
'1667829693813697', '1667829690921903', '1667829690849747', '16... |
700f9d0a455bf79c9bf6de4f2784f13b96256faea19c15ddee71fb7957e14c31 | Python | 1,317 | 56 | import sqlite3
from datetime import datetime
import click
from flask import current_app
from flask import g
def get_db():
"""Connect to the application's configured database. The connection
is unique for each request and will be reused if this is called
again.
"""
if "db" not in g:
g.db =... |
bb3fc5fd6b07479c2b6aaba4774c9de32064ee2bf100728d9dfac0d8df2a7d7c | Python | 1,317 | 41 | class defaultdict(dict):
"""Back compatible defaultdict: http://code.activestate.com/recipes/523034/"""
def __init__(self, default_factory=None, *a, **kw):
if default_factory is not None and not hasattr(default_factory, "__call__"):
raise TypeError("first argument must be callable")
... |
6a8558afe47e95977a431deef275e3b596b6be17c5b472e373f3748995d5b84f | Python | 1,318 | 41 | #!/usr/bin/env python
#=========================================================================
#
# Copyright NumFOCUS
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://... |
cf261e11b79d2adb9040e54c62c67460a4d8edc20b2314d1f3f298e3b2667fc0 | Python | 1,318 | 45 | from sys import argv
from msp import MSP
msp = MSP()
msp.file = __file__
msp.seed = int(argv[1])
fraction_of_standard_epoch = 5509 / 162706
msp.decay_per_epoch = 0.9 ** fraction_of_standard_epoch
msp.architecture["num_motifs"] = 82
msp.architecture["sparse_spec"] = dict(type="SpatiallySparseAcrossChannels")
msp.arc... |
d2549f870665b8e9ea2f1ea4b74e3b1eb1f45b1ec2e2f52e33787e988a76d785 | Python | 1,318 | 59 | """
Interactive canvas widgets for the portal.
Exposes the arena canvas, the objects placed on it and the state model that
keeps the two in step.
"""
from __future__ import annotations
from .environment_mapping import env_params_to_canvas_state
from .environment_models import (
CanvasArena,
CanvasRingOverlay... |
f954c7f9b555210318e27bcc595e4ea6a1623e8b8d01f03b22eb71661c592174 | Python | 1,318 | 41 | #!/usr/bin/env python
from distutils.core import setup, Extension
from distutils.command.build_ext import build_ext
import numpy
import git
class CustomBuildExtCommand(build_ext):
"""build_ext command for use when numpy headers are needed."""
def run(self):
# Import numpy here, only when headers are... |
27adef73fd128ec2cbfab23b3af3a40f2df12e8866171d9433c871de86cd2bae | Python | 1,319 | 57 |
# import libraries
import pandas as pd
from sklearn.utils import shuffle
import sklearn
import sklearn.model_selection
from fastai import *
from fastai.vision import *
base_path = '/content/FBCG Dataset/Training Set'
# get image file path
path = Path(base_path)
file_path=get_files(path, recurse=True)
print(len(file... |
6b340da0c9dee5899408909ee4d249f5b19cfb340580d89029b8b0d64b0003ba | Python | 1,319 | 45 | """
CREaTor
Copyright (C) 2023 Microsoft Research
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed... |
839a66747a0d9aa8959f7809ea0a71d85da944480a60ea86466581cf96689545 | Python | 1,319 | 68 | import pytest # noqa
from pytest import fixture, parametrize_with_cases
from seqdata import read_vcf
@fixture
def vcf():
raise NotImplementedError
@fixture
def reference():
raise NotImplementedError
def consensus(sample):
raise NotImplementedError
def bed_no_variants():
raise NotImplementedErr... |
9beb9e52a873980958fcdc7611a15a82b587a33e3692116c4f9e388e3e23cccd | Python | 1,319 | 43 | import torch
from nitorch import io
from nitorch.spatial import resize, voxel_size
from nitorch.core.py import fileparts
from glob import glob
root = '.'
odir = f'{root}/lsfm/slide_center_oct/'
device = 'cuda'
for i in range(8, 24):
foct = io.map(f'{root}/oct/slices/unstack/oct.{i:02d}.nii.gz')
centero... |
db3db77da9e2042cb623aa3341ebfceaabe96963e00409edae734cdfd9063eea | Python | 1,319 | 40 | """
Fix unite clustering from L1:
- loss of barcode information under summary picklefile
"""
import os
import pickle
import snapatac2 as sa2
def update_pkl(cid, cll:str = "L1",
from_dir: str = "L2_dlt2_encoder",
prefix = "sa2_clustering",
snap_prefix: str = "nfeat-top_nc50... |
4a3b27e3e494aa7fb22eca952aa6e2773c1de920da52d78fa5bd0e00a72fe6ae | Python | 1,320 | 42 | import unittest
import numpy as np
from torch import nn
import torch
from parameterized import parameterized
from modular_splicing.utils.sequence_utils import (
decode_packed_seq,
map_to_all_seqs_idx,
slice_packed_seq,
)
class PackedSeqTest(unittest.TestCase):
@parameterized.expand([(x,) for x in ... |
74bb63931ab2125e11eb6dbe19695c60a572da7f72698ecaf354755dc54e708b | Python | 1,320 | 43 | """ point array class """
import numpy as np
class DynamicPointArray:
""" A point array that uses a numpy array to store points and
resizes when its capacity is reached. It is used by algorithms
that require the points as an numpy array and append points
incrementally.
