sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
176ac43de51f99faad2862040ea01edf9d89783136229910a33c0dabb96326ca | Python | 14,748 | 262 | # .\comet.win64.exe C:\Users\animeshs\HeLaReps\230301_hela_Slot1-54_1_3894.d\230301_hela_Slot1-54_1_3894_6.0.313.mgf
# import sys
from pathlib import Path
#pathFiles = Path("C:/Users/animeshs/HeLaReps/230301_hela_Slot1-54_1_3894.d")
pathFiles = Path("C:/Users/animeshs/HeLaReps")
fileName='*txt'
uniprotID='DECOY_'
xCor... |
26dc380b7588a747726034262dcb5819dbaa6228ecb44d8d5526b09115b1233d | Python | 14,763 | 352 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
import os
import pathlib
import openmm
import pooch
import pytest
from gufe import SmallMoleculeComponent
from openff.units import unit
from openmmtools.states import ThermodynamicState
fr... |
7322c81db31230ac4b56c6885d633af11a73c4570b4f141f2eda0cf28c1e62e1 | Python | 14,765 | 355 | #!/usr/bin/env python
#
# Copyright (c) 2017 10X Genomics, Inc. All rights reserved.
#
from __future__ import annotations
import os.path
import re
from collections.abc import Sequence
from typing import TYPE_CHECKING
import h5py as h5
import numpy as np
import cellranger.analysis.clustering as cr_clustering
import ... |
4cf1c5e0bb225dd64cfaf2e2a50aea56c53f4e9d793d89dbc2b0b9d1181cd25b | Python | 14,779 | 404 | #!/usr/bin/env python3
"""
WSI Inference Pipeline
Performs sliding-window segmentation of Bielschowsky-stained WSI numpy arrays to
predict axon masks. The input is a single full-resolution numpy array
(wsi_clahe_enhanced.npy) rather than individual tiles; inference runs in horizontal
strips to keep peak RAM manageable... |
c39d094bd3c46577e6e6617a212b84520307e4218a13aabcbc9c0646deab66e0 | Python | 14,799 | 374 | # ############################################################################
# # Copyright (c) 2022-2026 University of Helsinki
# # Copyright (c) 2019-2022 Saint Petersburg State University
# # # All Rights Reserved
# # See file LICENSE for details.
# ##################################################################... |
1aae58cefb71df3d19ece885b611284abd87a984468026bb3cf93832483a33bb | Python | 14,803 | 395 | import torch
import torch.nn as nn
import pandas as pd
import torch.nn.functional as F
from .meta.electrode_names import channels
class LogWaveletCWT(nn.Module):
def __init__(
self, scales, wavelet="morl", eps=1e-8, mean_normalize=False, bin_size=None
):
super().__init__()
self.scales ... |
7be5ae7eb9b7206c2f7dc6d1201cfc21f75d95f2daa18956cab30a1acb6ca4f1 | Python | 14,826 | 348 | # Copyright (c) Facebook, Inc. and its affiliates.
from typing import Callable, Dict, List, Optional, Tuple, Union
import fvcore.nn.weight_init as weight_init
import torch
from torch import nn
from torch.nn import functional as F
from detectron2.config import configurable
from detectron2.layers import ASPP, Conv2d, De... |
256975fcb57e7dc4f67b18cfe3c68fd15fd8e354afc9aa7ec8a5fc83e5c2e8ce | Python | 14,848 | 535 | """Tests for experimental datasets."""
import numpy as np
import pytest
from mesa import Agent, Model
from mesa.experimental.data_collection import (
AgentDataSet,
DataRegistry,
ModelDataSet,
NumpyAgentDataSet,
TableDataSet,
)
from mesa.experimental.data_collection.dataset import DataSet
def tes... |
0a577ba0f570ffe5be5de7a393006afbaabb00ba57f393eb7eebd5d65e5a5c07 | Python | 14,891 | 286 | import timeit
import argparse
import numpy as np
import pandas as pd
import torch.optim as optim
import torch
import torch.nn as nn
import torch.nn.functional as fn
from data_preprocess import *
from Metapath_Augmentation.path_aug_model import Metapath_Augmentation
from Structural_Augmentation.struc_aug import Structur... |
86261ee59082ce0721a140b68a3700ad4dd097d1de10ec40b6949f04d2d8d449 | Python | 14,894 | 283 | """大脳皮質‐基底核回路ネットワーククラス"""
from Neuron import LIFmodel
from Input import PoissonNeuron
from myfunc0829 import GetSynapsepath
import numpy as np
from numpy import dot
import pickle
from concurrent.futures import ThreadPoolExecutor
import os
rng = np.random.default_rng()
def parallel_matrix_multiplication(ma... |
ff555042dce965d9857189dbd5bb546abea75d4ce618028133a9bd086d9caf03 | Python | 14,912 | 391 | #!/usr/bin/env python3
#
# Copyright (c) 2017 10x Genomics, Inc. All rights reserved.
#
# TODO(Spatial team): This stage is no longer used by Count AGGR/Reanalyze at all, and
# parse_aggr_csv.rs is used instead.
# It's currently only used in Spatial Aggr, so we should extend parse_aggr_csv.rs
# to handle Spatial Aggr ... |
6d30916ec45a3bc47f7abd55e2b66fe86c6020a0fc0965e525fbc70d07c7470e | Python | 14,916 | 383 | #!/usr/bin/env python
#
# Copyright (c) 2024 10X Genomics, Inc. All rights reserved.
#
"""Functions for calling cell-associated barcodes."""
