sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
88ad40d97ee8963dbfc83c2e89a09fc5415d9013e6eb0e2d448becdb39936dab | Python | 1,243 | 45 | import json
import torch
import pandas as pd
from monai.data import Dataset, DataLoader
from monai.utils import set_determinism
from lightning import Trainer
from classifier import NPhaseClassifier
from preprocess import get_preprocess_infer
def main():
set_determinism(42)
with open("datalist.json", "r") a... |
1aba3f29449a69bc82db9e47b58f258c4e3d35db3fa10c25cab3983810cdec6e | Python | 1,244 | 28 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
try:
from .model import get_bibtex, get_layers, get_model, get_model_list
except ImportError:
import importlib.util
from pathlib import Path
_MODEL_PATH = Path(__file__).resolv... |
39292914124ddcc2be4a008d5784429d772915885dd7eca195ae3680e203f734 | Python | 1,244 | 70 | #-*- coding:utf-8 -*-
#Import urlparse in Python 2 or urllib.parse in Python 3
try:
import urlparse
except ImportError:
import urllib.parse as urlparse
from docutils import nodes
from docutils.parsers import rst
class youtube(nodes.General, nodes.Element):
pass
def is_url(s):
if s.startswith(... |
4ad719c06d84f1e5f96121a03ae61b1a252f3fce986a6a4e1c0f308843c765be | Python | 1,244 | 43 | '''
dynamic import model
'''
import importlib
def import_model(model_path):
# 获取模块路径和类名
module_path, class_name = model_path.rsplit('.', maxsplit=1)
# 1 利用字符串导入模块
module = importlib.import_module(module_path)
# 2 利用反射获取类名
cls = getattr(module, class_name)
# 3 生成类的对象
# obj = cls()
r... |
562886a6a8ffd0a27ba589be31511bcf13e0a2322d21a794330d87b27a65f652 | Python | 1,244 | 28 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
try:
from .model import get_bibtex, get_layers, get_model, get_model_list
except ImportError:
import importlib.util
from pathlib import Path
_MODEL_PATH = Path(__file__).resolv... |
328b32cb81473c2d8a08b5a0f63c10b36687bb3817ec7debc0cb0e7c894a387a | Python | 1,245 | 40 | import numpy as np
def remove_duplicate_voxels_from_paths(paths):
"""Remove duplicate consecutive voxels from the paths
Duplicate consecutive voxels are identified and removed - the list of
voxels is then shifted to fill in the gaps left by the duplicates, so the
format is consistent with the origina... |
66cfebcec1449b2c47fc6490f49fa88b77597960322ad2ca7dd715d503cc40dd | Python | 1,245 | 42 | # -*- coding: utf-8 -*-
"""TODO"""
import numpy as np
import core.core_global as core
from core.core_definitions import simulation_timestep
from core.monitor import Monitor
class WeightMatrixMonitor(Monitor):
"""TODO"""
def __init__(self, source, filename, interval=1.0):
"""TODO"""
super().... |
b0365660ee9b2ed7cae0421634cecc7792385c0a42df264eff5cbbe1884d8e6f | Python | 1,245 | 46 | """
Download the demo data
"""
import os
import shutil
import zipfile
from tensorflow.keras.utils import get_file
PROJECT_DIR = "demos/unpaired_us_prostate_cv"
os.chdir(PROJECT_DIR)
DATA_PATH = "dataset"
DATA_REPO = "dataset_trus3d-master"
ZIP_PATH = "master.zip"
ORIGIN = "https://github.com/ucl-candi/dataset_trus3d... |
c79cf28d737c886ebf3c34d3b62ed8c1ed663437a31dabca72264a7b0ea51e73 | Python | 1,246 | 47 | #
import sys
import os
import math
#from keras.utils import FeatureSpace
import tensorflow as tf
import pandas as pd
import keras
from keras import layers
from tensorflow import data as tf_data
import random
import numpy as np
from sklearn.preprocessing import StandardScaler
from sklearn.metrics import classification_r... |
5b5cc3e746beeb182bfabf561a865f389005be2bc05548124f32290d70169b5c | Python | 1,247 | 42 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sun Apr 28 17:45:23 2024
@author: brainmappers
"""
def roi(subjects_dir,subject,hemi,surface,mesh,number):
import os
import numpy as np
import math
if mesh=='164k':
m=163842
#read csv file and save as lists in... |
af929345be03a1f4a7d39f22449c129e579497ca7afa7725068eaaaa095d64f8 | Python | 1,247 | 37 | # -*- coding: utf-8 -*-
"""
Percent signal change conversion
This scripts converts timeseries data into percent signal change.
"""
# external inputs
import nibabel as nb
# local inputs
from fmri_tools.io.get_filename import get_filename
from fmri_tools.preprocessing.timeseries import ScaleTimeseries
# input
file_i... |
d1036ccec6b42e5b80067191f57afdb168c99ef5aa33db5056895de011e05d01 | Python | 1,247 | 29 | # Copyright (c) 2026 Rohit Jena. All rights reserved.