"""
def __init__(self, i... |
a53e18839e2d7a67d8a4d2ffa2db4ce25325825729d3bf0198715761a6842dd1 | Python | 1,320 | 45 | from sys import argv
from msp import MSP
msp = MSP()
msp.file = __file__
msp.seed = int(argv[1])
fraction_of_standard_epoch = 64764 / 162706
msp.decay_per_epoch = 0.9 ** fraction_of_standard_epoch
msp.architecture["num_motifs"] = 82
msp.architecture["sparse_spec"] = dict(type="SpatiallySparseAcrossChannels")
msp.ar... |
eb6d83056513964d83cdd855af902380e941a0f1535d07a6c76f3a3e7e2b839a | Python | 1,320 | 41 | # Copyright 2019 Novartis Institutes for BioMedical Research Inc. Licensed
# under the Apache License, Version 2.0 (the "License"); you may not use
# this file except in compliance with the License. You may obtain a copy
# of the License at http://www.apache.org/licenses/LICENSE-2.0. Unless
# required by applicable law... |
12dc31cab53cbf7f4b5d7005f09f1b2dd1955e092789b64262be83a8b4577d3d | Python | 1,322 | 40 | '''
timothe.guyonnet@gmail.com & michael.reimann@epfl.ch
'''
from setuptools import setup, find_packages
setup(
name='parcellation_project',
version='0.2',
install_requires=['rectangle-packer >= 2.0.0',
'numpy >= 1.18.5',
'voxcell >= 2.6.3',
... |
3d1517fac1e2ba47cca4dff0e177208e9a46f5be369dd4440d1f3e3e66dd06a6 | Python | 1,322 | 67 | from typing import List
class NoComponentsAvailableError(Exception):
def __init__(
self,
msg=(
"No components were available. CarbonTracker supports Intel "
"CPUs with the RAPL interface and NVIDIA GPUs."
),
*args,
**kwargs,
):
super().__i... |
b50b88ecc5af4535e4b0ba8180c215ecdec5e2cd463e0f09a53996135335b0c9 | Python | 1,322 | 36 | #!/usr/bin/env python3
import argparse
import tskit
import msprime
import numpy as np
import pyslim
def main(args):
ts = pyslim.update(tskit.load(args.in_path))
ts_recap = pyslim.recapitate(ts, recombination_rate=args.rho, ancestral_Ne=args.Ne)
sampN = np.random.choice(ts_recap.samples(), size=args.N, r... |
fd8096f3b157b62a8f380a786d3f9602016b79e0c9db984027580522cd3676dc | Python | 1,322 | 33 | #! /usr/bin/env python
import os
import pandas as pd
import sys
from sqlalchemy import create_engine
if __name__=='__main__':
"""Create table for meta info on Hi-C libraries.
To be run after placing Hi-C libraries in
'../lib/hic/<Enzyme>/hic_data/<Cell line>/<Replicate>.db'
"""
hic_fp = os.path.... |
471324896ee30159eec1b3b7d06c52920df5c639392736c969a82eed8dd3d272 | Python | 1,323 | 52 | """
Tests to make sure preprocess functions work
"""
import eugene as eu
import pytest
from pathlib import Path
HERE = Path(__file__).parent
@pytest.fixture
def sdata():
sdata = eu.datasets.random1000()
eu.pp.ohe_seqs_sdata(sdata)
return sdata
@pytest.fixture
def ohe_seqs(sdata):
return sdata.ohe_... |
ea6ba1ab4151444a0849bcab980cb45a059ab57a4a3f7a994e4d206f41b100ce | Python | 1,323 | 52 | #!/usr/bin/env python
"""Aggregate qc of all the subjects."""
import os
from argparse import ArgumentParser, RawTextHelpFormatter
from pathlib import Path
import pandas as pd
def get_parser():
"""Build parser object."""