from __future__ import annotations
from typing import TYPE_CHECKING, NamedTuple
import numpy as np
import numpy.ma as ma
from cellranger.analysis.diffexp import adjust_pvalue... |
e06b3598cd44b483e191fcdbc00c44e213cebd1d962b96b7b1325a3ee9c106c6 | Python | 14,924 | 283 | """大脳皮質‐基底核回路ネットワーククラス"""
from Neuron import LIFmodel
from Input import PoissonNeuron
from myfunc0829 import GetSynapsepath
import numpy as np
from numpy import dot
import pickle
from concurrent.futures import ThreadPoolExecutor
import os
rng = np.random.default_rng()
def parallel_matrix_multiplication(ma... |
227a753c30317fc26a1ed8fe987f0d5b05ba9edbff83eeda9b0102dcf13dbdaa | Python | 14,984 | 420 | # -*- coding: utf-8 -*-
"""Functions for working with triangle meshes + surfaces."""
from joblib import Parallel, delayed
import numpy as np
from scipy import ndimage, sparse
from neuromaps.images import load_gifti, relabel_gifti, PARCIGNORE
def point_in_triangle(point, triangle, return_pdist=True):
"""
Che... |
31043552a01918ad2d1dc2e8b0696c03b522f2cf48f9a1d65f7f0a0a627b9257 | Python | 14,986 | 380 | # Copyright (c) Facebook, Inc. and its affiliates.
import copy
import itertools
import json
import logging
import os
import pickle
from collections import OrderedDict
import torch
import detectron2.utils.comm as comm
from detectron2.config import CfgNode
from detectron2.data import MetadataCatalog
from detectron2.stru... |
e3f7d5cdaf1d396d110d9f9be97bbd8dbf8f3ad657453962d5cf1dc4c332255d | Python | 14,988 | 366 | #!/usr/bin/env python
# Copyright 2016-2026 Biomedical Imaging Group Rotterdam, Departments of
# Medical Informatics and Radiology, Erasmus MC, Rotterdam, The Netherlands
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obt... |
8b24ac3aacd4e30950932227d4016c4f564425113399d1528d3165efe97f9d0e | Python | 14,989 | 332 | """
apply_warp - Image registration transformation application
Part of the micaflow processing pipeline for neuroimaging data.
This module applies spatial transformations to register images from one space to another
using affine and/or non-linear (warp field) transformations. It's commonly used to:
- Transform... |
ffe5b298f193ef55a73a04ba4a0751b6e5eedec681039e1a63e4f4be74e0a91b | Python | 14,999 | 353 | """
Connectors
==========
<!-- difficulty: intermediate -->
Show where a neuron talks to its partners.
A neuron's *connectors* are its synapses, gap junctions - anything with a position on the neuron and
a `type`. Any neuron that carries a `connectors` table can draw them, whatever its class, and every
backend unders... |
3ffb55f3a1ab857fb1b5806c2033764e67d11c55d89e8cd69fcd184c8d0c0537 | Python | 15,008 | 436 | # This script is part of navis (http://www.github.com/navis-org/navis).
# Copyright (C) 2018 Philipp Schlegel
#
# 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... |
8ed37613559cc2618b01fecbd102112ee45a571f11d9b988e8bc8fa18abbe843 | Python | 15,012 | 388 | from types import SimpleNamespace
import numpy as np
import torch
import stoic_train.lightning_model as lm
from stoic_train.losses import ComplexProductLoss, ResidueWeightFocalLoss, SparsityLoss
from stoic_train.lightning_model import StoichiometryModelLightning
class DummyStoic(torch.nn.Module):
def __init__(
... |
ebe171edca7fe53b84bcf34ce73d8b6478eb191ef27c65af7ebd2f2695c455ce | Python | 15,050 | 418 | #!/usr/bin/env python3
"""
===============================================================================
create_pyg_dataset.py — Build PyTorch Geometric datasets from enzyme structures
===============================================================================
• Reads training/test CSVs (with columns incl. `unip... |
d6f9e9780eeec4df98cd75534f9214b2869bea3869c6779e36a13391d87a356c | Python | 15,070 | 336 | #!/usr/bin/env python
# Copyright 2016-2026 Biomedical Imaging Group Rotterdam, Departments of
# Medical Informatics and Radiology, Erasmus MC, Rotterdam, The Netherlands
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obt... |
e43aff325714a9921ca013b26d078e6353683c6af280bd5afec0f762b22d1d1c | Python | 15,071 | 392 | import os
import sys
import csv
import argparse
import itertools
import pandas as pd
import numpy as np
import importlib
import rootutils
import torch
from torch import Tensor
from copy import deepcopy
from lightning import seed_everything
from tqdm import tqdm
from types import SimpleNamespace
from typing import List
... |
abf60916cf832aff7096a722ac45a43ce3d783b0013bb40e209bc9ba729cf350 | Python | 15,076 | 408 | #https://towardsdatascience.com/how-to-download-and-visualize-your-twitter-network-f009dbbf107b
keyz = {k:v for k, v in (l.split('=') for l in open("F:/GD/scripts/keyz"))}
#C:\\Users\\animeshs\\AppData\\Local\\Programs\\Spyder\\Python\\python.exe -m pip install tweepy
#add long BEARER_TOKEN from https://developer.twitt... |
fddb1e8b373053814e25c571d950bd37efc85ad19ae0d26f6a073e9668a277bc | Python | 15,090 | 376 | # This script is part of navis (http://www.github.com/navis-org/navis).