#
# This file is part of FireANTs, distributed under the terms of
# the FireANTs License version 1.0. A copy of the license can be found
# in the LICENSE file at the root of this repository.
#
# IMPORTANT: This code is part of FireANTs and its use, reproduction, or... |
d7bcbcf1ae7acaed474db806a642ec7d585f3f819c6751bb3f8374f8f1c812a4 | Python | 1,247 | 42 | import numpy as np
from nems import Model
from nems.layers.base import Parameter, Phi, Layer
from nems.distributions import Normal
from nems.tools.json import nems_to_json, nems_from_json
def test_save_load():
shape1 = (2,3)
shape2 = (1,)
d1 = Normal(
mean=np.full(shape=shape1, fill_value=0.2),
... |
ee407adbc0a153f57440d359046806f810c66b1085dba2b9e9258a40951e72d5 | Python | 1,247 | 35 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import os
import tempfile
from scilpy import SCILPY_HOME
from scilpy.io.fetcher import fetch_data, get_testing_files_dict
# If they already exist, this only takes 5 seconds (check md5sum)
fetch_data(get_testing_files_dict(), keys=['processing.zip'])
tmp_dir = tempfile.T... |
f513c8c9526da491676e510081cb52061e54cbc64818b268d991aba4bd61f289 | Python | 1,247 | 41 | import functools
import os
from rich.console import Console
CITATION_LINK = "https://github.com/BrainLesion/preprocessing#citation"
def citation_reminder(func):
"""
Decorator to remind users to cite brainles-preprocessing.
The reminder is shown when the environment variable
`BRAINLES_PREPROCESSING_... |
4c1bc2172da554639da6ff28ea0555332ea34b7edca8a6754118e0547d8bc470 | Python | 1,248 | 40 | from typing import TypeVar
from torch import nn
T = TypeVar('T', bound='Module')
class BatchEvalModule(nn.Module):
def __init__(self, *args, **kwargs):
super(BatchEvalModule, self).__init__(*args, **kwargs)
self.batch_evaluation = False
def batch_eval(self):
def set_batch_eval(mod... |
7e590a2730047ad528643070c13729d9c2e5ccee91c492cdb9e24cb053e96ce0 | Python | 1,248 | 41 | # -*- coding: utf-8 -*-
#
# test_spikes.py
import unittest
import arbor as A
from arbor import units as U
from .. import fixtures
"""
all tests for the simulator wrapper
"""
class TestSpikes(unittest.TestCase):
# test that all spikes are sorted by time then by gid
@fixtures.single_context()
def test_spi... |
de62b0c274a352f63533eccba2dd06239b7ceafb2d9feaf015d44904f4c09e24 | Python | 1,248 | 33 | import argparse
import train
import src.config
def loso_cv(config, dataset_path=None):
'''Starts a leave-one-out cross validation'''
config.FOLDS = 0 # Enable loo split
# In case sequence length and frame shift lead to cutting of
# last part of the signal, shall the last part stay cutted or not
#... |
37a98b95d14dc0ef47a76f751d397be137d72191b3a3cd960cd530195d4419ca | Python | 1,249 | 41 | import numpy as np
import pandas as pd
from sklearn.ensemble import RandomForestClassifier
from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score, matthews_corrcoef, auc, roc_curve
from sklearn.metrics import classification_report
from sklearn.metrics import confusion_matrix
from sklearn.mo... |
3bd835ec3b800868e38893cfa6157744d79feefb6eab76e29641cc5fbbe4836b | Python | 1,249 | 42 | import sys
import numpy as np
import matplotlib.pyplot as plt
def read_ecg_readings (input_file):
data = np.genfromtxt(input_file)
nlin, ncol = np.shape(data)
timesteps = data[:,0]
currents = data[:,1:]
num_leads = ncol-1
return timesteps, currents, num_leads
def plot_ecg_readings (t, currents, nleads):
for... |
4144de60d92689bc45bb4f009591b30273077c4a01a7692df68eb9934c267e65 | Python | 1,249 | 64 | r"""Testing package.
This package provides helper methods and decorators to ease testing.
"""
from .decorators import (
is_full_test,
onlyFullTest,
is_distributed_test,
onlyDistributedTest,
onlyLinux,
noWindows,
noMac,
minPython,
onlyCUDA,
onlyXPU,
onlyOnline,
onlyGraph... |
4b2066926b0a97f6a565c26e88c3d934302f2d1bc1642d568c8e4fd18760efc4 | Python | 1,249 | 34 | import os
import json
import torch
os.environ['CUDA_VISIBLE_DEVICE'] = '5'
import pandas as pd
import numpy as np
from tqdm import tqdm
from pathlib import Path
from transformers import *
pretrained_weights = 't5-small'
tokenizer = T5Tokenizer.from_pretrained(pretrained_weights)
model = T5EncoderModel.from_pretrained(... |
09972bcbe0045f00608789dace00b16d8f9cc3a01723f157b53bc82e44acb46a | Python | 1,250 | 57 | #!/usr/bin/env python
"""
Application to convert LAV file to AXT file. Reads a LAV file from standard
input and writes a AXT file to standard out; some statistics are written
to standard error.
usage: lav_to_axt [--silent] [path=replacement] < lav_file > axt_file
"""
__author__ = "Bob Harris (rsharris@bx.psu.edu)"
... |
2f41efba4b6e98f230e00a69eb2b12be883b995f602f69255e38461f88162b2e | Python | 1,250 | 48 | import pytest
from napari_dmc_brainmap.visualization.vis_utils.visualization_utils import (
deduplicate_preserve_order,
get_descendants,
normalize_seaborn_style,
)
@pytest.mark.parametrize(
("style", "expected"),
[
("white", "white"),
("dark", "dark"),
("whitegrid", "white... |
38de4872aee93ad850f1db8ef41e4f56a50b9690489dcfa3356e0e6098fae3da | Python | 1,250 | 27 | # Copyright (C) 2020-2022 Intel Corporation
#
# SPDX-License-Identifier: MIT
from django.urls import include, path
from rest_framework import routers
from . import views
router = routers.DefaultRouter(trailing_slash=False)
# https://github.com/encode/django-rest-framework/issues/6645
# I want to "call" my functions.... |
865cabf5c4241b9630d41cb3db5b5cc96b44d7b6f469ffe76fe13ce036392231 | Python | 1,250 | 41 | import pytest