parser = ArgumentParser(description=__doc__, formatter_class=RawTextHelpFormatter)
... |
481493f064bc37593b69bb6329e6599e8c6d3bfea0fd063a9d557d381871699e | Python | 1,324 | 45 | from sys import argv
from msp import MSP
msp = MSP()
msp.file = __file__
msp.seed = int(argv[1])
fraction_of_standard_epoch = 9241 / 162706
msp.decay_per_epoch = 0.9 ** fraction_of_standard_epoch
msp.architecture["num_motifs"] = 82
msp.architecture["sparse_spec"] = dict(type="SpatiallySparseAcrossChannels")
msp.arc... |
4859e5fcbd8d933159bb68183e2a40835c89ca70e9d1f1c78a3984b22cf1abfa | Python | 1,324 | 43 | import numpy as np
import cv2 as cv
from F01 import Feature
class F03(Feature):
def get_map(self, img, img_f01, eroded_roi):
map_float32 = self.get_map_float32(img, img_f01, eroded_roi, normalize=False)
return np.uint8(map_float32)
def get_map_float32(self, img, img_f01, eroded_roi, normaliz... |
4a970d5642d74be64ff0ec8b2062528b49524bc2bc1f0de6cd26fbafbddf559b | Python | 1,324 | 31 | import gpytorch
from gpytorch.models import ApproximateGP, ExactGP
from gpytorch.variational import CholeskyVariationalDistribution, VariationalStrategy
class Approx_GPModel(ApproximateGP):
def __init__(self, inducing_points):
variational_distribution = CholeskyVariationalDistribution(inducing_points.size... |
55409432dc9efcf06f9a4e3769256d0b162670cf6d523dc0db82d183d0181239 | Python | 1,324 | 44 | # coding=utf-8
# Copyright 2022 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... |
c720ab53bd555eb5691d83e9a8a0de7106eb6755225d6d9cd7fb9824be61a246 | Python | 1,324 | 31 | import torch
from torch.utils.data import Dataset
class AuxAttnDataset(Dataset):
def __init__(self, size_A, size_B, device, init_method='one', mask_size=256, given_constant=1):
super(AuxAttnDataset, self).__init__()
self.A_size, self.B_size = size_A, size_B
if init_method == 'one':
... |
ef5d4fceef8231cd479e33423151e29fe18ae2a0883e34ead744a7b6d58392f0 | Python | 1,325 | 46 | from sys import argv
from msp import MSP
msp = MSP()
msp.file = __file__
msp.seed = int(argv[1])
msp.architecture["num_motifs"] = 82
msp.architecture["sparse_spec"] = dict(type="SpatiallySparseAcrossChannels")
msp.architecture["motif_model_spec"] = dict(
type="AdjustedMotifModel",
model_to_adjust_spec=dict(
... |
081f21dfd10c061406d275aab2442302e00bdbe1fde5908bfa59695c8090782b | Python | 1,326 | 47 | #!/usr/bin/env python3
"""
Barebones utility for changing the name of the package in `pyproject.toml`.
"""
import re
from argparse import ArgumentParser
from pathlib import Path
import tomli
import tomli_w
def main():
parser = ArgumentParser(
description="Script for changing the name of a project in a py... |
98736779b035a316be5de7ba906bf63f8611fb2df84336b8ca5d00e61755f2ac | Python | 1,326 | 44 | import sys
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from ._connector import Connector
from ._decreasing import Decreasing
from ._hoverlabel import Hoverlabel
from ._increasing import Increasing
from ._insidetextfont import Insidetextfont
from ._legendgrouptitle import Legendgrouptitle... |
f59ca3761515bebb7ac4b74e30e5533cdee08f274b59018daf886f1683eba2e0 | Python | 1,326 | 40 | """Implementation for the app.events shortcuts."""
from contextlib import contextmanager
from kombu.utils.objects import cached_property
class Events:
"""Implements app.events."""
receiver_cls = 'celery.events.receiver:EventReceiver'
dispatcher_cls = 'celery.events.dispatcher:EventDispatcher'
state_... |
3a96d9224f501f0392fd266f3064926d5f99e90f5b7a53e7b64a32e7eb62fa8a | Python | 1,327 | 47 | """
Ethoscope Node API Package
This package contains modular API components for the Ethoscope Node Server.
Each module handles a specific domain of functionality to improve maintainability
and separation of concerns.
Modules:
- base: Common infrastructure and utilities
- device_api: Device management and control
- ba... |
5fe41afe3ea350d0fc2aed102160db9836699fb7a9f4b9e5b70b04697778e9f7 | Python | 1,327 | 41 | import tensorflow as tf
from sklearn.model_selection import GridSearchCV
from tensorflow.keras.wrappers.scikit_learn import KerasClassifier
from codecarbon import EmissionsTracker
def build_model():
model = tf.keras.models.Sequential(
[
tf.keras.layers.Flatten(input_shape=(28, 28)),
... |
c86335051bcdbde0c4efe65e1120926027c143a15df0e6a9cd3cbc7489fe730f | Python | 1,327 | 47 | from sys import argv
from msp import MSP
msp = MSP()
msp.file = __file__
msp.seed = int(argv[1])
msp.architecture["num_motifs"] = 82
msp.architecture["sparse_spec"] = dict(type="SpatiallySparseAcrossChannels")
msp.architecture["motif_model_spec"] = dict(
type="AdjustedMotifModel",
model_to_adjust_spec=dict(
... |
d49c1266ef86b374a7357a9b197178931f5e7b9604f1669e820db41734853d7f | Python | 1,327 | 31 | import argparse
parser = argparse.ArgumentParser(description="")
# parser.add_argument('--input_tsv', type=str, help="")
parser.add_argument('--input_probs', nargs='+', help="")
parser.add_argument('--output_csv', type=str, help="")
parser.add_argument('--params', nargs='+', help="")
args = parser.parse_args()
#wit... |
edb04254f5d24e12d26b71ba8367f18d248f46b02d75683cac2b34af1a63fc61 | Python | 1,327 | 45 | import cv2
import os
import numpy as np
class Combine_Image():
def __init__(self, path_AB):
self.path_AB = path_AB
if not os.path.exists(path_AB):
os.makedirs(path_AB)
def combine_image(self, path_A, path_B):
img_A = cv2.imread(path_A)
img_B = cv2.imread(path_B)
... |
5eb0313f0cd8b08373c9e60f75976f46a7e564947557eecbbd59db68fadd275f | Python | 1,328 | 43 | import urllib
from pl_bolts.datasets.base_dataset import LightDataset
from pl_bolts.datasets.cifar10_dataset import CIFAR10, TrialCIFAR10
from pl_bolts.datasets.concat_dataset import ConcatDataset
from pl_bolts.datasets.dummy_dataset import (
DummyDataset,
DummyDetectionDataset,
RandomDataset,
RandomDi... |
f275e7b7c05b93f0c895231874b828bcfc7b96b7b46f5966d9f4048e829b6f40 | Python | 1,329 | 47 | import numpy as np
from sklearn.metrics import f1_score
from sklearn.metrics.cluster import adjusted_mutual_info_score
def cal_ami(a1, a2):
labels1 = a1.astype(np.int16)
labels2 = a2.astype(np.int16)
ami = adjusted_mutual_info_score(labels1.flatten(), labels2.flatten())
return ami
def ca... |
37caf6d45adfd10b9c5688db936cfcdd659a34b48b26da96be7e01de39e87fdd | Python | 1,330 | 33 | from ovseg.preprocessing.SegmentationPreprocessing import SegmentationPreprocessing
from ovseg import OV_PREPROCESSED
import os
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("raw_data", default='OV04', nargs='+',)
args = parser.parse_args()
raw_data = args.raw_data
data_name = '_'.join(sorted... |
684d4a189d80c90c8b701547cbce31d37862be095c9101e9998164b53456af75 | Python | 1,330 | 40 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import numpy as np
import json
pages_db = "./pages_db.json"
def get_total_number_of_epochs(f_name):
with open(pages_db) as f:
pages_data = json.load(f)
try:
number_of_epochs = pages_data[f_name]
except IOError:
"No key in json file!"