# Copyright (C) 2018 Philipp Schlegel
#
# 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... |
92f57b8d4d7504d54c22eca876720f6661873f69e31b12cbfadd20dd444bf6c2 | Python | 15,093 | 418 | """Internal utilities for snakemake template."""
from __future__ import annotations
import string
from collections.abc import Iterator, Mapping, Sequence
from typing import TYPE_CHECKING, Any, Final, overload
import attrs
from typing_extensions import LiteralString, override
@attrs.define(frozen=True)
class _Wildc... |
c3959da96f4ee1bc1ef87e9e3eaf6f181a9ed5ce797b87b8f76322cd21ba5e6b | Python | 15,099 | 369 | # Copyright (c) Facebook, Inc. and its affiliates.
import math
from typing import List, Tuple, Union
import torch
from fvcore.nn import giou_loss, smooth_l1_loss
from torch.nn import functional as F
from detectron2.layers import cat, ciou_loss, diou_loss
from detectron2.structures import Boxes
# Value for clamping la... |
91639ef79e8308f8b41b1f3ddeb9f6c936a1933b493a9de8cfb3cd4bcf8dbe8d | Python | 15,103 | 463 | """ Created on Tue Sep 23 13:12:00 2025
@author: dcupolillo """
from __future__ import annotations
import numpy as np
import pyabf
from scipy.optimize import curve_fit
from ipfx.feature_extractor import SpikeFeatureExtractor
def ohm_law(
voltage: float | None = None,
resistance: float | None = No... |
e77dfbf42e6bec9729ac7d3269aa0114de758d06b4089d81b0663cfc4768b972 | Python | 15,105 | 378 | """Tests for `navis.downsample_neuron` on skeletons.
The focus is on what downsampling has to keep intact besides the node table:
connectors and tags refer to nodes by ID, and most of those nodes disappear.
"""
import navis
import numpy as np
import pandas as pd
import pytest
# The methods that thin a skeleton by *... |
93afadf7b69762b78b9c3ee839b4d83086dbf8bb0034fef7a881738ef5bc02fc | Python | 15,118 | 443 | """ Utility functions """
__author__ = "Fabi Bongratz"
__email__ = "fabi.bongratz@gmail.com"
import os
import warnings
import collections.abc
from copy import deepcopy
from enum import Enum
import numpy as np
import nibabel as nib
import torch
import torch.nn.functional as F
from trimesh import Trimesh
from skimage ... |
a015767476208d83ecbd90eedd057989a9a350aa61dc200c2e4ba26e97f324d1 | Python | 15,122 | 367 | import torch
from torch_geometric.nn import knn_graph, radius_graph
import numpy as np
from scipy.sparse import csr_matrix
from scipy.sparse.csgraph import connected_components
from Bio.PDB.MMCIFParser import MMCIFParser
from e3nn.o3 import spherical_harmonics
from constants import ALL_LABELS_BACKBONE, ALL_ATOM_LABELS... |
5c24b7593e2d8d387b7dfd5ccc6ab75c350db8b4f88fe1efe5969d58a10238fa | Python | 15,139 | 368 | from abc import ABC, abstractmethod
import numpy as np
import torch
from torch import Tensor
from torchmetrics.regression import SpearmanCorrCoef
from chemprop.utils.registry import ClassRegistry
UncertaintyEvaluatorRegistry = ClassRegistry()
class RegressionEvaluator(ABC):
"""Evaluates the quality of uncertai... |
e381d6adc7dc3b31e49315d7edaf6bb39c4ec105a1cf24b9bb32636083350af0 | Python | 15,144 | 379 | """
ICMS83 DataLoader adapter.
Produces the same trial_df and recording as the standard DataLoader
but handles ICMS83's unique data layout:
- Key files at S:/ICMS83/Keys/{date}/Ch{intan}_D{depth}_H{H}M{M}.mat
with dataCellArr format (N x 1 cell, each entry 8 x 1):
[0] stimLevel (µA) [1] respon... |
d94c1949c3e10d45b6c4deb241009da245b2a71ab4d86f943ae8ac0640d75e9b | Python | 15,150 | 315 | import torch
import torch.nn as nn
import torch.nn.functional as F
from taming.modules.losses.lpips import LPIPS
from taming.modules.discriminator.model import NLayerDiscriminator, NLayerDiscriminator3D, weights_init
class DummyLoss(nn.Module):
def __init__(self):
super().__init__()
def adopt_weight(we... |
d258a4f1b442f40b3f7d005f690a5cdca3f2fee6b012e6182e86d0be97dbb40d | Python | 15,156 | 403 | import os
import re
from itertools import product
from bids.layout import BIDSLayout
def read_bids_dataset(bids_input, subject_list=None, session_list=None, collect_on_subject=False):
"""
extracts and organizes relevant metadata from a bids dataset necessary
for the dcan-modified hcp fmri processing pip... |
7b03dc455cf24566688752f7e5a4661643e6ec8c5f93fa61fcba3a9d1d7a89be | Python | 15,166 | 341 | from __future__ import annotations
import warnings
from copy import deepcopy
from functools import lru_cache, partial
from typing import Union, Tuple, List, Type, Callable
import numpy as np
import torch
from nnunetv2.preprocessing.resampling.utils import recursive_find_resampling_fn_by_name
import nnunetv2
from ba... |
f44b0d621ec3debcd8b2b16a065dd0baf55a8adb5dc3ba28296ac6aec87d6198 | Python | 15,171 | 416 | """
Behavioural Statistical Analysis — P1 (Control vs PTSD)
Boxplot + jitter, ggplot2 style. Separate figures for OF, EPM, DLB.
