sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
809fea853828ca08c82cded6e9e00f5a7e029c91bb848b1a3f4b6feeb03cc384 | Python | 825 | 21 | # Copyright 2011-2014 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 obtain a copy of the Licen... |
510e72e596341e48e4668b387583fe38ff50944000baa87bc91e8f22aed08e80 | Python | 828 | 21 | # Copyright 2011-2014 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 obtain a copy of the Licen... |
01de158238f16c719ee8d87c3baae699915afbc34a749e763c00056961a76bce | Python | 829 | 32 | # type: ignore
try:
from snakemake.cli import get_argument_parser, main
from snakemake.common import configfile
from snakemake.common.configfile import load_configfile
except ImportError:
import snakemake.io as configfile
from snakemake import get_argument_parser, main
from snakemake.io import ... |
417c0aca968da9ac04a48165c7a047aa081aa7271e814e3dae2c9e4a9bf1af07 | Python | 829 | 21 | # Copyright 2011-2014 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 obtain a copy of the Licen... |
9423bc94ca06ff3e9a0058e8f6f40e8fd4b40630502c14a95916be13b1015204 | Python | 829 | 29 | from .mask_rcnn_R_50_FPN_100ep_LSJ import (
dataloader,
lr_multiplier,
model,
optimizer,
train,
)
from detectron2.config import LazyCall as L
from detectron2.modeling.backbone import RegNet
from detectron2.modeling.backbone.regnet import SimpleStem, ResBottleneckBlock
# Config source:
# https://git... |
f1587752becd6119d7a580a448cfabfe77cd3d28231403a7302364b742304a29 | Python | 829 | 21 | # Copyright 2011-2014 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 obtain a copy of the Licen... |
44bf2ecb8f2ad6a5ea8f0bedb96328170308c0ce89c6683cf29d4ca734e56b76 | Python | 830 | 22 | # Copyright 2011-2014 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 obtain a copy of the Licen... |
7d92fca35455aee5a4ba0eedecb8aa0fe40beb1fe99868edff6daeff26387742 | Python | 832 | 23 |
import setuptools
with open("README.md", "r") as fh:
long_description = fh.read()
setuptools.setup(
name='lpips',
version='0.1.4',
author="Richard Zhang",
author_email="rizhang@adobe.com",
description="LPIPS Similarity metric",
long_description=long_description,
long_descriptio... |
aab0f414d671bbaf31968d0210078011c0b1478e415984abd600086e97ebf427 | Python | 834 | 21 | # Copyright 2011-2014 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 obtain a copy of the Licen... |
7e1dc2c31bba70ec281d9aa593110202c281fb29dc6eb783cb8964afdbc3afd3 | Python | 835 | 27 | # Copyright (c) Facebook, Inc. and its affiliates.
# pyre-unsafe
from .meshes import builtin
from .build import (
build_detection_test_loader,
build_detection_train_loader,
build_combined_loader,
build_frame_selector,
build_inference_based_loaders,
has_inference_based_loaders,
BootstrapDat... |
b37d7dacf7491fbcab6feaed66cdab5c5b69d1e523c9b98acfb231127acf4563 | Python | 836 | 24 | # Copyright (c) Facebook, Inc. and its affiliates.
from detectron2.utils.registry import Registry
PROPOSAL_GENERATOR_REGISTRY = Registry("PROPOSAL_GENERATOR")
PROPOSAL_GENERATOR_REGISTRY.__doc__ = """
Registry for proposal generator, which produces object proposals from feature maps.
The registered object will be cal... |
0030b29cbf48a7a64ab5e3190bfa19d605b30a681e2e55f2f39a4457a10e27f9 | Python | 837 | 21 | # Copyright 2011-2014 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 obtain a copy of the Licen... |
06154382e2f6f0da6495a1eb27d874ae822c91e9ac643c8c58ca7b92e80cd26b | Python | 837 | 37 | """
Preprocessing module for imaging data.
This module contains functions for image filtering, denoising, and artifact correction.
