sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
ba93e4ee3753dd87574998e4a14f2ace97e172201f5c13bc2e79a0d2d33cdbe5 | Python | 1,166 | 33 | import zipfile
import os
import subprocess
import time
import zenodo_get
def unzip_file(zip_file_path, extracted_folder_path):
# Open the zip file
with zipfile.ZipFile(zip_file_path, 'r') as zip_ref:
# Extract each file one by one
for file_info in zip_ref.infolist():
zip_ref.extract... |
0adc952fffcb2b4f3a413e273f918eba93355f2df2cdd453f2456d92db0cada1 | Python | 1,168 | 44 | import plotly.plotly as py
import plotly.figure_factory as ff
import plotly.graph_objs as go
data = [['', 'Emma', 'Isabella', 'Ava', 'Olivia', 'Sophia', 'row-sum'],
['Emma', 16, 3, 28, 0, 18, 65],
['Isabella', 18, 0, 12, 5, 29, 64],
['Ava', 9, 11, 17, 27, 0, 64],
['Olivia', 19, 0, 31, 1... |
3e256e3069a7d4d9dc1aacaf969b9d26149e91e73d6fc2717f90cea488a3e615 | Python | 1,168 | 38 | import pandas as pd
import numpy as np
def load_database():
# set up to run the R code
try:
import rpy2.robjects as robjects
from rpy2.robjects.packages import importr
import anndata2ri
anndata2ri.activate()
robjects = robjects
importr("CellChat")
except I... |
920d5efb80e861b85396e55ce28284ae76c5f6521b5bc325d209d52c875828ac | Python | 1,168 | 27 | import os
import sys
import pandas as pd
from model.Ouroboros import Ouroboros
from utils.chem import prepare
if __name__ == "__main__":
model_name = sys.argv[1]
smiles_col = sys.argv[2]
extrnal_data = pd.read_csv(sys.argv[3])
job_name = f'{os.path.splitext(os.path.basename(sys.argv[3]))[0]}_{os.path.b... |
a5ba8ab965f9be66300a66259689b978302d1038b63ab811dbd15aea5feeaac6 | Python | 1,168 | 28 | from typing import Union, Tuple, Callable
import numpy as np
RandomScalar = Union[int, float, Tuple[float, float], Callable[..., Union[int, float]]]
def sample_scalar(scalar_type: RandomScalar, *args, **kwargs):
if isinstance(scalar_type, (int, float)):
return scalar_type
elif isinstance(scalar_type... |
ec20b0f99499dca9095e7eee9d85f0e1d33d8b20a41d60d9d40158a2787782e8 | Python | 1,168 | 34 | # -*- coding: utf-8 -*-
"""
Temporal correction
This scripts performs slice timing correction and temporal regridding on a nifti
time series. The script needs an installation of afni.
"""
# local inputs
from fmri_tools.preprocessing.slice_timing_correction import slice_timing_correction
# input
file_in = [
"/da... |
30452e1e68a2b81645dd5804d1ee19133184eab4e40e4b6e137bb4395395e2aa | Python | 1,169 | 36 | """ Create a cube mesh with perserved sharp edges in a plane """
# TODO USE POLYLINES
import SVMTK as svm
from pathlib import Path
if __name__ == "__main__":
print("Start ",__file__)
outdir = Path("results")
outdir.mkdir(exist_ok=True)
surf = svm.Surface()
# Center coordinates
x,y,z = 0,0,0
... |
6b52d1c5511e6f187a92d0628eda30ea7444fc9f59e68df4f59b93a8e55dea2a | Python | 1,169 | 49 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import argparse
USAGE = '''usage: %(prog)s [options] arg1 arg2'''
def get_args():
"""TODO: Docstring for get_args.
:returns: TODO
"""
parser = argparse.ArgumentParser(usage=USAGE)
parser.add_argument('-i', action='store', default='', required=Tru... |
4ec2fb90d57ad007a4c4ef0a3eaf7ea304912478165e62a5da43bae945648a5d | Python | 1,170 | 44 | """Calculate summary statistics.
"""
from sys import argv
if len(argv) != 3:
print("Please pass the number of states and run id, e.g. python 5_calc_summary_stats.py 8 1")
exit()
n_states = int(argv[1])
run = int(argv[2])
#%% Import packages
print("Importing packages")
import os
import pickle
import numpy a... |
7820679cb0371f021ddc61a7d05901d447a76e56f2ed4305cf9efb5f91468f87 | Python | 1,170 | 37 | """Top-level Pydantic configuration for a finetuning run."""
import os
from pydantic import BaseModel, Field, field_validator
from .data_split_configuration import DataSplitConfiguration
from .dataset_configuration import FastSurferDatasetConfiguration
from .sfcn_configuration import SFCNConfiguration
from .target_c... |
e876fef4da371030e203671c91178742cdc24a691c96b244724ca70051f13539 | Python | 1,170 | 39 | import numpy as np
import torch
def torch_detrend(x: torch.Tensor) -> torch.Tensor:
"""
Detrends a tensor along the last axis using a linear fit.