Statistical pipeline:
1. Outlier removal — IQR 1.5×
2. Normality — Shapiro-Wilk per group
3. Two-group test — t-test (if both normal) or Mann-Whitney U (if any non-normal)
4.... |
7b2e7ac709ce068bb374fdbb4b7d23d56a7e08152247d9f43d19c20938536db4 | Python | 15,180 | 417 | """ Configuration management for SpineDataset
Created on January 21, 2026
@author: dcupolillo """
from __future__ import annotations
from pathlib import Path
import yaml
import tensorflow as tf
class SpineDatasetConfig:
"""
Manages configuration loading and parameter validation for spine analysis.
... |
2bbd05a40d085a7d81653029afa0c96cef19c4275c3f8426e226a1c09a23cebc | Python | 15,198 | 426 | #!/usr/bin/python3
##################################################################################
#
# MIT License
#
# Copyright (c) 2025 Kevin Rockenbach, Agnieszka Golicz
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "So... |
4c0f6a847d5709f5b306000e017725d384ea66b3034b96da4f2da3000711d414 | Python | 15,220 | 273 | import unittest
from collections import OrderedDict
from copy import deepcopy
import numpy as np
from batchgenerators.augmentations.utils import resize_segmentation
from scipy.ndimage import map_coordinates
from skimage.transform import resize
from nnunetv2.preprocessing.resampling.default_resampling import resample_... |
45b709a3442f5f8767f248f552a87812bef806f23a99e3e83e2a0a2f29af6027 | Python | 15,260 | 344 | """
bet - Brain Extraction Tool
Part of the micaflow processing pipeline for neuroimaging data.
This module provides brain extraction (skull stripping) functionality using either:
1. SynthSeg-generated parcellations to create brain masks
2. User-provided binary masks
It accurately segments the brain from su... |
c46682a3b7d0abb9e225109e0154d0d45873ca60fb4a0993d4a448358955035c | Python | 15,289 | 354 | """
Plotting Overview
=================
<!-- difficulty: beginner -->
Which plotting mode and which backend to reach for, and how they compare.
{{ navis }} draws neurons two ways: **static 2D figures** via [`matplotlib`](http://www.matplotlib.org),
and **interactive 3D scenes** via [`octarine`](https://schlegelp.gith... |
4dc82f2d8c035a8ef9f0f917a8b8bdeb384a12f3b90fe112985e82bcf69bae51 | Python | 15,336 | 409 | # Copyright (c) 2020 10X Genomics, Inc. All rights reserved.
"""Code for simulating and fitting data from a Joint Inference By Exploiting Stoichiometry model.
The model assumes that for a given number of labeled cells going through a GEM Well, we have a
poisson based expectation around the number of k-lets (1,2,3,etc.... |
379204eb6ef4580a6eb321ee694c6e266acdb8f40449e1dec3bfd5447634f6cc | Python | 15,345 | 411 | from __future__ import annotations
import argparse
import copy
import functools as ft
import itertools as it
import re
from pathlib import Path
from typing import Any, ClassVar
import pytest
from hypothesis import given
from hypothesis import strategies as st
import tests.strategies as sb_st
from snakebids.plugins.c... |
fa005b2e089010f03f419a104938cd5a10d148f5cd43852e25bb281d91405b42 | Python | 15,363 | 357 | ############################################################################
# Copyright (c) 2025-2026 University of Helsinki
# All Rights Reserved
# See file LICENSE for details.
############################################################################
"""Tests for output format improvements:
- ReadInfoPrinter (re... |
0b3770b2c9053499bf48865c7c270ada567056a0411f5d2bbf9de0cad11b0cd5 | Python | 15,368 | 305 | """
If you use this code, please cite one of the SynthSeg papers:
https://github.com/BBillot/SynthSeg/blob/master/bibtex.bib
Copyright 2020 Benjamin Billot
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 Lice... |
dced0cef4c09ac8f1b79b7038224c951a23b2b0f2ca80214f9fa16f5b608827d | Python | 15,369 | 429 | """
Run UnitMatch on all animals (ICMS83 + experimental).
Generates:
- Per-animal unitmatch results (probability matrix, UIDs, tracks)
- Combined tracking summary across all animals
Usage:
python -m batch_process.postprocessing.run_unitmatch
python -m batch_process.postprocessing.run_unitmatch ICMS92
"""
impo... |
a8f9740f4020577764c7189c07c1a677228142194f8e99227924c67d6147d022 | Python | 15,378 | 476 | """Test the backends of the visualization package."""
import random
import types
from typing import ClassVar
from unittest.mock import MagicMock
import numpy as np
import pytest
from mesa import Model
from mesa.discrete_space.grid import OrthogonalMooreGrid
from mesa.experimental.continuous_space import ContinuousSp... |
fce72fa2f81e0d5a126d72e08dbcc9e08a467233ea3a54e8c35d1ad3ff21b03a | Python | 15,407 | 349 | import os
import random
import shutil
from pathlib import Path
from typing import List, Tuple, Optional, Callable
import cv2
import numpy as np
import tifffile
import torch
from albumentations import (
Blur, GaussNoise, ShotNoise,
RandomBrightnessContrast, Compose, RandomScale, RandomCrop, PadIfNeeded)
from sc... |
1382cf91d289d8c3e27c85a0a0e0dcfac386f28e4d2987d712fa591a524fe6f2 | Python | 15,441 | 392 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
axon_directionality.py – Grid-based axon orientation analysis of WSI masks.