from impedancefitter.utils import draw_scheme
# those were used for testing the code
# they do not work with LMFIT!!!
# they were just there to check that everything is alright
working = [
"RC + R + parallel(R, C) + parallel(R, C)",
"parallel(R + R, C + C)",
"parallel(R, C)",
"parallel(... |
4b61aabe54755df19ce3afedcf6a484d1cf7f88cd3d626974bfdf59c37a2cd6e | Python | 1,251 | 45 | import sys
import yaml
import os
import h5py
import pandas as pd
from scipy.stats import scoreatpercentile as sap
import numpy as np
from glob import glob
pathpath = 'PATHS/filepaths_IBL.yml'
with open(pathpath, 'r') as myfile: pathdict = yaml.safe_load(myfile)
sys.path.append(pathdict['code']['workspace'])
from pfc... |
e0afd7a0ea9084c66883a90134b08584638cfcd0250285725d8efbac3e245f47 | Python | 1,251 | 35 | """Utility and helper functions.
Modules
-------
- :py:mod:`~osl_dynamics.utils.array_ops` — Array operations (covariance ↔
correlation conversions, matrix decompositions, etc.).
- :py:mod:`~osl_dynamics.utils.filenames` — :py:class:`OSLFilenames` for
managing pipeline file paths.
- :py:mod:`~osl_dynamics.utils.lo... |
61c057c07968f8cdf7aad68216a103d4d16e25d21995d4c6f7b240706abfccfc | Python | 1,252 | 46 | import logging
import anndata
import numpy as np
import scipy.sparse
import unittest
import batchglm.api as glm
import diffxpy.api as de
glm.setup_logging(verbosity="WARNING", stream="STDOUT")
logger = logging.getLogger(__name__)
class TestAccuracyGlmNb(
unittest.TestCase
):
"""
Test whether optimizers ... |
fedd05dfc2d34e09a0e4b8ad9ef96e97ee197920d378437d4d98965a88636dbe | Python | 1,252 | 44 | import numpy as np
import pandas as pd
from sklearn.ensemble import RandomForestClassifier
from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score, matthews_corrcoef, auc, roc_curve
from sklearn.metrics import classification_report
from sklearn.metrics import confusion_matrix
from sklearn.mo... |
55e9b5a3f44e2203cd904eae34cd826e7ae0b23503743d7bcee21256e0b15234 | Python | 1,253 | 48 | """
Helper functions for data visualization.
"""
import math
import pandas as pd
import numpy as np
import plotnine as p9
def shade_plot(X: np.array, Y: np.array, sigma: np.array, x_label: str, y_label: str,
width: int = 5, height: int = 3):
"""_summary_
Parameters
----------
X : np.a... |
89dd62062ccca73ad7a9474fb6a0114176f7bb3737e562c2ff3551ba5bc2ca0c | Python | 1,253 | 40 | # -*- coding: utf-8 -*-
"""
Function for extracting rotational component from an affine matrix and writing out in affine form
"""
import numpy as np
from numpy.linalg import svd
import argparse
# pass arguments
parser=argparse.ArgumentParser(
description=''' Function for extracting rotational component from an a... |
b36b505b752db9428b294a4e83d93bf07713cdcd764ef51f89cb54f4a9532e24 | Python | 1,254 | 44 | # -----------------------------------------------------------------------------
# Copyright © 2009- The Spyder Development Team
#
# Licensed under the terms of the MIT License
# (see LICENSE.txt for details)
# -----------------------------------------------------------------------------
"""Provides QtWebEngineCore cla... |
50972550a2de82e22255ea7f6e6d1eb71f032fae2dbaddf48c858c7dc029303a | Python | 1,255 | 35 | """
The task of this file is to split the provided sequences file into training, validation and test data.
"""
import numpy as np
if __name__ == '__main__':
filename = "ngs_sequences.txt"
split = [0.7, 0.15, 0.15]
with open(filename, "r") as file:
sequences = file.readlines()
sequences = [se... |
61336932d091fdaf40968b664f5bcd5caa751a5169d34c5a8b46190b17b37340 | Python | 1,255 | 46 | import subprocess
import tempfile
from pathlib import Path
from re import subn
from typing import Optional
from dti.utils import create_mask
from gmri2fem.utils import with_suffix
def dtifit(
dti_eddy_corrected: Path,
bvals: Path,
output: Path,
tmppath: Optional[Path] = None,
):
if tmppath is Non... |
4e4bac04a503ec46ba451050fd501adfa06d7db325d2b905eb7a6ee5853b29e8 | Python | 1,257 | 33 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import os
import tempfile
from scilpy import SCILPY_HOME
from scilpy.io.fetcher import fetch_data, get_testing_files_dict
# If they already exist, this only takes 5 seconds (check md5sum)
fetch_data(get_testing_files_dict(), keys=['connectivity.zip'])
tmp_dir = tempfile... |
2083be876d94d9aa94cf7d07df15cd2c9b26abff54c6acf54267940b6f2d3f26 | Python | 1,258 | 64 | import re
# user_to_post.csv»ñÈ¡tweetÁбí
# node.json»ñÈ¡postÍÆÎÄ
# postÊǸö×Öµä
# maybe item = item.replace('\n',' ')
def count_characters(text):
text = text.replace('\n',' ')
return len(text)
def count_hashtags(text):
hashtags = re.findall(r'#\w', text)
return len(hashtags)
def count_words(text):
... |
2edb7e19961f1a4210c07cad2803cfdada467fe8ce517eca82df35712e42ced1 | Python | 1,258 | 41 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
from typing import Any
from django.apps.registry import Apps
from django.db import migrations
from django.db.backends.base.schema import BaseDatabaseSchemaEditor
from django.db.models import Q
_RETIRED_EVENT_KEY = "delete:organization"
def _remov... |
fa451f7c378188b1060036b329a45264217e9364d1712faa709afdb863fb9366 | Python | 1,258 | 36 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import os
import tempfile
from scilpy import SCILPY_HOME
from scilpy.io.fetcher import fetch_data, get_testing_files_dict
# If they already exist, this only takes 5 seconds (check md5sum)
fetch_data(get_testing_files_dict(), keys=['tracking.zip'])
tmp_dir = tempfile.Tem... |
5b1df47cd88ec9ff92c1710031597b76dba8e3c0bd4bc20016335057b8a2237a | Python | 1,259 | 43 | import pytest
from scilpy.tests.arrays import fodf_3x3_order8_descoteaux07, \
fodf_3x3_order8_descoteaux07_filtered_unified
@pytest.mark.ml
def test_get_data_order_6_28coeffs():
""" fODF should keep the same number of coeffs."""