:param x: Array to detrend
:returns: Detrended array
"""
m = x.mean(dim=-1, keepdim=True)
samples = torch.linspace(-1, 1, x.shape[-1], device=x... |
02fa0e8053587934a39c0c1e5d5c42052441f7e3cef924f3c11352070e5443af | Python | 1,171 | 36 | """Test QtWinExtras."""
import sys
import pytest
from qtpy import PYQT6, PYSIDE2, PYSIDE6
from tests.utils import using_conda
@pytest.mark.skipif(
PYQT6 or PYSIDE6,
reason="Not available on Qt6-based bindings",
)
@pytest.mark.skipif(
sys.platform != "win32" or using_conda(),
reason="Only available ... |
7020268b35bf4181c26f33c6ee143010d15c74f80a356a2835f6df143ccb31c4 | Python | 1,171 | 34 | from setuptools import setup, find_packages
with open("README.md", "r", encoding="utf-8") as fh:
long_description = fh.read()
with open("requirements.txt") as f:
requirements = [line.strip() for line in f if line.strip() and not line.startswith("#")]
setup(
name="avpenet",
version="1.0.0",
author... |
82d3771fb6d57d03441d89be78f0e5af590868001be8aca0a45299971434fbe5 | Python | 1,171 | 36 | from collections import Counter
import numpy as np
from probeinterface import read_spikeglx
from probeinterface.neuropixels_tools import build_neuropixels_probe
def test_spikeglx_reader_is_available_from_public_api() -> None:
assert callable(read_spikeglx)
def test_np2013_catalogue_geometry_matches_four_shank_... |
8f81427e8fb6a22accb120192010069c9275bd4dfebe4991c4cd6e91b818b5fc | Python | 1,172 | 30 | """Cooperative cancellation for pipeline runs.
The pipeline is long-running (spike detection + probabilistic thresholding can
take minutes). To let the GUI's Stop button actually interrupt a run, each step
periodically calls ``check_cancel(should_cancel)`` — typically once per
recording — which raises :class:`Pipeline... |
fb39b6629b89b3fe16c22c34761154b197de9803107988668043e7f0b91d4c58 | Python | 1,172 | 50 | # The Python wrapper generated using pybind11 is a compiled dynamic library,
# with a name like _arbor.cpython-38-x86_64-linux-gnu.so
#
# The library will be installed in the same path as this file, which will imports
# the compiled part of the wrapper from the _arbor namespace.
from ._arbor import * # noqa: F403
#... |
736c9879f7f753c45cd9bad2bbe34fada5370ebe1ae5f13ef268398b67a0547d | Python | 1,173 | 29 | import matplotlib.pyplot as plt
def plot_3d_z_indices(vol, idx_list, transpose=True,
num_rows=1, num_cols=1,
label_loc_x=5, label_loc_y=5,
im_origin = "lower", figsize=(18,16)):
"""Plot z-index slices of a 3d volume as subplots"""
vol = vol.sq... |
91fbfd7a82f54eb94a83827d59259bd670870226f9285009eefb0f19eaf4b5f4 | Python | 1,173 | 45 | from setuptools import setup, find_packages
import versioneer
author = 'David S. Fischer, Florian R. Hölzlwimmer'
author_email='david.fischer@helmholtz-muenchen.de, diffxpy@frhoelzlwimmer.de'
description="Fast and scalable differential expression analysis on single-cell RNA-seq data"
with open("README.rst", "r") as f... |
b597db3636bc36ccf0b9f0fe98a6707a9583ea4f8f9f163391d27454e458da7b | Python | 1,173 | 45 | """Module for logger."""
import logging
import os
import sys
def get(name: str) -> logging.Logger:
"""
Configure the logger with formatter and handlers.
The logger should be used as:
.. code-block:: python
from deepreg import log
logger = log.get(__name__)
The log level depend... |
6b189d849e4fa5993ae7f7e8e826e973c924290f0150f3b0de2ee8f2f65b667d | Python | 1,174 | 32 | import torch
from .base_reducer import BaseReducer
class DivisorReducer(BaseReducer):
def unpack_loss_info(self, loss_info):
losses, loss_indices, reduction_type, kwargs = super().unpack_loss_info(
loss_info
)
if reduction_type != "already_reduced":
kwargs = {"divi... |
9d477599b3b0cfa123cba299856522e7baf8a093b4b9f91701f316051570d285 | Python | 1,174 | 30 | import torch
import torch.nn as nn
import torch.nn.functional as F
from .efficientnet3d import EfficientNet3DB0
class sTSCnetDual(nn.Module):
"""
eTSC-Net (sTSCnet_dual):
- Dual input (T2W and FLAIR)
- Two EfficientNet3D-B0 feature extractors
- Trainable fusion weights
- Final classi... |
38ac4b5d5021613716ab3494feacb24d29d1130824351efbf04c7d7d67671c29 | Python | 1,175 | 54 | """Dual estimation of observation model parameters.
"""
from sys import argv
if len(argv) != 3:
print("Please pass the number of states and run id, e.g. python 4_dual_estimation.py 8 1")
exit()
n_states = int(argv[1])
run = int(argv[2])
#%% Import packages
print("Importing packages")
import os
import pickl... |
5c3728012eaa588cb5da0e181fe2a1c85c01f619f039a6710bfef39555cfa5d8 | Python | 1,175 | 36 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
from django.db.models.signals import post_save
from django.dispatch import receiver
from cvat.apps.engine.models import Project, Task
from cvat.apps.quality_control.models import (
QualitySettings,
ensure_base_quality_requirements,
)
def _... |
d3acd0702a691dad33386c492dab785bd5a44c9d2c3f2f76d5657e3fc958548f | Python | 1,176 | 38 | # -*- coding: utf-8 -*-
"""Tools for smoothing 3D nifti data."""
from pathlib import Path
import numpy as np
import nibabel as nb
from dipy.denoise.nlmeans import nlmeans
from dipy.denoise.noise_estimate import estimate_sigma
__all__ = ["nlm"]
def nlm(file_in, file_out, n=64, scale=1.0):
"""Apply edge-preservin... |
4d841dac9099c9f779dd9bdd418359f09b41a51b854d56343fc4842599a41392 | Python | 1,178 | 54 | #!/usr/bin/env python
"""
Remove any blocks from a maf that overlap any of a set of intervals.