For each spatial resolution defined in axon_density.RESOLUTION_CONFIGS, divides
the binary axon mask (wsi_axon_mask.npy) into a grid of square cells and computes
structure-tensor orientation... |
040553e1c9d496aa43b7ffc612fa617b4d0da964b097bb346057f8c4202906ad | Python | 15,455 | 436 | # Copyright (c) Facebook, Inc. and its affiliates.
# pyre-unsafe
import contextlib
import io
import logging
import os
from collections import defaultdict
from dataclasses import dataclass
from typing import Any, Dict, Iterable, List, Optional
from fvcore.common.timer import Timer
from detectron2.data import DatasetCa... |
d605bacbf4044059e9082207e25fbce774924da5977381cb062ef39b5495d087 | Python | 15,463 | 471 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
from pathlib import Path
from typing import Callable, Iterable, Optional, Union
import networkx as nx
from gufe import AtomMapper, SmallMoleculeComponent
from konnektor import network_analy... |
7a450720bd7a0404b35060f1145f83f65109da6515efcdb7b8d155bdf2329596 | Python | 15,473 | 370 | """
Tier-2 prototype: build the tutorial gallery index ourselves.
`mkdocs-gallery` still does all the heavy lifting - it executes every tutorial,
renders the per-tutorial pages, exports the ``.py`` / ``.ipynb`` downloads and
generates the thumbnails. This hook replaces *only* the rendered content of the
gallery landin... |
cedb98fb9dbbe5039f4d82d7be9943de202b5cafb048991d9fb894b713989ba2 | Python | 15,479 | 365 | """
apply_warp - Image registration transformation application
Part of the LAMAReg processing pipeline for neuroimaging data.
This module applies spatial transformations to register images from one space to another
using both affine and non-linear (warp field) transformations. It's commonly used to:
- Transform subje... |
26751fff2ac4d44efee2ba289d5aed9a4ac06d9543a7d6f3a41eadbaf47552f0 | Python | 15,483 | 378 | """
Neuron Collages
===============
<!-- difficulty: intermediate -->
Arrange hundreds of neurons on a single page.
!!! important "This example is not executed"
Like the [light-level skeletonization tutorial](../0_io/zzz_tutorial_io_05_skeletonize), this one is
*not* run when the documentation is built - it p... |
0799471293f7c6c906b98014d13846062e833529ecfb377a8871bf7b602c1d6b | Python | 15,497 | 394 | import os, yaml, pickle, shutil, tarfile, glob
import cv2
import albumentations
import PIL
import numpy as np
import torchvision.transforms.functional as TF
from omegaconf import OmegaConf
from functools import partial
from PIL import Image
from tqdm import tqdm
from torch.utils.data import Dataset, Subset
import tami... |
1bc681d2a9990890c26f9ade6aa82e7792e7552e318bfcf0945ab4137f4f5bc4 | Python | 15,503 | 335 | """Tests for the patch-grid planner and the stitching weights."""
import numpy as np
import pytest
from bio_image_unet.utils import tiling
from bio_image_unet.utils.tiling import (ACTIVATION_BYTES_PER_FILTER, TileBlender,
auto_batch_size, auto_patch_size, available_memory,
... |
3589472e488035fa3110b74b9e9cc4948cfbd5da81df75db42e200cb47f08412 | Python | 15,507 | 370 | #source https://www.bruker.com/protected/en/services/software-downloads/mass-spectrometry/raw-data-access-libraries.html
import sys
if len(sys.argv)!=2: sys.exit("USAGE: python pepCountTTP.py <path to MSn containing directory>, \n e.g.,\npython pepCountTTP.py \"F:/promec/LARS/TIMSTOF/Morten/210902 Morten 1 _Slot1-37... |
5880195daa9c52c0530927fd1c7b4964f35b733d7c3664cdc358ac64337c0375 | Python | 15,508 | 366 | """
If you use this code, please cite one of the SynthSeg papers:
https://github.com/BBillot/SynthSeg/blob/master/bibtex.bib
Copyright 2020 Benjamin Billot
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 Lice... |
5dd745188f8831a705569dd2a181ec6046cae4cbc446d19480df94414a8f26a1 | Python | 15,533 | 381 | import os
import numpy as np
import pandas as pd
import matplotlib
import matplotlib.pyplot as plt
import anndata as ad
import scanpy as sc
from scipy.io import mmwrite, mmread
import seaborn as sns
import scipy
np.random.seed(42)
# load anndata
dir_path = "/home/nomura/Proj/mmvelo/experiments/SHARE-seq_hf/2023-08-0... |
dd3009cdc5f55e0f7413058a852bcd1643888ae4ce495fd011a1c210f39fca7b | Python | 15,536 | 390 | # Copyright (c) Facebook, Inc. and its affiliates.
import collections
import math
from typing import List
import torch
from torch import nn
from detectron2.config import configurable
from detectron2.layers import ShapeSpec, move_device_like
from detectron2.structures import Boxes, RotatedBoxes
from detectron2.utils.re... |
8fce7ef080d200c577d5fef9fd55827dd9c0d33398635eae6f17fb030ec781a6 | Python | 15,568 | 426 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
"""
Generic tools for plotting networks. Interfaces NetworkX and matplotlib.