# Imported here so as not to trigger an import error with pytorch
from ... |
d18333c3f2623997bb07f8f490141c9d06666b02e8549109a09413cef53f465a | Python | 1,259 | 37 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import os
import tempfile
import nibabel as nib
from scilpy import SCILPY_HOME
from scilpy.io.fetcher import fetch_data, get_testing_files_dict
# If they already exist, this only takes 5 seconds (check md5sum)
fetch_data(get_testing_files_dict(), keys=['tractograms.zip... |
08912c1af66f94b39668a53a858a37beabdf3948077897f53f57ed999e6d9f2a | Python | 1,260 | 53 | """
Load TPC wedges
"""
from itertools import product
from pathlib import Path
import numpy as np
import torch
from .utils import get_data_root
def __to_list(arg, default):
if arg is None:
return default
if isinstance(arg, int):
return [arg]
elif isinstance(arg, [list, tuple]):
... |
258c8d4680145c4d5734f97f05da99ff93379251ad906187d7ecdda95b47107b | Python | 1,260 | 43 | import numpy as np
from scipy.ndimage import binary_fill_holes
# Hello! crop_to_nonzero is the function you are looking for. Ignore the rest.
from acvl_utils.cropping_and_padding.bounding_boxes import get_bbox_from_mask, bounding_box_to_slice
def create_nonzero_mask(data):
"""
:param data:
:return: the ... |
d0ee9e4fdf3fb738ae3bd4dec8a17728903a1af58eb17dd340238b387632ec72 | Python | 1,260 | 51 | """
This script is used to compare the beta values of two orthogonalized regressions
"""
import sys
import os
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
import numpy as np
import pandas as pd
from scipy import stats
def compare_slopes_odr(file_1, file_2):
# Read beta and s... |
660ea5666b1815a8511ce6ee806d5200ddbf94e8c22f26005c2cf8056039b46d | Python | 1,261 | 55 | #!/usr/bin/env python3
import arbor as A
from arbor import units as U
from util import plot_spikes
# global parameters
# cell count
N = 5
# total runtime [ms]
T = 1000
# numerical time step [ms]
dt = 0.1
class unconnected(A.recipe):
def __init__(self, N) -> None:
super().__init__()
self.N = N
... |
94d6aedbd6d637f4bd76989758cdc18bb78d9c8c0f3adc62baea28cfcc6345a7 | Python | 1,261 | 54 | import torch
from inspect import isfunction
import contextlib
import tempfile
import time
from typing import Optional
import shutil
import logging
# from .ss_utils import *
def exists(val):
return val is not None
def default(val, d):
if exists(val):
return val
return d() if isfunction(d) else d
... |
fde3f36db89bf8cbc36967047bd1c2bcbc7622ce3865d7dc85e9a71621271821 | Python | 1,261 | 28 | import numpy as np
from ccf_streamlines.angle import vector_to_3d_affine_matrix, find_closest_streamline, determine_angle_between_streamline_and_plane
def slice_angle_tilt(pin_df, specimen_id, closest_surface_voxel_file, surface_paths_file):
""" Estimate angle of slice from CCF pinning information
Parameters... |
812ddeaa469d1c1ed60fd3a0b13e3495d284b3421e83531f59b2abff2f0dca91 | Python | 1,262 | 45 |
import numpy as np
import cv2
def _clahe(image):
#-----Reading the image-----------------------------------------------------
if not isinstance(image, np.ndarray):
image = cv2.imread(image, 1)
#-----Converting image to LAB Color model-----------------------------------
lab = cv2.cvtColor(im... |
d1ff7c44597731f3f79e08d908567ab8ebe9545912ebde9e8ca3861df0e3be0d | Python | 1,263 | 37 | # by Shaoxuan Yuan at 2024/04/22
from PIL import Image, ImageDraw
import json
def fill_polygon(json_file_path, output_file_path):
# 读取JSON文件中的标注信息
with open(json_file_path, 'r') as json_file:
json_data = json.load(json_file)
# 获取图片的宽度和高度
width = json_data['imageWidth']
height =... |
e3bdb0ab9b42610b16ce93deaf407d230a2c560848b53acb94dd81ebdda63c99 | Python | 1,263 | 33 | import torch
from batchgeneratorsv2.transforms.base.basic_transform import ImageOnlyTransform
from batchgeneratorsv2.helpers.scalar_type import RandomScalar
class MissingModalityTransform_perImage_full(ImageOnlyTransform):
def __init__(self, probability: RandomScalar = 0.2, num_channels: int = 4):
"""
... |
6c974dc57a349776a73d53f33f344a78d16ce521cc82af1da545cf2ee0d206d1 | Python | 1,265 | 40 | from unittest.mock import MagicMock
import numpy as np
import pytest
from PIL import Image
from eir.data_load.data_preparation_modules import prepare_image
from eir.setup.input_setup_modules.setup_image import (
ImageNormalizationStats,
get_image_transforms,
)
@pytest.mark.parametrize("resize_approach", ["r... |