usage: %prog interval files... < maf
"""
import sys
import bx.align.maf
from bx import intervals
from bx.cookbook import doc_optparse
def __main__():
options, args = doc_optparse.parse(__doc__)
try:
ass... |
ff5c08e10e45167cbb02c89bfb4a663c6d2bfcfd927d090fb8afe90e4222af95 | Python | 1,178 | 31 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
from django.core.management.base import BaseCommand, CommandError
from rest_framework.exceptions import ValidationError
from cvat.apps.engine.user_deletion import delete_user_with_cleanup
from cvat.apps.iam.models import User
class Command(BaseCom... |
8ef0718491363490f54e9fa35b5befbd7d424eabfd006494c7b4b32848c57005 | Python | 1,179 | 41 | import torch
import torchio
import numpy as np
from torchio.transforms import Transform
class NormalizeXvals(Transform):
def __init__(self, normalization_factor, **kwargs):
self.normalization_factor = normalization_factor
super().__init__(**kwargs)
def apply_transform(self, subject):
... |
519703d7c8134787e872555235426c8670df583364b9aa1dc1168e12aff4a9ab | Python | 1,180 | 31 | #!/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... |
9a30420a88330fc6daa7af782782c16445e4165411c609ee842412293b3ae3b5 | Python | 1,180 | 46 | #!/usr/bin/env python
"""
Test HAL error handling.
"""
import os
import pytestqt
import sys
from PyQt5 import QtCore, QtGui, QtWidgets
import storm_analysis.sa_library.datareader as datareader
import storm_control.hal4000.hal4000 as hal4000
import storm_control.sc_library.hdebug as hdebug
import storm_control.sc_lib... |
a0ea959ed8691fece73bd4728a4b77c1c832466d7c5deccf20a152f7d8fe0a52 | Python | 1,180 | 53 | from pathlib import Path
import nibabel as nib
def get_full_case_id(cid):
try:
cid = int(cid)
case_id = "case_{:05d}".format(cid)
except ValueError:
case_id = cid
return case_id
def get_case_path(cid):
# Resolve location where data should be living
data_path = Path(__fi... |
1147c6832130134d8751b70be782bdcec1520552378508688762e8350170e040 | Python | 1,181 | 39 | import numpy as np
from PIL import Image
from scipy.ndimage import gaussian_filter
from skimage import morphology
from brainways.utils.image import convert_to_uint8
class PreProcess:
def __init__(self):
self.remove_outer_speckles = RemoveOuterSpeckles()
self.pseudo_flatfield = PseudoFlatField()
... |
e4b0eae20dde040501a69181b7ccfca2a8571a1fcef0d0fec146e55e7373bfbd | Python | 1,181 | 31 | import sys
import subprocess
from glob import glob
import os
import yaml
lick_exptypes = ['Detection']#'Detection',,'Association' --> association sucks, ditch it!
script1 = 'preprocessing/lick_extraction/run_licktrace_icadet.py'
scripts = [script1]#script1,
pathpath = 'PATHS/artifact_paths.yml'
with open(pathpath, 'r... |
f92250721afd37fbb7d7d08a62aa292471b1335915bb1256aa1ea03b94caab86 | Python | 1,181 | 37 | import os
import subprocess
from dataclasses import dataclass
@dataclass(frozen=True)
class ReadsData:
dir_path: str
fwd: bool = True
rev: bool = False
def run_cmd(command: list):
os.system(" ".join(command))
def qiime2_version():
o, e = run_cmd(["conda", "env", "list"])
qi... |
6827538db3950cc518786d44735c452120bc36df595449656db05165ef83f825 | Python | 1,183 | 40 | import yaml
from pathlib import Path
import os
def get_project_root():
current_dir = Path(__file__).resolve().parent
while not (current_dir / 'README.md').exists(): # Find dir with README.md (project root)
if current_dir.parent == current_dir:
return Path.cwd()
current_dir = curren... |
cd160c69ba1d222604e046f786a0648cc738e12454b07e7622f3e2c5957c1b5f | Python | 1,183 | 43 | from napari_dmc_brainmap.utils import dropdown_utils
def test_available_atlases_uses_v3_listing_api(monkeypatch) -> None:
monkeypatch.setattr(
dropdown_utils,
"get_all_atlases_lastversions",
lambda: {
"admba_3d_e11_5_mouse_16um": "3.0",
"allen_mouse_25um": "1.2",
... |
d1398a06b305f3dae43e800bd7f6c80deded5049221bd51c99de60cac93371ad | Python | 1,183 | 34 | import torch
from eir.data_load.data_preparation_modules import common
def test_sample_sequence_uniform():
test_tensor = torch.arange(0, 100)
sampled_tensor = common._sample_sequence_uniform(
tensor=test_tensor, tensor_length=len(test_tensor), max_length=50
)
assert len(sampled_tensor) == 50... |
fc3907db2060f8993a29b9be7fc13bc004dd23c6c203b07735b70aa3c9c061d9 | Python | 1,183 | 32 | import cv2
from nicety.conf import get_conf
from glob import glob
from tqdm import tqdm
from connectomics.data.utils.data_io import readvol, savevol
def apply_tiled_clahe(vol, clip_limit=2.0, tile_grid_size=(8, 8), kernel_size=256):
clahe = cv2.createCLAHE(clipLimit=clip_limit, tileGridSize=tile_grid_size)
fo... |
76ccfaff7294a65f56f58cfb212159f3234122e348e5ab5f9eae3a6ec430b8f1 | Python | 1,185 | 37 | class TestTrain:
# Parse command line arguments with all required arguments provided
def test_parse_with_all_required_arguments(self):
# Given
import sys
from argparse import Namespace
from unittest.mock import patch
from python.segmentation.train import parse
... |
9724cdb6be17660dca5042eae427cbc1373744c8836d3cdc7dd02e146ac79c0f | Python | 1,185 | 37 | class TestTrain:
# Parse command line arguments with all required arguments provided
def test_parse_with_all_required_arguments(self):
# Given
import sys
from argparse import Namespace
from unittest.mock import patch
from python.segmentation.train import parse
... |
9df23b2e972aad5090d29bb0b3fdb003fc5c96954d6c22b140e460567b6a5b4d | Python | 1,185 | 45 | # myelinfccoupling/util.py
from pathlib import Path
from typing import Dict, List
import pandas as pd
def ensure_dir(path: Path) -> None:
"""Create a directory (and parents) if it does not exist."""