return number_of_epoch... |
d51d977f8fe0ebad6dbabd6b747266b264f46756b869b261de846228926a02b4 | Python | 1,330 | 42 | import os
import warnings
from typing import Callable, Dict, Optional
MISSING_PACKAGE_WARNINGS: Dict[str, int] = {}
WARN_MISSING_PACKAGE = int(os.environ.get("WARN_MISSING_PACKAGE", False))
def warn_missing_pkg(
pkg_name: str,
pypi_name: Optional[str] = None,
extra_text: Optional[str] = None,
stdout... |
08c3e180897a8c476a2c2157a338c246a890444c3bd58ed743e9f625e37431a8 | Python | 1,331 | 38 | """
This module create TransformerClassifPerProt
"""
# pylint: disable=W0223
import logging
import torch.nn as nn
from torch.nn.modules.dropout import Dropout
class TransformerClassifPerProtChangeDropout(nn.Module):
"""
This class define a Transformer model that classify an entire protein to ONE classe
""... |
1773711391fc66c485d695a0c9beb563dc58ba80bfb9ac0203e9a782f6f7a5d4 | Python | 1,331 | 17 | __doc__ = """
Copyright (C) 2014 Ingo Fruend
This code reproduces the analyses in the paper
Fruend, Wichmann, Macke (2014): Quantifying the effect of inter-trial dependence on perceptual decisions. J Vis, 14(7): 9.
Permission is hereby granted, free of charge, to any person obtaining a copy of this softwar... |
2ea81102f66b5c446ce37c13b36c029eb01e4f8043e88174554243d57f3ca9e9 | Python | 1,331 | 37 |
# %% Create a group level brain mask for SPM
'''
Loops through every participant's brain mask generated by fmriprep and creates
a group level mask that includes all voxels that had at least 2 participants brain
mask
'''
from nilearn import plotting
import nibabel as nib
import numpy as np
from nilearn.image import new... |
82b951307c2624504d8d4e093f445440c90491d493a21981b9fadeef0d3ca833 | Python | 1,331 | 38 | import socket
import os
hostname = socket.gethostname()
if 'vogel' in hostname:
from .local_vogel import *
elif 'zog' in hostname:
from .local_zog import *
elif 'magpi' in hostname:
# Magpi Rev C and Rev D board revisions have different hardware
# (solenoid vs servo hopper). To be sure we use the corr... |
f25336058ed29285244ba8fddf81ac012ebc7c4b9f26e9137390c91820370912 | Python | 1,331 | 39 | from __future__ import print_function
import sys
import unittest
import SimpleITK as sitk
class TransformixImageFilterTest(unittest.TestCase):
"""Test the deformation field api"""
def setUp(self):
pass
def test_TransformixImageFilter_GetDeformationField(self):
fixedImage = sitk.Image( ... |
bfcdbfd99e97f01e3b10a8ad8f6f8e349bf311024ebced109894497e460b7065 | Python | 1,332 | 44 | """Wrapper for transforming the reward."""
from typing import Callable
import gym
from gym import RewardWrapper
class TransformReward(RewardWrapper):
"""Transform the reward via an arbitrary function.