ec48c97101703a8429f548ae7da4e31272aa141cc632e8643d81932531c1f331 | Python | 1,265 | 37 | import os
import scanpy as sc
import pandas as pd
import anndata as ad
import numpy as np
os.chdir("/data/wuqinhua/phase/covid19/datasets")
adata = ad.read_h5ad('./pre_data/6_Liu_2021/sce.h5ad')
adata = ad.AnnData(X=adata.raw.X, var=adata.raw.var, obs=adata.obs)
submatrix_block = adata.X[:15, :25].toarray()
submatri... |
f4543d0e00b843f39db8034831e289b1def17d20a9832838236744860e51bae5 | Python | 1,265 | 37 | # Copyright (C) 2021-2022 Intel Corporation
# Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
import shutil
from datumaro.components.dataset import Dataset
from cvat.apps.dataset_manager.bindings import (
GetCVATDataExtractor,
detect_dataset,
import_dm_annotations,
)
from cvat.apps.dat... |
41b54d099736d378e6f10117f4a18ff8d71e25d853e99266d16f08af4658b655 | Python | 1,266 | 43 | # emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
# vi: set ft=python sts=4 ts=4 sw=4 et:
### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##
#
# See COPYING file distributed along with the PyMVPA package for the
# copyright and license terms.
#
### ### ### ### ###... |
9470644370d21486d0274dc7ebf2afbd0c84d1a77a6c30c265d3667a49b917c1 | Python | 1,266 | 36 | # Copyright (c) DP Technology.
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""isort:skip_file"""
from .unicore_dataset import UnicoreDataset
from .base_wrapper_dataset import BaseWrapp... |
7adc2cb46f44b9cb034633ff633ad7f4069aeb9728135cf86517fe9433cc8a3a | Python | 1,267 | 36 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import os
import tempfile
from scilpy import SCILPY_HOME
from scilpy.io.fetcher import fetch_data, get_testing_files_dict
# If they already exist, this only takes 5 seconds (check md5sum)
fetch_data(get_testing_files_dict(), keys=['processing.zip'])
tmp_dir = tempfile.T... |
cc22495390f0e0163820ab5fbb5f1aeeea88de0c3e7a9ce61bd4afbabdaa72ec | Python | 1,267 | 34 | import os
import glob
from .session import BIDSSession
class BIDSSubject:
def __init__(self, subject_id, bids_dir):
self.subject_id = subject_id
self.bids_dir = os.path.abspath(bids_dir)
self.subject_dir = os.path.join(self.bids_dir, f"sub-{subject_id}")
if not os.path.exists(self.... |
4757e885dd7efa7ab2de88060216e5697403884a665d2f4df0f9833943caf1ce | Python | 1,268 | 36 | import pytest
from impedancefitter.utils import draw_scheme
# those were used for testing the code
# they do not work with LMFIT!!!
# they were just there to check that everything is alright
working = ["RC + R + parallel(R, C) + parallel(R, C)",
"parallel(R + R, C + C)",
"parallel(R, C)",
... |
6acaecbe795abb425801fda31d1b626eaeb87c5812b0cc6d782afe13dfc62fd2 | Python | 1,268 | 35 | from brainscore_vision.model_helpers.activations.pytorch import PytorchWrapper
from brainscore_vision.model_helpers.activations.pytorch import load_preprocess_images
import ssl
import functools
import antialiased_cnns
from brainscore_vision.model_helpers.check_submission import check_models
ssl._create_default_https_c... |
ca8fa71ceba7b878e2256080a8f654a791be0d43da5b9d60ffe9e5814b2ed69b | Python | 1,268 | 43 | # Generated by Django 3.2.18 on 2023-06-08 19:15
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
("engine", "0068_auto_20230418_0901"),
]
operations = [
migrations.AlterField(
model_name="labeledimage",
name="sourc... |
d9cacfac0f74281f5dc02bffbaf77c2dcfe3762b596ac8636df96f23365ead3f | Python | 1,268 | 39 | import numpy as np
from argparse import ArgumentParser
import json
from tqdm import tqdm
parser = ArgumentParser()
parser.add_argument('--dataset', type=str)
args = parser.parse_args()
dataset_name = args.dataset
assert dataset_name in ['Twibot-22', 'Twibot-20', 'cresci-2015']
n_hidden = 128
if __name__ == '__main... |
fad1a57d8e8773da82a9ec323835a97195834b352f58129a638422a64ddcbdf7 | Python | 1,268 | 29 | import os
import subprocess
import shutil
import nibabel as nib
import numpy as np
import pandas as pd
from nipype.interfaces.base import BaseInterface, BaseInterfaceInputSpec, TraitedSpec, File, Directory, traits, CommandLineInputSpec, File, TraitedSpec, CommandLine, Directory
from nipype.interfaces.utility import Ide... |
aa6b79fd570b84d608dc29249fc23b09812c01012ba5ef1940cd78645b1a0f4f | Python | 1,269 | 37 | import numpy as np
def harm_probas(agesA, agesB, bins):
"""
Computes a sampling probability given ages from two datasets and consecutive age ranges.