path.mkdir(parents=True, exist_ok=True)
def sanitize_label(label: str) -> str:
"""
Make a label safe... |
4956f2f83249b6440945ba5bf51cf41cda936b46c915a646b871c9999c458476 | Python | 1,187 | 44 | #!/usr/bin/env python
"""
QPushButton specialized to be a shutter button.
Hazen 4/17
"""
from PyQt5 import QtWidgets
class QtShutterButton(QtWidgets.QPushButton):
def __init__(self, parent = None, **kwds):
kwds["parent"] = parent
super().__init__(**kwds)
self.cam_fn = None
self.... |
60080ebb92eb8df876690bcef34fbd50d3d38af60b720e7035aa93686c4fe2ab | Python | 1,187 | 52 | import numpy as np
from impedancefitter import get_equivalent_circuit_model
from impedancefitter.loss import Z_in, Z_loss
omega = 2.0 * np.pi * np.logspace(1, 8, num=20)
L = 1
C = 1
R = 1
def test_loss_type():
"""Test return type."""
Z = Z_loss(omega, L, C, R)
assert isinstance(Z, np.ndarray)
def tes... |
a79699cc51cc19681865a74acdacd16fa073e250fb062198a3ab9accc8888096 | Python | 1,187 | 37 | import networkx as nx
import logging
from zigzag.classes.stages.Stage import Stage
from zigzag.classes.workload.dummy_node import DummyNode
logger = logging.getLogger(__name__)
class WorkloadStage(Stage):
"""
Class that iterates through the nodes in a given workload graph.
"""
def __init__(self, l... |
c0fb22bababa7cce9b09e2351b0f71c0d70fb4a30e1119d7ea663edaa73ee56f | Python | 1,187 | 23 | from brainscore_vision import stimulus_set_registry
from brainscore_core.supported_data_standards.brainio.s3 import load_stimulus_set_from_s3
BIBTEX = """@inproceedings{NEURIPS2019_97af07a1,
author = {Barbu, Andrei and Mayo, David and Alverio, Julian and Luo, William and Wang, Christopher and Gutfreund, Dan and Tenen... |
339cfbe34fdec07bd4f31ebf3628edcd75d7eb5cf344f43f29cafd77a3ef6a53 | Python | 1,188 | 36 | def replace_with_custom_fn_if_matches_filter(
model, replacement_fn, filter_fn, cur_fqn=''
) -> None:
"""
For each `child` in `model`, replaces it with `replacement_fn(child)`
if `filter_fn(child)` is `True`
"""
name_to_child = dict(model.named_children())
for name, child in name_to_child.it... |
7ad1468b5f09ab54dd84097a742e24e9ff9f268f25c24589a31b93aec06f03bd | Python | 1,188 | 41 | import torch
import numpy as np
def replace_numpy_with_torchtensor(obj):
# assume obj comprises either list or dictionary
# replace all the numpy instance with torch tensor.
if isinstance(obj, dict):
for key in obj.keys():
if isinstance(obj[key], np.ndarray):
obj[key] =... |
c5b0a8774b113761c0b665c35faf281d37f1c1328375faef6d59ee97dee711b9 | Python | 1,188 | 39 | import unittest
import sys
import random
import jellyfish
class TestHashCounter(unittest.TestCase):
def setUp(self):
jellyfish.MerDNA.k(100)
self.hash = jellyfish.HashCounter(1024, 5)
def test_info(self):
self.assertEqual(100, jellyfish.MerDNA.k())
self.assertEqual(1024, self.h... |
e1deeb70ae745f0eb1375e4d6ebc5da305fb6579325924b0151956f032c96d6e | Python | 1,189 | 41 | from setuptools import setup
import sys
CLASSIFIERS = [
"Development Status :: 4 - Beta",
"Natural Language :: English",
"License :: OSI Approved :: MIT",
"Operating System :: OS Independent",
"Programming Language :: Python :: 3.7",
"Topic :: Scientific/Engineering :: Bio-Informatics",
]
if s... |
0d9d5424a8c6aa6abaf97bcf52de280f3fc7fe3efc3f9c0f8da29b344fd1f3cb | Python | 1,190 | 73 | from .application import ApplicationBackend
from .widgets import (
CheckBox,
ComboBox,
Container,
DateEdit,
DateTimeEdit,
Dialog,
FloatRangeSlider,
FloatSlider,
FloatSpinBox,
Image,
Label,
LineEdit,
LiteralEvalLineEdit,
MainWindow,
Menu,
MenuBar,
Passw... |
fe9a62ddd0e70ff3e9ac6e6f20fc02ed32a68f960fca3a9270c906d7917aef44 | Python | 1,190 | 32 |
cdict = {'rA':'grey','rB':'k',\
'c1':'firebrick','c2':'dodgerblue','c3':'goldenrod','c4':'darkviolet'}
c_empty = 'w'
Adom_c23Imbalance = {'reg_prob_dict':{'rA':0.7},\
'cat_labels':['c1','c2','c3'],\
'cond_dict':{('c1','rA'):0.6, \
... |
12dc88151234d1108f05acd2dac4b63fd3929255ec74b3bdc93016c5002bb4e0 | Python | 1,191 | 45 | import functools
import numpy as np
def arrayize(type):
def decorator(func):
def wrapper(*args, **kwargs):
return np.fromiter(func(*args, **kwargs), type)
return functools.update_wrapper(wrapper, func)
return decorator
@arrayize(int)
def detect_peaks(y, min_high_ratio=0.... |
256f79882d40cbc2f3dd8fe203c9c9295e39c539b360f51eb3f8a3ddbf49c56a | Python | 1,192 | 44 | import torch
import numpy as np
class Cutout(object):
"""Randomly mask out one or more patches from an image.