Warning:
If the base environment specifies a reward range which is not invariant under :attr:`f`, t... |
67db8535668e486366d330a2d56525403b325fa56ecbf8f3a3daff5c4bdde022 | Python | 1,333 | 42 | import sqlite3
from .db import DB
class DistrictInformation(DB):
def __init__(self):
super().__init__()
self.table_name = 'HR_district_info'
self.table_desc = 'Haryana district-wise case information'
self.cols = self.getcolumns()
def getcolumns(self):
cols = {
... |
d7acadf13f25cd1bf6293adf810262466ae5f8975ce1362dc8af3297e13e4651 | Python | 1,333 | 40 | import tensorflow as tf
from tensorflow.python.client.device_lib import list_local_devices
import os
def is_multi_gpu_model(model):
'''Checks if the model supports multi-GPU data parallelism.'''
return hasattr(model, 'is_multi_gpu_model') and model.is_multi_gpu_model
def get_gpu_count():
'''Returns the n... |
15de739f4c433f9530d97d1e2eb6e6e5effc5af0de53d5d825dc2bad5c9a5c57 | Python | 1,334 | 37 | import os
from shutil import copy
def check_dir_exists(path):
if not os.path.exists(path):
os.mkdir(path)
def split_by_name(dir_path, real_save_path, fake_save_path):
check_dir_exists(real_save_path)
check_dir_exists(fake_save_path)
if not os.path.exists(real_save_path):
os.mkdir(real... |
565173bd8b77b1920cb27aea4912277eac0b4deb63ad4a2338ab64bcc6cf5a5b | Python | 1,334 | 46 | from selenium import webdriver
from selenium.webdriver.common.keys import Keys
from selenium.webdriver.support import ui
from bs4 import BeautifulSoup
import os, os.path
import time
driver = webdriver.Chrome("/opt/bin/chromedriver")
import traceparts_parameters as tp
tp.login(driver)
time.sleep(5) # wait for page... |
2155b8e5929a80104f2e4798fa1dbcad4d7ea7abf76427174a0fc34348a6171a | Python | 1,335 | 40 | import sys, os
sys.path.insert(0, os.path.abspath('../../src'))
from moxel import __version__ as version
# Configuration file for the Sphinx documentation builder.
#
# For the full list of built-in configuration values, see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Projec... |
26e369291be8770cb609660cc81491aed94ac938cae19645a7f71ac6b318de5b | Python | 1,335 | 43 | #!/usr/bin/env python
#=========================================================================
#
# Copyright NumFOCUS
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://... |
54ae07de208aaf6bf500b773eac833271c192bcdad51551647e7a65a74f8eeb7 | Python | 1,335 | 42 | import numpy as np
def test_distance_calculations():
from pyrosm.distance import Unit, haversine
# Example line from Null Island to 10'10 --> should be ~1569 km
lon1, lat1 = np.array(0.0, dtype=np.float), np.array(0.0, dtype=np.float)
lon2, lat2 = np.array(10.0, dtype=np.float), np.array(10.0, dtype=... |
8b0a603afbbc60286511047859b1687aa5a10492f478d0810ee4e7514235b56b | Python | 1,335 | 33 | # Written by Seonwoo Min, Seoul National University (mswzeus@gmail.com)
# Some parts of the code were referenced from or inspired by below
# - Tristan Bepler's code (https://github.com/tbepler/protein-sequence-embedding-iclr2019)
# PLUS
""" Solubility FASTA file loading functions """
import numpy as np
import torch
... |
bfb0d7a3858d41e1da9255f3eda813a2f467c9621cd52a8a9afbcfacaf602a31 | Python | 1,335 | 36 | try:
import pytabprops
import unittest
from os.path import join, abspath
from numpy.testing import assert_allclose
from tests.tabulation.turb_adiabatic_equilibrium.rebless import run
from spitfire.chemistry.library import Library
from spitfire.chemistry.ctversion import check as cantera_ve... |
25f8937cf6bc76a60d4d29b2ecb43176f518cba94e82e3cf7fc86cb8e3aafea8 | Python | 1,336 | 35 | from types import SimpleNamespace
from ..data.pipeline import load_peaks
from modular_splicing.motif_names import get_motif_names
def peak_names(*, replicate_category):
"""
Get the names of the peaks for a given replicate category.
"""
return sorted(load_peaks(replicate_category=replicate_category))
... |
2fd893bdd40fa5bd3f0ff3b03effcb787c82d5a87f524b3f64984c5cb1108560 | Python | 1,336 | 33 | import numpy as np
import pandas as pd
from pyreadr import pyreadr
from utils.utils import plot_roc_curve, plot_pr
if __name__ == '__main__':
"""
Script to plot roc curves and pr curves.
"""
task = 'mortality'
population = pd.read_pickle(f'./data/{task}/population.pkl')
outcomes = population[... |
54ea737c69301db44e2d93121ff78b072e01adcec906283a3fd9857ea74f9fe4 | Python | 1,336 | 47 | import os
import utils
import yaml
import joblib
from sklearn.feature_selection import SelectKBest
from sklearn.pipeline import Pipeline
from sksurv.datasets import get_x_y
from sksurv.linear_model import CoxPHSurvivalAnalysis
from skopt.space import Real, Categorical, Integer
def preprocess_data(dataset, config):
... |
9892086b5a43625cd8c8f5729756e0cdd844fd6b0060208e066dae7eb7d4099d | Python | 1,336 | 47 | import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
from plot_params import get_plot_params
get_plot_params()
from ase import units
def arhenius_rate(T, Ga):
hbar = 6.582119569e-16 # eV s
A = units.kB * T / hbar
return A * np.exp(-Ga / (units.kB * T))
if __name__ == "__main__":... |
8d7af50eb780ece26b55e656bb267be77a34fa82f7b37aa51120112a4396368b | Python | 1,337 | 34 | from __future__ import annotations
import logging
import warnings
from bream4.device_interfaces.devices.base_device import BaseDeviceInterface
from bream4.toolkit.procedure_components.voltage_operations import apply_voltages_for_durations
class GlobalFlick(object):
def __init__(self, config: dict, device: BaseD... |
e206cd2c3d296a12d043d8656799bce282f4c771c3e55a84e72cc2b000fa853d | Python | 1,337 | 42 | #!/usr/bin/env python
'''Given a results.dat file and password for db, put the contents into google sql as
configurations that are being requested. Specify five of each.'''