----
PARAMETERS:
agesA: list of ages in the first dataset
agesB: list of ages in the second dataset
bins: list of ages correspondi... |
195c09f0bf022377feefb69ab61df34089771be43e7f566155a9d7b7c3e8a93c | Python | 1,270 | 35 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
from pathlib import Path
from typing import Any
from django.dispatch import receiver
from rq.job import Job as RQJob
from cvat.apps.dataset_manager.cron import InstanceTmpDirectoriesCleaner, TmpDirectoryCleaner
from cvat.apps.engine import backgrou... |
47e578cce00f3959a53c890d68c676f6e490a3a0fb505495033bda3b4e291b1e | Python | 1,270 | 33 | """
Predicted concentration vs estimated concentrations
for the Look Locker and Mixed sequences with a given SNR
"""
import matplotlib.pyplot as plt
import click
from plot_noise_look_locker import plot_estimated_versus_actual as plot_look_locker
from plot_noise_mixed import plot_estimated_versus_actual as plot_mixed
... |
7c21cd088e8c4a369deb21ed15c2343009dc50f6111e8c4c092d50dc5588fdb6 | Python | 1,270 | 20 | from testsetclass import TestsetClass
class ALKBDE10(TestsetClass):
def __init__(self):
self.weak = 1.0
self.molecules = ['cao', 'be', 'lio', 'mg', 'na', 'lif', 'ca', 'nao', 's', 'f', 'o', 'h', 'mgo', 'mgs', 'hf', 'kf', 'beo', 'bef', 'li', 'k']
self.exp_values = {'0': 138.7, '1': 106.6, '2... |
0057b04298cbcbb918fab5ccdb3a055880cf8f45c10cd934ce7593520cac7c95 | Python | 1,271 | 47 | # -*- coding: utf-8 -*-
from time import time
def get_duration(start_time, decimal=2):
""" Convert a duration in seconds """
return round(time() - start_time, decimal)
def is_float(value):
"""Returns True if the argument can be casted to a float."""
try:
float(value)
return True
... |
5923880dfc99918058517058dff3579435b50ef7bed4981e55ffab8c51be9e77 | Python | 1,271 | 36 | #############################################################################
# Copyright (C) 2020-2026 MEmilio
#
# Authors: Henrik Zunker
#
# Contact: Martin J. Kuehn <Martin.Kuehn@DLR.de>
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the Lice... |
71d04c60fcc7394dc2b9972de2c6219c579c929709cdc298662977a12a085740 | Python | 1,271 | 35 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import os
import tempfile
from scilpy import SCILPY_HOME
from scilpy.io.fetcher import fetch_data, get_testing_files_dict
# If they already exist, this only takes 5 seconds (check md5sum)
fetch_data(get_testing_files_dict(), keys=['processing.zip'])
tmp_dir = tempfile.T... |
384c68ab8cca69d1f8b23b1ec1b2d503e05da8055d54ec43685ce717102237f0 | Python | 1,273 | 41 | # -----------------------------------------------------------------------------
# Copyright © 2009- The Spyder Development Team
#
# Licensed under the terms of the MIT License
# (see LICENSE.txt for details)
# -----------------------------------------------------------------------------
"""Provides QtSql classes and f... |
b7006240f63d952e6087d6b94be0404b828d6857a199541e824b6cb7efa6abd0 | Python | 1,274 | 27 | """A collection of miscellaneous utility functions.
TODO: Anything that used to be in nems.utils.py should go in this directory,
with functions of similar purpose grouped in modules. Even if there's just
one function that belongs in a solo group, it should *not* just be dumped
in 'misc' or 'etc' or a... |
29cd9b84c8a8677113fd14a61ed5820c918dc6a2be8dd19d8e6756b3162a6490 | Python | 1,276 | 39 | import pytest
from qtpy import PYQT5, PYQT_VERSION, QtXml
def test_qtxml():
"""Test the qtpy.QtXml namespace"""
assert QtXml.QDomAttr is not None
assert QtXml.QDomCDATASection is not None
assert QtXml.QDomCharacterData is not None
assert QtXml.QDomComment is not None
assert QtXml.QDomDocument... |
8bf48dc821e4a30dd55e9d0ba584c843b2c1683f77050fb5e941c21c6b82261b | Python | 1,276 | 54 | from typing import Literal, ClassVar
from matplotlib import pyplot as plt
from argclz import argument
__all__ = [
'PlotOptions',
'FIG_MODE',
]
FIG_MODE = Literal['simplified', 'presentation']
class PlotOptions:
"""Plot options (i.e., figure style, dark theme, ...)"""
GROUP_PLOT: ClassVar = 'Plot ... |
b69722cdafc6406cf060e8ebc3b0d808e7658c6a0c477f4cd03f6cd412a5b894 | Python | 1,276 | 34 | import torch
from batchgeneratorsv2.transforms.base.basic_transform import ImageOnlyTransform
from batchgeneratorsv2.helpers.scalar_type import RandomScalar
class MissingModalityTransform(ImageOnlyTransform):
def __init__(self, probability: RandomScalar = 0.2):
"""
Custom transform to randomly set... |
3beaa32759a93a8484d58bed33a276acac1b2aa60907affcf6b12f2132e3575f | Python | 1,277 | 53 | from typing import List, Union
import numpy as np
import tensorflow as tf
from deepreg.constant import EPS
def is_equal_np(
x: Union[np.ndarray, List], y: Union[np.ndarray, List], atol: float = EPS
) -> bool:
"""
Check if two numpy arrays are identical within a tolerance.