Args:
n_holes (int): Number of patches to cut out of each image.
length (int): The length (in pixels) of each square patch.
"""
def __init__(self, n_holes, length):
se... |
27530511063cb592fd0a3fd6d4a29b0758ad3e94c944542d573ea01b8b78f63e | Python | 1,192 | 39 | # laminar_rs/config.py
from __future__ import annotations
from dataclasses import dataclass
from pathlib import Path
from typing import List
@dataclass
class LaminarConfig:
"""
Configuration for a single subject / dataset.
Parameters
----------
data_dir : Path-like
Directory containing th... |
55185478b378869a4ce41a2c8f67659d28488e4c697859148100128f9d54a8ce | Python | 1,192 | 43 | from pathlib import Path
import click
from tqdm import tqdm
from brainways.project.brainways_subject import BrainwaysSubject
from brainways.utils.cell_detection_importer.utils import (
cell_detection_importer_types,
get_cell_detection_importer,
)
@click.command()
@click.option(
"--input",
type=Path,... |
986f209a10a26c8ada3c21bdd451f1a2baea0493e3dacb3843ac00b70cc4ff4b | Python | 1,194 | 44 | # -*- coding: utf-8 -*-
"""
Created on Thu Apr 6 21:08:42 2023
@author: axthi
"""
from simnibs import sim_struct
def get_simu_template():
"""
returns standard simulation settings
Returns
-------
S : SESSION sim-struct
a SESSION sim-struct with standard simulation settings defined,
... |
ab076a681fb05fb75a0d049092469afe15278e6025504076db75d2856b483fa3 | Python | 1,194 | 32 | _base_ = ['RepLKNet-31B_22Kpretrain_upernet_160k_ade20k_640.py',]
model = dict(
backbone=dict(
channels=[192, 384, 768, 1536],
drop_path_rate=0.3,
),
decode_head=dict(
in_channels=[192, 384, 768, 1536]
),
auxiliary_head=dict(
in_channels=768
),
)
lr_config = dict... |
bed0fb294fb7cb16ee9ddb178adb8b5956ed973a80e3b069b105256e9b2cd100 | Python | 1,195 | 47 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
from enum import StrEnum
from django.conf import settings
from cvat.apps.iam.permissions import OpenPolicyAgentPermission
class UserGrowthDataPermission(OpenPolicyAgentPermission):
class Scopes(StrEnum):
LIST = "list"
VIEW = "... |
c695c24b8a7ff5ab2d1241a68511fbb0adbda4978db606651244bd5a8ebfe5b0 | Python | 1,195 | 28 | import numpy as np
import pytest
from brainscore_vision import load_dataset, load_stimulus_set
SESSIONS = {'190923': 1200, '201025': 1200, '210225': 1200, '211022': 1600}
@pytest.mark.private_access
class TestStimulusSet:
@pytest.mark.parametrize('session, num_stimuli', SESSIONS.items())
def test_stimulus_se... |
ba4b7a221318c1a9bc42034d999de480f41eb9509189f5b2eec6237aad1aece5 | Python | 1,197 | 40 | import os
import sys
import numpy as np
import pickle as pkl
from sklearn.neighbors import KNeighborsClassifier
from sklearn.model_selection import GroupKFold
sys.path.append('/home/garullie/CEBRA_analysis/')
from dataset_load import data_load
#index = int(os.environ["SLURM_ARRAY_TASK_ID"]) - 1
index=10
print(f"SLURM... |
f3c83f53a0693203167e3207c0b94183eb51573a7cf7d002615701b6db2904d9 | Python | 1,197 | 45 | #!/usr/bin/env python3
"""
merge_xtc.py
Script to reconstruct MD trajectory files (.xtc) that were split into multiple parts
for Zenodo upload. Works for both CNA-bound and Unbound systems.
Usage:
python merge_xtc.py
Requirements:
- Python 3
- All .part files must be in the same directory as ... |
c60ae7433139b220a34d07e5e1bf0e92a77bca6af418f35d6c2fbc1ac999e438 | Python | 1,198 | 43 | import logging
import sys
def setup_logger(name=None, level=logging.INFO):
"""Set up a logger with consistent formatting.
This function configures a logger with a standard format that includes
timestamp, logger name, log level, and message. It ensures that handlers
are not duplicated if the logger al... |
40431ef96938d1c64ca0b1fe283c948470116490adfaab534c9ce1f3b48f1253 | Python | 1,199 | 46 | import os
import numpy as np
import nibabel as nib
dsi_file = "/mnt/e/Neuroimage/workdir/fix/sub-TI001_ses-6m_acq-DSIb4000_dir-AP_space-preprocdwi_dwiref.nii.gz"
ref_file = "/mnt/e/Neuroimage/workdir/fix/b0_ref.nii.gz"
out_file = "/mnt/e/Neuroimage/workdir/fix/sub-TI001_ses-6m_acq-DSIb4000_dir-AP_space-preprocdwi_dwi... |
5cb9470d6bf0caab446adaa6aeb7e6cb5a87c3718479cbec500267c00cb198ab | Python | 1,199 | 37 | from typing import Literal
import torch
from torch.nn.functional import pad
def process_tensor_to_length(
tensor: torch.Tensor,
max_length: int,
sampling_strategy_if_longer: Literal["from_start", "uniform"],
padding_value: int = 0,
) -> torch.Tensor:
tensor_length = len(tensor)
if tensor_len... |
a05f3b26bc246769e1e685f7a8d5ff9e334d4ec2f6276697ac67a5f580478065 | Python | 1,199 | 42 | import os
import logging
import sys
def make_dir_if_not_exists(
pathstring,
): # pathstring sollte #das hier ist unnötig sobald ich alles als stream mache, dann mache ich einfach aus prinzip ein directory.