Create subclasses of ``Node``, ``Edge``, and ``GraphDrawing`` to customize
behavior how the graph is visualized ... |
15698ed51443be85d3cb378fd4032792b3f8ecef162dc6b75b367033e0772d01 | Python | 15,641 | 515 | """_summary_
Utility functions for EEG visual classification project."""
import glob
import os
import argparse
from pathlib import Path
from datetime import datetime
import platform
import random
import hashlib
import torch
from torch.utils.data import DataLoader
import numpy as np
import pandas as pd
import matplotl... |
a0643bb7ddadd4932c73bfa4581f3e7e36f8a3e80651b08e9a2fef895b01b949 | Python | 15,645 | 344 | """Tests for `navis.ml.sample_cable` and `navis.ml.sample_surface`."""
import navis
import numpy as np
import pandas as pd
import pytest
# --------------------------------------------------------------------------- #
# Builders for controlled geometry
# ---------------------------------------------------------------... |
7edaec5d4f1c9b0c908c21fc91f23b96d96856626dcc82b70b5f616fe66b7db7 | Python | 15,648 | 352 | import os, math
import torch
import torch.nn.functional as F
import pytorch_lightning as pl
from main import instantiate_from_config
from taming.modules.util import SOSProvider
def disabled_train(self, mode=True):
"""Overwrite model.train with this function to make sure train/eval mode
does not change anymor... |
2250a710be99633f33c7e2ab838789129fa7477ada3ddcce7b7461e0641d53e8 | Python | 15,659 | 324 | #!/usr/bin/env python3
"""Validate a portable RAVEN source release and its optional Zenodo payload.
The default check deliberately accepts a clean GitHub clone with no checkpoints,
experiment logs, downloaded VGG16 cache, or generated HDF5 datasets. Add
``--verify-checkpoints`` after extracting the Zenodo archive to ... |
b4d9076af52e066cbe1d905da552a5ad855e136fdaf792acd271b1c47457fbc4 | Python | 15,702 | 395 |
# This script is part of navis (http://www.github.com/navis-org/navis).
# Copyright (C) 2018 Philipp Schlegel
#
# 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 o... |
8201a5ce9b3052583c3582f1bff4fc35324838940832c049aaeceef00428d891 | Python | 15,716 | 381 | ############################################################################
# Copyright (c) 2025-2026 University of Helsinki
# All Rights Reserved
# See file LICENSE for details.
############################################################################
"""Tests for ExonSpliceSiteCounter: region-based exon splice-s... |
9e4ffc6ff327e24118ce7f98181855b70b72c02304dd5c511a007fb8c6092d64 | Python | 15,719 | 460 | #!/usr/bin/env python
#
# Copyright (c) 2020 10X Genomics, Inc. All rights reserved.
#
# Calculate data required for rarefaction and extrapolation curves.
#
"""A stage for calculating clonotype diversity plot from clonotypes.csv.
Classes:
Clonotypes: used to load information from clonotypes.csv for the purpose of... |
c6bb48998493bb74db5bf68affa9bb039508c9576781b22a744bf7ad6a3676c5 | Python | 15,730 | 330 | ############################################################################
# Copyright (c) 2023-2026 University of Helsinki
# # All Rights Reserved
# See file LICENSE for details.
############################################################################
"""
Curio barcode detectors (formerly DoubleBarcodeDetector)... |
323834ccb97317eddfc6b8595636cee3ccd358d8b3fdce695dcd4fb76dee4d53 | Python | 15,757 | 498 | import numpy as np
import pandas as pd
from joblib import Parallel, delayed
from sklearn.metrics import roc_auc_score, r2_score, average_precision_score, \
mean_absolute_error, mean_squared_error, precision_recall_curve, auc
from sklearn.model_selection import RepeatedKFold, cross_val_predict, \
ParameterGrid, ... |
07feac449fcf485be61eb3c49fb225699a27ce0fcedc3e4c2d9d94a2bf0687d3 | Python | 15,771 | 404 | ############################################################################
# Copyright (c) 2022-2026 University of Helsinki
# # All Rights Reserved
# See file LICENSE for details.
############################################################################
"""Unit tests for the polyA / TSS prediction counters.
The ... |
b33ade702e7b4367becc01101a59f1370afc49d755d3c9208959af52e3a9db72 | Python | 15,782 | 448 | """
synthseg - Neural Network-Based Brain MRI Segmentation
Part of the micaflow processing pipeline for neuroimaging data.
This module provides an interface to SynthSeg, a deep learning-based tool for automated
brain MRI segmentation that works across different MRI contrasts without retraining.