:param x:
:param y:
... |
052bffaba7970ddfe0e92f196cafb7297045d45cfdded8fa1493618866aa6cb2 | Python | 1,278 | 37 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import os
import tempfile
from scilpy import SCILPY_HOME
from scilpy.io.fetcher import fetch_data, get_testing_files_dict
# If they already exist, this only takes 5 seconds (check md5sum)
fetch_data(get_testing_files_dict(), keys=['others.zip'])
tmp_dir = tempfile.Tempo... |
92ced681731dba7a1d041c057e3d579b4a829b6dc04f3b7cb1eb4785f9b2429e | Python | 1,278 | 38 | from typing import Set
from zigzag.classes.hardware.architecture.core import Core
from zigzag.classes.hardware.architecture.memory_instance import MemoryInstance
class Accelerator:
"""
The Accelerator class houses a set of Cores with an additional Global Buffer.
This Global Buffer sits above the cores, an... |
99755e1d74e2207652f4b70ab4c6ead857821ef7cc45cc9ad985c2403e2a2292 | Python | 1,278 | 43 | # -*- coding: utf-8 -*-
"""
Spyder Editor
This is a temporary script file.
"""
from os import listdir
import pandas as pd
tallyfile=pd.DataFrame()
filedirectory='filtered'
files=listdir('filtered')
z=0
for file in files:
if file.endswith('.summary'):
unclassified=0
total=0
... |
adacb6652c1c524e5891f5e1de108d4c53046cf92f6de7f4fa8620b8d292ed6c | Python | 1,279 | 34 | import torch.nn as nn
from Model.resnet import resnet18, resnet34, resnet50
from Model.vgg import vgg16_bn, vgg19
from efficientnet_pytorch import EfficientNet
from Model.DenseNet import densenet121
import pretrainedmodels
def create_model(model, pretrain):
if model == 'vgg16_bn':
Model = vgg16_bn(pretrai... |
ae76257dac17c3aaf4f0302d8e780d57ef53d681dc0ea04a967b2e20af3721b0 | Python | 1,279 | 28 | # Copyright (c) OpenMMLab. All rights reserved.
def make_divisible(value, divisor, min_value=None, min_ratio=0.9):
"""Make divisible function.
This function rounds the channel number to the nearest value that can be
divisible by the divisor. It is taken from the original tf repo. It ensures
that all la... |
a4bb3ce86724f8a1c266d539ac37ea9710ce3fb58f480236efdd98c3ba0a8abb | Python | 1,280 | 39 | """Filter CSV files in a directory to keep only rows with valid RDKit SMILES."""
from pathlib import Path
import pandas as pd
from rdkit import Chem
from tap import tapify
from tqdm import tqdm
def filter_valid_smiles(
data_dir: Path,
smiles_column: str = "smiles",
) -> None:
"""For each CSV in the dire... |
a9ec826454798b48e12c662a1c4d976097b335352ffd0112e5794312ea349235 | Python | 1,280 | 49 | # -*- coding: utf-8 -*-
# python standard library inputs
import os
import sys
# external inputs
from nipype.interfaces.freesurfer import Curvature
def get_curvature(file_in, path_output, a=10):
"""Get curvature.
This function calculates a curvature file for an input surface mesh using
freesurf... |
db2feb7ff5d4dfa6d60daf1b2929f83cf834eff046e276d5a18101c139d91834 | Python | 1,280 | 28 | """TensorFlow layers, callbacks, and utilities used by the models.
This subpackage contains the building blocks that the model classes in
:py:mod:`osl_dynamics.models` use internally. Most users will not need to
interact with this subpackage directly.
Modules
-------
- :py:mod:`~osl_dynamics.inference.layers` — Custo... |
0d6e3378c7936c75693ca0f32014e35b3e8666414075c4f9e03bd5cdebe7bc4d | Python | 1,281 | 46 | # fmt: off
# flake8: noqa
import csv
import os
from collections import OrderedDict
def validate_metrics_list(metrics_list):
"""Get names of metric class and ensures they are unique, further checks that the fields within each metric class
do not have overlapping names.
"""
metric_names = [metric.get_n... |
94ca2320a60584679b75699e31fccbd1a5463fd6a6f12cac2017ca29776daaae | Python | 1,281 | 39 | # =============================================================================
# MODULES AND ENVIRONMENT VARIABLES
# =============================================================================
# Python built-in
import os
import sys
import time
import logging
import json
import pickle
import re
import math
import im... |
995698624b10052e7b219dec0f3c6f40891129807b2d29ec2e25681f83d414a1 | Python | 1,282 | 51 | # -*- coding: utf-8 -*-
# python standard library inputs
import os
# external inputs
from nibabel.freesurfer.io import read_morph_data, write_morph_data, \
read_geometry
from scipy.interpolate import griddata
def morph2dense(source_sphere, target_sphere, input_morph, path_output):
"""Morph to dense.