totalpath = os.path.join(os.getcwd(), pathstring)
if not os.path.isdir(totalpath):
try:
... |
d6e08af56c31f41ef0c7d9c73a9088c3f6615729910cb71c51bad33809a483b5 | Python | 1,199 | 39 | import os
import sys
import numpy as np
import pickle as pkl
from sklearn.neighbors import KNeighborsClassifier
from sklearn.model_selection import GroupKFold
sys.path.append('/home/garullie/CEBRA_analysis/')
from dataset_load import data_load
index = int(os.environ["SLURM_ARRAY_TASK_ID"]) - 1
print(f"SLURM ID = {ind... |
efb9440afe36cfda5d691dc2eafa17242fc5df47e027c98a29b04dc00a39ada7 | Python | 1,199 | 33 |
import dtiplayground.dmri.preprocessing as prep
import yaml, os
from pathlib import Path
import dtiplayground.dmri.common.tools as tools
class IDENTITY_Process(prep.modules.DTIPrepModule):
def __init__(self,config_dir,*args,**kwargs):
super().__init__(config_dir,*args,**kwargs)
global logger
... |
fae4db3fd0aacfe61068ccaeb5be9e94d1e4ba74f8a9e18d303c2bd33eb10a92 | Python | 1,199 | 34 | #!/usr/bin/env python
import math
import stl
from stl import mesh
import numpy
import sys
import argparse
import glob
#command line interface
parser = argparse.ArgumentParser()
parser.add_argument("-f", action = "store", dest = "foldername", help = "Store the root folder's name")
parser.add_argument("-o", action = "st... |
9e87f96702133f1ea568a61f3d1b617c4a100195dede0839e8e90cee52f91499 | Python | 1,200 | 28 | import matlab.engine
def dict_to_matlab_struct(pars_dict):
"""
Converts a Python dictionary to a MATLAB struct.
:param pars_dict: A dictionary where keys represent the names of fields in the MATLAB struct and the values
represent the corresponding field values.
:type pars_dict: di... |
bba9e6a920c0d0dd651acef2ab143bf1b63a8b464b0dee96fbea4f5c949480dc | Python | 1,200 | 55 | #!/usr/bin/env python
"""
Application to convert LAV file to MAF file. Reads a LAV file from standard
input and writes a MAF file to standard out; some statistics are written to
standard error.
usage: lav_to_maf [--silent] [path=replacement] < lav_file > maf_file
"""
import sys
import bx.align.lav
import bx.align.ma... |
cdf4a5dd18c88625a1f6745d6b1b32d81399f1107aa0a7eaf2f9565958bbe66a | Python | 1,200 | 37 | # Generated by Django 4.2.20 on 2025-04-28 16:14
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
("quality_control", "0009_qualitysettings_quality_settings_task_or_project"),
]
operations = [
migrations.AddConstraint(
model_na... |
e4cfea2fee53392dc847c4f14d9661490a3bc67bc4d6adbe601f3015bfd9f925 | Python | 1,201 | 50 | import numpy as np
from PIL import Image as PILImage
from .base import Stimulus
from brainscore_vision.model_helpers.activations.temporal.utils import batch_2d_resize
class Image(Stimulus):
def __init__(self, path: str, size: int):
self._path = path
self._size = size
def copy(self):
... |
05c161908997ebe1af8ee81c5d7588ee845c2e3c744fb83b5331eb202204ede8 | Python | 1,202 | 43 | """ Creates a cylinder mesh with boundary segmentations """
# TODO: complete
import SVMTK as svm
from pathlib import Path
if __name__ == "__main__":
print("Start ",__file__)
outdir = Path("results")
outdir.mkdir(exist_ok=True)
surf = svm.Surface()
# Lower and upper cylinder center coordinates.
x0,y... |
9486131a23def554c82054213d0bbb87a400d4f22bd9f49ac0385eb70b7fb013 | Python | 1,202 | 32 | import gdb
import re
ns_pattern = re.compile(r'nlohmann(::json_abi(?P<tags>\w*)(_v(?P<v_major>\d+)_(?P<v_minor>\d+)_(?P<v_patch>\d+))?)?::(?P<name>.+)')
class JsonValuePrinter:
"Print a json-value"
def __init__(self, val):
self.val = val
def to_string(self):
if self.val.type.strip_typedef... |
6b3019cfcf0b15afc68557ab615dea06f416e8e1d366290b3a7b327de5e8156b | Python | 1,203 | 49 | import sys
_atom=[]
_posit=[]
for rl in open(sys.argv[1],'r'):
_atom.append(int(rl[6:11]))
_x=float(rl[30:38])
_y=float(rl[38:46])
_z=float(rl[46:54])
_posit.append([_x,_y,_z])
print('[ moleculetype ]')
print('; Name Exclusions')
print('Protein_DON 1')
print('\n')
print("[ atoms ]")
# ... |
dc24bd15df6628f18a1d670c7a2fab2bfc231f63f8efaf95f2c05ccbf9506d2e | Python | 1,203 | 32 | #!/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... |
a1aea9031eb78be5a17b1a2dafe5c86086df95fb2284bbb617a84bf42e599723 | Python | 1,204 | 30 | #!/usr/bin/env python3
import pandas as pd
import argparse
import os
import gzip
parser = argparse.ArgumentParser(description='Combine significant pairs from multiple eQTL mapping runs.')