import sys, re, MySQLdb
import pandas as pd
import makemodel
import numpy as np
opts = makemodel.getoptions()
def addrows(fname,host,db,passwo... |
0186540087fc1ff480fb52a5eb88119ea68079c643a58994bc0de1fc70dff27a | Python | 1,338 | 33 | # Written by Seonwoo Min, Seoul National University (mswzeus@gmail.com)
# Some parts of the code were referenced from or inspired by below
# - Tristan Bepler's code (https://github.com/tbepler/protein-sequence-embedding-iclr2019)
# PLUS
""" Stability FASTA file loading functions """
import numpy as np
import torch
... |
2b654251872dc59dfc39a13ddeeed80ebc2e842ef832a3229e7901486f9bf13b | Python | 1,338 | 53 | #!/usr/bin/python
import sys
import os
import re
import pandas as pd
import numpy as np
import math
import json
import glob
##### return unique element in list #####
def unique(a):
unique = []
[unique.append(s) for s in a if s not in unique]
return unique
def main():
##### check argument #####
if len(sys.argv)<2... |
4219c13d847bb0917c41f1ceebe2f85615fded8414347f0620baca855b1f0453 | Python | 1,338 | 50 | #!/usr/bin/python
import sys
import os
import re
import numpy as np
import pandas as pd
import ConfigParser
import json
def main():
##### check argument #####
if len(sys.argv)<3:
sys.exit("ERROR: not enough arguments\nUSAGE ./celltype_perDatasetPlotData.py <filedir> <ds>")
##### get command line arguments #####
... |
5ff5785f5323671df9082f1c8c1c07122a14382a8ddd69ba50e4be5c5e2703dd | Python | 1,338 | 52 | from celery.app.annotations import MapAnnotation, prepare
from celery.utils.imports import qualname
class MyAnnotation:
foo = 65
class AnnotationCase:
def setup_method(self):
@self.app.task(shared=False)
def add(x, y):
return x + y
self.add = add
@self.app.task(... |
618e3cae5473e6beba8df37f848262df59ccf78f4ca56dafb461d0e813da9bb9 | Python | 1,338 | 51 | import attr
import scipy.stats
@attr.s
class Accuracy:
"""
Represents the accuracy of a prediction.
The accuracy is represented as a mean value, and a confidence interval (95% by default).
"""
mean = attr.ib()
low = attr.ib()
hi = attr.ib()
@staticmethod
def of(matr, confidence... |
da965208ebf404153769f034c8c78191c4c70a05d7107aad891b156c66902f19 | Python | 1,338 | 41 | import pytest
import glob
import os
import sys
import pathlib
PATH_HERE = os.path.abspath(os.path.dirname(__file__))
PATH_PROJECT = os.path.abspath(PATH_HERE+"/../")
PATH_DATA = os.path.abspath(PATH_PROJECT+"/data/abfs/")
PATH_HEADERS = os.path.abspath(PATH_PROJECT+"/data/headers/")
try:
# this ensures pyABF is im... |
43e46a3772010988be06c3c8b3c530d681a941ef13319bcffaad7756be94fcf1 | Python | 1,339 | 42 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Mar 7 15:05:52 2022
@author: psicobiologia
"""
import numpy as np
from sklearn import metrics
from statsmodels.stats.contingency_tables import mcnemar
# define full path to target variable
target_path = '/path_to_target/target.csv'
# define full path... |
2dd7acb6bd579fd88bb0d1092f8a2d93beae9535df29b51d0924fafe3f3e0070 | Python | 1,340 | 26 | # Copyright 2019 Novartis Institutes for BioMedical Research Inc. Licensed
# under the Apache License, Version 2.0 (the "License"); you may not use
# this file except in compliance with the License. You may obtain a copy
# of the License at http://www.apache.org/licenses/LICENSE-2.0. Unless
# required by applicable law... |
5a0a5ce7017a69a9e5e273256cd31df29a7663bcd00afc8c0f4b8ccafa8a66db | Python | 1,340 | 45 | # -*- coding: utf-8 -*-
# @Author: gviejo
# @Date: 2022-01-17 23:01:05
# @Last Modified by: gviejo
# @Last Modified time: 2022-02-07 18:01:14
import numpy as np
import pandas as pd
import pynapple as nap
from matplotlib.pyplot import *
import pynacollada as pyna
from sklearn.manifold import Isomap
from matplotlib.... |
49c85cf7dc307e01abba3ce69ee8712cc2090eaadcf5eb2fe83da90df27ed158 | Python | 1,341 | 39 | """These models have been pre-trained using self-supervised learning. The models can also be used without pre-
training and overwritten for your own research.
Here's an example for using these as pretrained models.