SynthSeg segmen... |
bf1d0375d5a082b041cf060ef74f520baccd30b297ea2075cab3426d87e40c98 | Python | 15,798 | 359 | import argparse
import gc
import inspect
import os
from pathlib import Path
from typing import Union, Tuple
import warnings
import nnunetv2
import numpy as np
import torch
from acvl_utils.cropping_and_padding.bounding_boxes import bounding_box_to_slice
from acvl_utils.cropping_and_padding.padding import pad_nd_image
f... |
9d6686ae760d3c3be017e66b79d10e66ea602c1acefb8d855018897b01e9b40d | Python | 15,805 | 551 | #!/usr/bin/env python
"""Run pseudobulk TF-activity inference with decoupler and CollecTRI."""
from __future__ import annotations
import hashlib
import json
from pathlib import Path
from typing import Any
import anndata as ad
import decoupler as dc
import numpy as np
import pandas as pd
from scipy import sparse
fro... |
829ca6740b9b30bf8b565368b42994314fd5a0919f9ca275a80acbfbfd03e256 | Python | 15,807 | 354 | import sys
import mne
import nibabel.freesurfer.mghformat as mgh
import numpy as np
from copy import deepcopy
from toolbox import utils
from numba import jit, float64
## Constant to acces lh and rh in tuple
LEFT_HEMI = 0
RIGHT_HEMI = 1
TRAV_OUT = "TRAV_OUT"
STANDING = "STANDING"
TRAV_IN = "TRAV_IN"
TRA... |
6c300eb7e925f853c4b456ed00bfbc26067d82fd0ba2b0e7e6f6fb7971eb9c80 | Python | 15,810 | 310 | """
If you use this code, please cite the first SynthSeg paper:
https://github.com/BBillot/lab2im/blob/master/bibtex.bib
Copyright 2020 Benjamin Billot
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 ... |
6359cf9a4c8d96c8201629e806906bc544012c93df69d4614a018f4f74253b9f | Python | 15,843 | 440 | """The model class for Mesa framework.
Core Objects: Model
"""
# Postpone annotation evaluation to avoid NameError from forward references (PEP 563). Remove once Python 3.14+ is required.
from __future__ import annotations
import random
import warnings
from collections.abc import Callable, Sequence
from typing impor... |
3a2b7d93f780cdc69f2475890363727fa9335aa54ec830334be63449c4550027 | Python | 15,884 | 311 | import openmm
import openmm.app as app
import openmm.unit as unit
from openff.toolkit.topology import Molecule
from openff.units import unit as ffunit
from openmmforcefields.generators import SMIRNOFFTemplateGenerator
from rdkit import Chem
import pdbfixer
import numpy as np
import h5py
from collections import defaultd... |
516d59aa3d693097cc2ee4958447028f78ce35f989f2c9550e94fc0cd55397f7 | Python | 15,915 | 423 | # noqa: D100
import os
import warnings
from dataclasses import fields
import numpy as np
from matplotlib import pyplot as plt
from matplotlib.cm import ScalarMappable
from matplotlib.collections import PolyCollection
from matplotlib.colors import LinearSegmentedColormap, Normalize, to_rgba
from matplotlib.figure impor... |
7348a8d90c3209af5fa5f9971999e0689350e0432c8068062f35ed335d135668 | Python | 15,922 | 409 | """Tests for the two face readings of mesh connectivity - `connectivity="face"`
and `connectivity="manifold"` - i.e. components of faces joined by shared
*edges* rather than components of vertices joined by shared faces.
Each reading is strictly finer than the one before it, and each drops a kind of
junction. `"face"`... |
603b0de92ee7435503ddb1357ee36edb956bddd5f15d935d61372846f2f588cb | Python | 15,925 | 465 | import argparse
import shutil
import subprocess
import sys
from pathlib import Path
from typing import Iterable, List, Tuple
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
import numpy as np
import torch
SCRIPT_DIR = Path(__file__).resolve().parent
ROOT = SCRIPT_DIR.parent
RINAMI_DIR = ROOT ... |
14c5fefabb61973d1b01a84ac92447ae0dc5eeaf3fe3625a098ad746e6a58b33 | Python | 15,926 | 379 | import os
import time
import csv
import h5py
import numpy as np
import argparse
import matplotlib.pyplot as plt
import pandas as pd
import nibabel as nib
from nibabel import processing as nibp
# ------------------------------------------------------------------------
# 1) Locally define extract_bbox
# ---------------... |
47dffa4e78bb6f474212332b3fc4636036a6e4ec7ab3c4ac6677694f29086672 | Python | 15,926 | 379 | import os
import time
import csv
import h5py
import numpy as np
import argparse
import matplotlib.pyplot as plt
import pandas as pd
import nibabel as nib
from nibabel import processing as nibp
# ------------------------------------------------------------------------
# 1) Locally define extract_bbox
# ---------------... |
91d520c1c43a9179bf651619780d342dee6a5ec96e0312fcdc776d3ff5ae2e58 | Python | 15,928 | 379 | import os
import time
import csv
import h5py
import numpy as np
import argparse
import matplotlib.pyplot as plt
import pandas as pd
import nibabel as nib
from nibabel import processing as nibp
# ------------------------------------------------------------------------
# 1) Locally define extract_bbox
# ---------------... |
d451a4157e18e47bdfae44d166d15a5bdb6741eaa600f9e4fd2073351759903e | Python | 15,930 | 379 | import os
import time
import csv
import h5py
import numpy as np
import argparse
import matplotlib.pyplot as plt
import pandas as pd
import nibabel as nib
from nibabel import processing as nibp
# ------------------------------------------------------------------------
# 1) Locally define extract_bbox
# ---------------... |
3b2b6e055f9edb4c66721f97251f1886b7bf101fc5547b17f65ae90ef9f86ab9 | Python | 15,931 | 378 | import os
import time
import csv
import h5py
import numpy as np
import argparse
import matplotlib.pyplot as plt
import pandas as pd
import nibabel as nib
from nibabel import processing as nibp