parser.add_argument('signifpair_list_file', help="File listing of 'signifpairs' outputs from eQTL pipeline.")
parser.add_argument('... |
ad3929d46f69dd8904430809cde892a2519a60370458d965e9cef4c8f2a3eb6a | Python | 1,204 | 22 | """Tests for the extractor mask and connected-component numbering (numpy only)."""
import numpy as np
from surface_morphometrics import extract_patches as ep
from surface_morphometrics import label_connected_components as lcc
def test_mask_from_property():
v = np.array([1.0, 5.0, np.nan, 30.0, 31.0, 0.0])
as... |
c0fe6f7a521520601d7031872fff8d76f965c151e1928febf56e6825dae2d7b1 | Python | 1,204 | 62 | #!/usr/bin/env python3
from dataclasses import dataclass
from scipy.integrate import solve_ivp
import numpy as np
@dataclass
class Params:
# coupling
w_ee: float = 12
w_ei: float = 10
w_ie: float = 15
w_ii: float = 0
# input
P: float = 1.25
Q: float = 0
# decay
tau_e: float = ... |
f1d1c8be5bad2dd010d0e1887480469d986cc3e41a409e7851e114628d81b1bb | Python | 1,205 | 42 | import scipy as s
from .basic_distributions import Distribution
from mofapy2.core.utils import *
class Bernoulli(Distribution):
"""
Class to define Bernoulli distributions
Equations:
"""
def __init__(self, dim, theta, E=None):
Distribution.__init__(self, dim)
# Initialise parame... |
2abe4cb0dbd0a05960ed770b4808edf20a268450cde97e8435d37505f6f7dcb6 | Python | 1,206 | 48 | # -*- coding: utf-8 -*-
# python standard library inputs
import os
import sys
import subprocess
# local inputs
from ..io.get_filename import get_filename
def upsample_surf_mesh(file_in, file_out, n_iter, method):
"""Upsample surf mesh.
The scripts takes generated FreeSurfer surfaces and upsamples them ... |
58dee11626abcd44725d52a7b98f97098c56ee3f481ca0afd77fdc0d89a8e1ad | Python | 1,207 | 42 | import pandas as pd
import numpy as np
import os
from pcafeat import select_ttest_features
np.random.seed(42)
n_samples = 100
n_features = 1000
df_X_train = pd.DataFrame(np.random.randn(n_samples, n_features))
df_X_train.columns = [f'feature_{i}' for i in range(n_features)]
df_X_train.iloc[:50, :10] += 0.5
df_X_trai... |
c2aa6231ae0a5e014ae4ebdb722f0b185baf1dc6451d078620c7b03efcbe6dee | Python | 1,207 | 43 | """Calculate summary statistics.
"""
from sys import argv
if len(argv) != 3:
print("Please pass the number of modes and run id, e.g. python 5_calc_summary_stats.py 6 1")
exit()
n_modes = int(argv[1])
run = int(argv[2])
#%% Import packages
print("Importing packages")
import os
import pickle
import numpy as ... |
fb6710eea1d78a36397ee9b7791e006f1aa88d7b9f1f4720957ae0779ea0f0f4 | Python | 1,207 | 42 | # 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.
import numpy as np
from . import BaseWrapperDataset, data_utils
class SortDataset(BaseWrapperDataset):
d... |
0dffdbc60c840443d80a8757e5f084e25c5a201134b934494fd959bf8d6ff75a | Python | 1,208 | 45 | # imagecodecs/tests/conftest.py
"""Pytest configuration."""
from __future__ import annotations
import glob
import os
import pathlib
import sys
from typing import Any
DATA_PATH = pathlib.Path(os.path.dirname(__file__)) / 'data'
if os.environ.get('VSCODE_CWD'):
# work around pytest not using PYTHONPATH in VSCode... |
64a03f7eb6a88136e5a50254973c7e0baebf8075fec9860e27d157bf7050a8ab | Python | 1,208 | 38 | # ruff: disable=F401
import click
from _cli import LazyGroup
@click.group(
cls=LazyGroup,
lazy_subcommands={
"mixed-t1map": "gmri2fem.mixed_t1map.mixed_t1map",
"looklocker-t1map": "gmri2fem.looklocker_t1map.looklocker_t1map",
"hybrid-t1map": "gmri2fem.hybrid_t1map.hybrid_t1map",
... |
793a0bdf22f93d1fade4c35bf139d0b6221d2d23dccfc4ef504612b2cc9b795f | Python | 1,208 | 42 | """Merge all the Therapeutics Data Commons (TDC) ADMET datasets into a single dataset."""
from functools import reduce
from pathlib import Path
import pandas as pd
from tqdm import tqdm
from tdc_constants import ADMET_ALL_SMILES_COLUMN
def merge_tdc_admet_all(data_dir: Path, save_path: Path) -> None:
"""Merge ... |
263ece7118988c71fe7b5d381f8c538238d1e56e9a3c1e260519dd6da48f9a05 | Python | 1,209 | 41 | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from .ai_gym import AIGym
from .analytics import Analytics
from .distance_calculation import DistanceCalculation
from .heatmap import Heatmap
from .instance_segmentation import InstanceSegmentation
from .object_blurrer import ObjectBlurrer
from .objec... |
36f26f2b033017ae57e373b5c62f41e42d63b35f2a026aed9f83f7fc5cf30d60 | Python | 1,209 | 38 | #!/usr/bin/env python3
"""Run inference for one preprocessed 3D volume."""