.. code-block ::
from pl_bolts.models.self_supervised import CPC_v2
images = get_imagenet_bat... |
5add5050e86046e3dec2943f51849d3fd306472ebd8dd9a79202d5d296702c3b | Python | 1,341 | 32 | from unittest import mock
from carbonserver.api.services.matomo_tracker import MatomoTracker
def test_tracker_is_disabled_without_url_and_site_id():
assert not MatomoTracker().enabled
assert not MatomoTracker(url="https://matomo.example.com").enabled
assert not MatomoTracker(site_id="3").enabled
def te... |
6e0fce4bb828770cdf4352be74dd4994e77983ea17a780d6b2ee9baf9833f758 | Python | 1,341 | 35 | """Test functions for specparam.metrics.error."""
from specparam.metrics.error import *
###################################################################################################
###################################################################################################
def test_compute_mean_abs_err... |
755bb972e6b0b6f090d08468eb7bec46c985416f5b48387465fbefaa9ff51526 | Python | 1,341 | 49 | import torch
import torch.nn as nn
import torch.nn.functional as F
class no_z_InstNorm(nn.Module):
def __init__(self, n_channels, **kwargs):
super().__init__()
self.norm = nn.InstanceNorm2d(n_channels, **kwargs)
def forward(self, xb):
nb, nc, nz, nx, ny = xb.shape
... |
adbaf6559de104cc8822b8e0e9c7cf93620e57af5a3d1ed9f5362e1460e3456c | Python | 1,341 | 38 | import numpy as np
def test_distance_calculations():
from pyrosm.distance import Unit, haversine
# Example line from Null Island to 10'10 --> should be ~1569 km
lon1, lat1 = np.array(0.0, dtype=np.float64), np.array(0.0, dtype=np.float64)
lon2, lat2 = np.array(10.0, dtype=np.float64), np.array(10.0, ... |
4babf80720337205679e8fbee34a7abba29600f14aeb93b228ffd467042c1fea | Python | 1,342 | 44 | """Checks kit: the torch.compile composition leg (heavy tier).
The mount decider (memo D1): Recorder refuses compiled models behind a
deliberate guard while the public optimizer/tensor hooks fire normally, so
the step-check family must run under torch.compile. This is the small CPU
leg; the AT-SCALE compiled leg stays... |
c497eece0b26077333c60b1510ffc0f2527385ce0c430dabe217e6a90a5e6995 | Python | 1,342 | 45 | from sys import argv
from msp import MSP
msp = MSP()
msp.file = __file__
msp.seed = int(argv[1])
msp.architecture["sparse_spec"] = dict(type="SpatiallySparseAcrossChannels")
msp.architecture["motif_model_spec"]["motif_width"] = 13
msp.architecture["motif_model_spec"]["motif_feature_extractor_spec"] = dict(
type="... |
485fff5cd43665536715710ef2fbf2d6ebf836a2299bb847b8ce38b88bdd50da | Python | 1,343 | 46 | from collections import OrderedDict
from xml.dom.minidom import parseString
import numpy as np
import tifffile
def load_ometif(path):
"""Load .ome.tif files
Please see :func:`impose.formats.load` for more information.
"""
with tifffile.TiffFile(path) as tif:
if not tif.is_ome:
ra... |
da5e2a9f4c124b9d2b89d7fa24288c03768366b4a5e2c19959877edb8e316e4b | Python | 1,343 | 40 | from mirp._images.generic_image import GenericImage
from mirp._masks.base_mask import BaseMask
class Feature(object):
def __init__(self, **kwargs):
self.name: None | str = None
self.abbr_name: None | str = None
self.ibsi_id: None | str = None
self.value: None | float = None
... |
fae5fd8c5574819dc7b172bba149f364e870deba451bccc20969b64a79a7e7db | Python | 1,343 | 31 | import os
import tempfile
from zipfile import ZipFile
from xyz2swcapi import NeuroMorphoAPI
def test_convert():
api = NeuroMorphoAPI()
api.convert(open('../../input/to_convert/neuron_Neurolucida_DAT.dat', 'rb'))
assert api.foldername is not None, "Folder name should be set after conversion."
def test_che... |
01bc9f83bfb64b31ce7bd316a3ee86ca1c80183e1785360b1d9172a56e33f250 | Python | 1,344 | 37 | import os
import re
import numpy as np
import matplotlib.pyplot as plt
import sys
sys.path.insert(1,'/home/mila/l/lindongy/deeprl-timecells')
from analysis import utils_linclab_plot
utils_linclab_plot.linclab_plt_defaults(font="Arial", fontdir="analysis/fonts")
# ====== extract behavioural data and plot performance =... |
e1293f252aba7d3a2f0f40121fc63009674bb57ea7e4478ce073a4999179cb7d | Python | 1,344 | 42 | from pytorch_lightning.utilities import rank_zero_only
@rank_zero_only
def log_hyperparameters(object_dict: dict) -> None:
"""Controls which config parts are saved by lightning loggers.