... |
a7e49889fce39ef8f72310fd40016e865965f5842cb065c4a10f757811809e68 | Python | 1,282 | 44 | import numpy as np
from pyment.metrics.r_squared import R2
def test_result_is_one_for_perfect_predictions():
metric = R2()
metric.update_state([1.0, 2.0, 3.0, 4.0], [1.0, 2.0, 3.0, 4.0])
assert np.isclose(metric.result().numpy(), 1.0), (
'Expected R2 to return 1.0 for perfect predictions'
)
... |
b75b942e3ca5fd10a5407dfdf7cfe38d95ab8246ea625da99cd66bf567307a15 | Python | 1,282 | 24 | from typing import Union, List, Tuple
import torch
from batchgeneratorsv2.transforms.base.basic_transform import SegOnlyTransform
class ConvertSegmentationToRegionsTransform(SegOnlyTransform):
def __init__(self, regions: Union[List, Tuple], channel_in_seg: int = 0):
super().__init__()
self.region... |
0f041496047b1e6ff8425ad7a5d7c68b2491cff0ede2ac54e7559274480b7e1d | Python | 1,283 | 44 | # 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
import os
import sys
sys.path.insert(0, os.path.abspath("../../"))
# -- Project information -----------------------... |
6d44fcd443b0a7df4340baae4807d47f6f2362933c38413aaea0d2081d55ab52 | Python | 1,283 | 42 | from __future__ import annotations
import pytest
from PySide6.QtCore import QPointF
from pytestqt.qtbot import QtBot
import labelme._utils
from labelme._app import MainWindow
from labelme._widgets._brightness_contrast_dialog import BrightnessContrastDialog
from ..conftest import close_or_pause
@pytest.mark.gui
def... |
7a90362e8f74aea28aa928232ccdb529215908050a3dc5edc6f4a3fed767b3c6 | Python | 1,285 | 53 | import dataclasses
from collections.abc import Callable
import torch
from torch import nn
from eir.models.fusion.fusion_default import al_features, default_fuse_features
al_identity_features = Callable[[dict[str, torch.Tensor]], dict[str, torch.Tensor]]
@dataclasses.dataclass
class IdentityConfig:
pass
def p... |
03ea0fb1f0339c33cf27391c3bac56160ba8ea52a6aed7320be97ab12b550bf0 | Python | 1,286 | 47 | from ..qt import *
from ..observable_item_models import TreeObservableCollectionModel
from ..config import ObservableDict
import logging
LOGGER = logging.getLogger(__name__)
class PersistenceWidget(QWidget):
def __init__(self, config: ObservableDict):
super().__init__()
LOGGER.debug('%s', config)
if '... |
341c8fd97aae6e46edf642a6e7ce4cec3ac563d5ec0d7187f10b883df2f53c9b | Python | 1,286 | 60 | import numpy as np
from impedancefitter.double_shell import double_shell_model
from impedancefitter.single_shell import single_shell_model
omega = 2.0 * np.pi * np.logspace(0, 12, num=30)
# for cole_cole_model
c0 = 1.0
em = 10.0
km = 1e-6
kcp = 0.5
ecp = 60
kmed = 0.1
emed = 80
p = 0.1
dm = 5e-9
Rc = 5e-6
# fo... |
c235a54e0dd0eba0bd9d7882fd949b7668340721ef9d15b298681c840f9498fe | Python | 1,286 | 38 | import os
import json
import torch
import pandas as pd
import numpy as np
from tqdm import tqdm
from pathlib import Path
path1 = Path('datasets/Twibot-20/node.json')
with open(path1, 'r') as f:
nodes = json.loads(f.read())
nodes = pd.DataFrame(nodes)
users = nodes[nodes.id.str.contains('^u')]
tweets = ... |
2dfa7f74abf81c867d0ca08140c378f44eb17361e2d9581ec67f49024e0b4b81 | Python | 1,287 | 45 | # -*- coding: utf-8 -*-
"""
Created on Fri Oct 21 12:26:17 2022
@author: tianj
"""
import torch.nn as nn
import torch
# Discriminator model class definition
class Discriminator(nn.Module):
def __init__(self,
patch_size: int):
super(Discriminator, self).__init__()
... |
4e34815e2f95541243cbc154717cb4e46a0ec8142feed0da29770e9f2a18aaf8 | Python | 1,287 | 41 | from typing import TYPE_CHECKING
from eir.models.output.sequence.sequence_output_modules import SequenceOutputModule
from eir.setup.output_setup_modules.sequence_output_setup import (
ComputedSequenceOutputInfo,
)
al_sequence_module_classes = type[SequenceOutputModule]
if TYPE_CHECKING:
from eir.models.model... |
e75745c52c6df825c0f83d7d512476a0212b8caf8f82f1b9bb1fa710bf9c614f | Python | 1,287 | 38 | class TestSegment():
# Parse command line arguments with all required parameters
def test_parse_with_all_required_parameters(self):
# Given
import sys
from argparse import Namespace
from python.segmentation.segment import parse
# Save original sys.argv
origi... |
0e320e7ea6289ec1ce533110b6d77dcb16f85b28bd1672c18651f2f4ad33889a | Python | 1,288 | 37 | # -*- coding: utf-8 -*-
"""
Created on Tue Dec 3 17:19:44 2019
@author: Yoshi
"""
import numpy as np
from statistics import mean
def data_reader(image_stack,cell_arrays,background_arrays):
# Creates empty array to store data in
image_total = image_stack.shape[0]
cell_total = len(cell_arrays)
... |
5e4530ba6023958fd74eba52d8923c37f9b1bdf830beab03e7b19c916b07af00 | Python | 1,288 | 46 | """Pydantic configuration for FastSurfer dataset loading."""
import os
from typing import Any, Callable
from numpy.typing import ArrayLike
from pydantic import BaseModel
from ..data.fastsurfer_dataset import FastSurferDataset
class FastSurferDatasetConfiguration(BaseModel):
"""Configuration for a FastSurfer da... |
afe340d67e953dff530e6b4327590a234b06009a5f9ecc948bb32aa1be157595 | Python | 1,288 | 50 | #!/usr/bin/env python
"""
Complement the regions of a bed file. Requires a file that maps source names
to sizes. This should be in the simple LEN file format (each line contains
a source name followed by a size, separated by whitespace).
usage: %prog bed_file chrom_length_file
"""
from bx.bitset_builders import binn... |
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