from __future__ import annotations
import argparse
from pathlib import Path
import numpy as np
try:
from .apis.inference import run_inference
except ImportError:
from apis.inference import run_inference
def parse_args() -> argparse.... |
f91e6296ec0ccec99eee7572d978e1ad95f62873956ff8fc52efc6106c49e3ef | Python | 1,209 | 20 | import torch
def lr_scheduler(scheduler, optimizer, ReduceLROnPlateau_factor = 0.1, ReduceLROnPlateau_patience = 5):
if scheduler =="scheduler_LambdaLR":
lr_scheduler = torch.optim.lr_scheduler.LambdaLR(optimizer,
lr_lambda=lambda epoch: L... |
0df8fa11051fc92eb989a27d99aff0e73deee4c4163f19d55a1c58a500692e12 | Python | 1,210 | 25 | # -*- coding: utf-8 -*-
"""
ClearMap analysis and statistics toolbox.
This part of ClearMap provides a toolbox for the statistical analysis and
visualization of detected cells or structures and region specific analysis
of annotated data.
For cleared mouse brains aligned to the Allen brain atlas, a wide range of
sta... |
128df1d38156a676955d673a3a3e52a6199f3330f7c4f1ba2556246dccae1b19 | Python | 1,210 | 38 | #!/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... |
5e4d8cc03c2ad30e21074b3175ae055a78f7eec9c2e7e07e833f59c75c00c662 | Python | 1,210 | 47 | from typing import ClassVar, Literal
from argclz import argument
from .cli_suite2p import Suite2pOptions
from .cli_treadmill import TreadmillOptions
__all__ = ['ShuffleBaseOptions',
'PositionShuffleOptions',
'SHUFFLE_METHOD']
SHUFFLE_METHOD = Literal['cyclic', 'random']
class ShuffleBaseOptio... |
866c5012c7e02036d9bdd06b876f0e4c0a9b0072ebb2a3d6d8aa5b248bbdbe03 | Python | 1,210 | 58 | #!/usr/bin/env python
"""
Application to convert AXT file to FASTA file. Reads an AXT file from standard
input and writes a FASTA file to standard out.
usage: %prog < axt_file > fasta_file
"""
__author__ = "Bob Harris (rsharris@bx.psu.edu)"
import sys
import bx.align.axt
def usage(s=None):
message = """
axt_t... |
bb20d33559f131f058e30f4fb9b54babb41f011988f939a51899d66038ce46e4 | Python | 1,210 | 18 | from testsetclass import TestsetClass
class ALK8(TestsetClass):
def __init__(self):
self.weak = 1.0
self.molecules = ['li3_me', 'na2', 'na+', 'li_h', 'li_me', 'li4_me4', 'na8', 'na2_h2', 'li4_c', 'li8', 'li2', 'li5_ch', 'li_ch2n', 'li_na_h2', 'li2_ch2n_2', 'li2_ch4', 'li+']
self.exp_values... |
f98786f801eaec9835fb89b69a32e072f0aa030e2cf363b9da1763f8c4c2afd9 | Python | 1,210 | 46 | #!/usr/bin/env python
"""
Tool for adding a column to a table. Expressions for the column are similar
to those supported by table_filter.py
usage: %prog expression colname < table
-H, --header: keep header in output
-C, --comments: keep comments in output
"""
import sys
import bx.tabular.io
from bx.cook... |
52c0fa9fb4265d36d687db785f39b63233e1193568dfa56d76c178b3e2b729bf | Python | 1,211 | 43 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
import io
from collections.abc import Callable
from contextlib import closing
from typing import ClassVar
import attrs
from PIL import Image
from shared.tasks.base import TaskSpecBase
from shared.tasks.enums import SourceDataType
from shared.utils.... |
70f8bdeceffa0293c65981cc43821b1ee0f6ec863cb5462927774eb2acb1fabe | Python | 1,211 | 37 | from ._ai_assisted_annotation_widget import AiAssistedAnnotationWidget
from ._ai_text_to_annotation_widget import AiTextToAnnotationWidget
from ._brightness_contrast_dialog import BrightnessContrastDialog
from ._canvas import Canvas
from ._empty_state import EmptyStateWidget
from ._label_dialog import LabelDialog
from ... |
d5e8c882c29c4106a4d22ee5f505aea2841ab5d2f95a28818d782ee015ba4b9b | Python | 1,211 | 36 | import torch
from torch import Tensor
import torch.nn as nn
class ConcatConv3D(nn.Module):
def __init__(self, in_channels: int, out_channels: int):
super(ConcatConv3D, self).__init__()
self._in_channels = in_channels
self._out_channels = out_channels
self.conv = nn.Conv3d(in_chann... |
26ebb01eeadbfb9b85d22ceddc0846cc5ea01a99d75e75c827d8cccdd7886306 | Python | 1,212 | 39 | import numpy as np
from gensim.parsing.preprocessing import preprocess_string,strip_non_alphanum,preprocess_documents
from tqdm import tqdm
from gensim.models import KeyedVectors
import torch
from torch.nn.utils.rnn import pad_sequence
import argparse
parser = argparse.ArgumentParser()
parser.add_argument('dataset', ty... |
a1ac156e70dc3373620ee640f47c8e4fc1f4d8a0d015df0985b4693a948c915d | Python | 1,212 | 29 | from tests.utils import pytest_importorskip
def test_qt3dinput():
"""Test the qtpy.Qt3DInput namespace"""
Qt3DInput = pytest_importorskip("qtpy.Qt3DInput")
assert Qt3DInput.QAxisAccumulator is not None
assert Qt3DInput.QInputSettings is not None
assert Qt3DInput.QAnalogAxisInput is not None
a... |
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