# ------------------------------------------------------------------------
# 1) Locally define extract_bbox
# ---------------... |
7afcde5314b76fb70d5ec1eef1827cc24809da101db5b2c99ee01a078e0d80b6 | Python | 15,932 | 379 | import os
import time
import csv
import h5py
import numpy as np
import argparse
import matplotlib.pyplot as plt
import pandas as pd
import nibabel as nib
from nibabel import processing as nibp
# ------------------------------------------------------------------------
# 1) Locally define extract_bbox
# ---------------... |
c578e9f56f652fb9e731e50b21f115f5f639771995b66450634829eaf8c0ad36 | Python | 15,932 | 379 | import os
import time
import csv
import h5py
import numpy as np
import argparse
import matplotlib.pyplot as plt
import pandas as pd
import nibabel as nib
from nibabel import processing as nibp
# ------------------------------------------------------------------------
# 1) Locally define extract_bbox
# ---------------... |
f5e982660215290f274ce9be5b1f2820e71a3142ad3c68a3a1d479775ab571a0 | Python | 15,932 | 385 | """
Created on 10/08/2017
@author: Niklas Pallast, Markus Aswendt
Neuroimaging & Neuroengineering
Department of Neurology
University Hospital Cologne
"""
from __future__ import print_function
import os
import time
import re
import sys
import numpy as np
import nibabel as nib
import nibabel.nifti1 as nii
import pv_... |
8b63e4f641ead459028d2a47ec2ab41b86e6a5bc0d86ff88ca98de94ea84a85d | Python | 15,934 | 377 | import os
import time
import csv
import h5py
import numpy as np
import argparse
import matplotlib.pyplot as plt
import pandas as pd
import nibabel as nib
from nibabel import processing as nibp
# ------------------------------------------------------------------------
# 1) Locally define extract_bbox
# ---------------... |
cc499f5ebe378dda45582110880a8accbaa6249e785bfa4c3f75e174e6eb8038 | Python | 15,934 | 379 | import os
import time
import csv
import h5py
import numpy as np
import argparse
import matplotlib.pyplot as plt
import pandas as pd
import nibabel as nib
from nibabel import processing as nibp
# ------------------------------------------------------------------------
# 1) Locally define extract_bbox
# ---------------... |
5ca46de480d0f5f3f1dfa47fc0a7a50de6c7a2f848e050183ea81a7522582e8f | Python | 15,936 | 379 | import os
import time
import csv
import h5py
import numpy as np
import argparse
import matplotlib.pyplot as plt
import pandas as pd
import nibabel as nib
from nibabel import processing as nibp
# ------------------------------------------------------------------------
# 1) Locally define extract_bbox
# ---------------... |
1dc5040d1f8897f3cdae594d18ba1eb248c646a19fd28c5ab4c748e264b70c65 | Python | 15,940 | 379 | import os
import time
import csv
import h5py
import numpy as np
import argparse
import matplotlib.pyplot as plt
import pandas as pd
import nibabel as nib
from nibabel import processing as nibp
# ------------------------------------------------------------------------
# 1) Locally define extract_bbox
# ---------------... |
a5e3f60259ea651f18fd8c19defb55a39e7635b11634dbefcb071a4c96777027 | Python | 15,940 | 379 | import os
import time
import csv
import h5py
import numpy as np
import argparse
import matplotlib.pyplot as plt
import pandas as pd
import nibabel as nib
from nibabel import processing as nibp
# ------------------------------------------------------------------------
# 1) Locally define extract_bbox
# ---------------... |
cf8694dde7c331e5b9c1af795ebc969c3021775f75e542bc056df87bffd76ea7 | Python | 15,942 | 379 | import os
import time
import csv
import h5py
import numpy as np
import argparse
import matplotlib.pyplot as plt
import pandas as pd
import nibabel as nib
from nibabel import processing as nibp
# ------------------------------------------------------------------------
# 1) Locally define extract_bbox
# ---------------... |
050ae1131a83bdaed0d0673d610326e52680ca2bb558040b0f7481b9749ab2c7 | Python | 15,946 | 379 | import os
import time
import csv
import h5py
import numpy as np
import argparse
import matplotlib.pyplot as plt
import pandas as pd
import nibabel as nib
from nibabel import processing as nibp
# ------------------------------------------------------------------------
# 1) Locally define extract_bbox
# ---------------... |
e0612d16531de0ef0e7a032ca5471a9ffe371cadc37bae912dab296747384efd | Python | 15,946 | 379 | import os
import time
import csv
import h5py
import numpy as np
import argparse
import matplotlib.pyplot as plt
import pandas as pd
import nibabel as nib
from nibabel import processing as nibp
# ------------------------------------------------------------------------
# 1) Locally define extract_bbox
# ---------------... |
969fa0e54e677d688bfe97f4173d040688f935990ab611f0b6fab905772bfc4f | Python | 15,948 | 379 | import os
import time
import csv
import h5py
import numpy as np
import argparse
import matplotlib.pyplot as plt
import pandas as pd
import nibabel as nib
from nibabel import processing as nibp
# ------------------------------------------------------------------------
# 1) Locally define extract_bbox
# ---------------... |
c64b43ad4a8d01a76270ffaefb6263a3438ad78c4a0d63a2e953e2feeecec8e5 | Python | 15,948 | 385 | """
Created on 10/08/2017
@author: Niklas Pallast, Marc Schneider, Markus Aswendt
Neuroimaging & Neuroengineering
Department of Neurology
University Hospital Cologne
"""
from __future__ import print_function
import os
import time
import re
import sys
import numpy as np
import nibabel as nib
import nibabel.nifti1 a... |
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