Additionally saves:
- Number of model parameters
"""
hparams = {}
cfg = object_dict["cfg"]
model = obj... |
12fe8ffd18ab636ce7973c2aa633db0989bdc537f0f76455c7277dc6c09c6c63 | Python | 1,346 | 47 | from __future__ import annotations
from enum import Enum, auto
from pytest_celery import CeleryTestWorker
from celery.app.control import Control
class WorkerKill:
"""Kills a worker in different ways."""
class Method(Enum):
DOCKER_KILL = auto()
CONTROL_SHUTDOWN = auto()
SIGTERM = au... |
17912001f19d654d8b94e65a6efa1969ceb9ac1e9b9fe9fc485f26c0e498b9f9 | Python | 1,346 | 46 | from ethoscope.hardware.interfaces.optomotor import OptoMotor
from ethoscope.stimulators.sleep_depriver_stimulators import MiddleCrossingStimulator
class OptoMidlineCrossStimulator(MiddleCrossingStimulator):
"""
Shine LED light when animals cross the midline.
Uses MODULE 3 LED even-channel mapping (same a... |
2d38fb139badfae76756a47920aa6036ccfd983a8c0afcd0dcde3980ee42669f | Python | 1,346 | 44 | import os
import numpy as np
import random
import nibabel as nib
import torch
from torch.utils.data import Dataset
class DatasetRDO(Dataset):
def __init__(self, paths, mode='training'):
self.mode = mode
self.paths = paths
lenghts = [len(k) for k in paths.values()]
assert all(x == ... |
872274bd31ae50c2c23e13e68016d036b6cce3dad822a09b20d8ce5c9bd1561d | Python | 1,346 | 35 | import numpy as np
import copy
import tns
def tmd_scale(barcode, thickness):
# only the two first points of each bar are modified
# because they correspond to spatial dimensions
scaling_factor = np.ones(len(barcode[0]), dtype=np.float)
scaling_factor[:2] = thickness
return np.multiply(barcode, scal... |
c8181de378f37d15066e3a4c3e911fbeb6bb818ce4de75d49422b36fb0422c17 | Python | 1,346 | 42 | # -*- coding: utf-8 -*-
import os
import setuptools
def read_file(filename):
return open(os.path.join(os.path.dirname(__file__), filename)).read()
setuptools.setup(
name = 'bleualign',
version = '0.1.1',
description = 'An MT-based sentence alignment tool',
long_description = read_file('README.md'),
author = 'Ri... |
ffac61d5075ef894d6bfa22a773551ba48e33dcc99d19bd689b697a343889f41 | Python | 1,346 | 57 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on April 2022
@author: Thomas Bonald <bonald@enst.fr>
"""
from abc import ABC
import numpy as np
from sknetwork.base import Algorithm
class BaseRegressor(Algorithm, ABC):
r"""Base class for regression algorithms.
Attributes
----------
value... |
5c76522cd9f24c0193f3c418a070ddff38293068d0869fd8474757c36d1b7053 | Python | 1,347 | 33 | # Written by Seonwoo Min, Seoul National University (mswzeus@gmail.com)
# Some parts of the code were referenced from or inspired by below
# - Tristan Bepler's code (https://github.com/tbepler/protein-sequence-embedding-iclr2019)
# PLUS
""" Fluorescence FASTA file loading functions """
import numpy as np
import torc... |
8da0c48764cb02bce6cab2391f2941b7c3fdd10fa6a139d00f9a2ba240cb20e4 | Python | 1,347 | 38 | """
This file lists the size of every structure in the structures file.
sectionSizes = {'HeaderV1': 1678, 'HeaderV2': 76, 'SectionMap': 216,
'ProtocolSection': 208, 'ADCSection': 82, 'DACSection': 132,
'EpochPerDACSection': 30, 'EpochSection': 4, 'TagSection': 64,
'St... |
e902ed80303de4958cb43bf121b0eb688f83a09b80d6b658378e175b913313ae | Python | 1,347 | 66 | """Array related utilities."""
import numpy as np
###################################################################################################
###################################################################################################
def normalize(data):
"""Normalize an array of numerical data (t... |
8e7b269e06d3d988f253c0c4a886bbc953d9e9c726808ac32e896c512ff51982 | Python | 1,349 | 43 | # Copyright 2024 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agre... |
9d58f4ebbef73710887330ed809f44519ec2d747370619ad4ead0ae7407956a5 | Python | 1,349 | 51 | import matplotlib
import numpy as np
import pytest
from pyriemann.utils.viz import (
plot_embedding,
plot_cospectra,
plot_waveforms
)
matplotlib.use("Agg")
pytestmark = pytest.mark.numpy_only
def test_embedding(get_mats):
n_matrices, n_channels = 5, 3
X = get_mats(n_matrices, n_channels, "spd"... |
3da350b2ce30e62075042bd7470fc46d6442c94b9a161b828a6d79c8f6c7578b | Python | 1,350 | 51 | # from .utils import get_img_from_fig, checkType
import scanpy
from anndata import AnnData
def non_spatial_plot(
adata: AnnData,
use_label: str = "leiden",
) -> None:
"""\
A wrap function to plot all the non-spatial plot from scanpy.
This function will produce 3 plots: PAGA graph, cluster plot in... |
413cb856547e536063b57f9e37f69adb55868094107b307a6091a23ed56dbef2 | Python | 1,350 | 48 | """
EDeN filetypes
"""
from galaxy.datatypes import data
from galaxy.datatypes.tabular import Tabular
class Gspan(Tabular):
"""Class describing an gSpan file"""
file_ext = "gspan"
def set_peek(self, dataset, is_multi_byte=False):
if not dataset.dataset.purged:
dataset.peek = "gS... |
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