"""
# Import main filtering functions
from .filters import median, gaussian
# Import denoising functions
from .denoise import (
radius_to_kernel_size,
compute_local_contrast,
... |
ddac56ae9f1926f94aabad95db5352763aeb39012e11d96cf3e8c791ec8a0893 | Python | 838 | 21 | # Copyright 2011-2014 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 obtain a copy of the Licen... |
63f011045059a7125e9aefa0fe8b9755340789e8afda90229d0b9584529e4dfb | Python | 839 | 36 | from .MAB_parsing import build_MAB_data_from_files
from .actions import LookupAction
from .args import activation_function_argument, bounded
from .command import Subcommand
from .parsing import (
build_data_from_files,
get_column_names,
make_datapoints,
make_dataset,
parse_activation,
parse_indi... |
c53044ed870b9481f8d1288badc7e61044524b6371751b221f9feb58e08ff25c | Python | 839 | 21 | # Copyright 2011-2014 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 obtain a copy of the Licen... |
f680b45a095a2da3c86ed5c688af13f0d49e723ab39a735ce9dc6bc14d1dab44 | Python | 839 | 27 | import numpy as np
import sys
x = np.array([0.1, 0.2])
w1 = np.array([[0.15, 0.20], [0.25, 0.3]])
w2 = np.array([[0.4, 0.45], [0.5, 0.55]])
y = np.array([0.2, 0.1])
bias = np.array([0.35, 0.6])
lr = 0.5
iterations = int(sys.argv[1]) if len(sys.argv) > 1 else 1
for iteration in range(iterations):
h =... |
59dfbc19407ec2467ff23d402e5e02f8f7c0442deb10295aa82ad111e9973d28 | Python | 840 | 25 | from setuptools import Command, find_packages, setup
__lib_name__ = "SPIDER"
__lib_version__ = "1.0.1"
__description__ = "SPIDER: Spatially Integrated Denoising via Embedding Regularization with Single Cell Supervision"
__url__ = "https://github.com/compbiolabucf/SPIDER"
__author__ = "MD Istiaq Ansari"
__author_email_... |
8224c102ee39f54ca0be86e9b5741245daffab88724b688ced82647d8c55091a | Python | 840 | 21 | # Copyright 2011-2014 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 obtain a copy of the Licen... |
8da30e93886447e323f7e1cd8fcb1a7c439fb29ee66c7be51ff18029ef3e9aeb | Python | 840 | 21 | # Copyright 2011-2014 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 obtain a copy of the Licen... |
b4ab9c9f5e46c76a963e9490e92c647a36babd6c16feb972f9723becd405bc34 | Python | 841 | 22 | # Copyright 2011-2014 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 obtain a copy of the Licen... |
3a0e02036f97fc97ab0db2ea406e3e24ec814e65b90cc23df36cc798970cbc41 | Python | 843 | 24 | # Python05-2.py
# IJ BAR: https://github.com/tferr/Scripts#scripts
####################################################
# 5.2 Scripting ImageJ: Creating an empty image (II)
####################################################
# Now that we have the documentation opened in our browsers,
# It will be easy to create the ... |
0cf139dcfc2db2e06d7b95ae909556f31f4ae9e2125d0bd2c2d41a28db543545 | Python | 846 | 21 | # Copyright 2011-2014 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 obtain a copy of the ... |
ea55eaa4f7bf94455dc34400fdbf5c4c9dd41de228b3765cbd894959c78f824a | Python | 847 | 36 | #!/usr/bin/env python
#
# Copyright (c) 2019 10X Genomics, Inc. All rights reserved.
#
"""Constants related to BAM file generation."""
# Bam tags
# NUM_HITS_TAG = "NH"
MULTIMAPPER_TAG = "mm"
ANTISENSE_TAG = "AN"
RAW_BARCODE_TAG = "CR"
PROCESSED_BARCODE_TAG = "CB"
RAW_BARCODE_QUAL_TAG = "CY"
RAW_UMI_TAG = "UR"
PROCESS... |
db295046b9c52dc2cbe078c3f904a1c62f41076389398dc00eef406ad154d576 | Python | 848 | 30 | from .mask_rcnn_R_50_FPN_100ep_LSJ import (
dataloader,
lr_multiplier,
model,
optimizer,
train,
)
from detectron2.config import LazyCall as L
from detectron2.modeling.backbone import RegNet
from detectron2.modeling.backbone.regnet import SimpleStem, ResBottleneckBlock
# Config source:
# https://git... |
23506c91b74c9c50e80e8bccaefa52b7ce777af394f98ae9e283c3c8a3938dc1 | Python | 849 | 30 | from functools import partial
from detectron2.modeling.backbone.vit import get_vit_lr_decay_rate
from .mask_rcnn_vitdet_b_100ep import (
dataloader,
lr_multiplier,
model,
train,
optimizer,
)
train.init_checkpoint = (
"detectron2://ImageNetPretrained/MAE/mae_pretrain_vit_huge_p14to16.pth?match... |
be8731d8cd2d540db4ea02f2194ea3b6be5c001ae6c3b4e78048e6e8da1a7412 | Python | 849 | 26 | import numpy as np
from thunderlab.tabledata import TableData
def collect_metadata(models, data):
# extract cell names from model table:
model_data = TableData(models, sep=',')
cells = model_data['cell']
cells = np.unique(cells)
# collect corresponding metadata:
metadata = TableData()
for ... |
475d4903d327df9f2e8bfc8d5198ae33ef65c7fe0363fb4a497b59f259d56cec | Python | 850 | 28 | import argparse
import lpips
parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument('-p0','--path0', type=str, default='./imgs/ex_ref.png')
parser.add_argument('-p1','--path1', type=str, default='./imgs/ex_p0.png')
parser.add_argument('-v','--version', type=str, de... |
8a8369f740edc5b53506810ca72325d6a7cd54d6f6e3cb3d5fac3f91c62c12fa | Python | 851 | 29 | import os
import nighres
from shutil import copyfile
import sys
tmpdir = sys.argv[1]
innerbin = sys.argv[2]
outerbin = sys.argv[3]
output_coords = sys.argv[4]
print("start")
nighres_args = {"save_data": True, "output_dir": tmpdir, "overwrite": True}
## convert binarized edges to levelset surfaces
levelset_inner = n... |
6e031e235c2dff825ca3b85a4e45bf6cee6d91b9bceddc05be0099cb3b18fbf5 | Python | 852 | 23 | from dataclasses import dataclass, field
from rdkit.Chem.rdchem import Atom, Bond
from chemprop.featurizers.atom import MultiHotAtomFeaturizer
from chemprop.featurizers.base import VectorFeaturizer
from chemprop.featurizers.bond import MultiHotBondFeaturizer
@dataclass
class _MolGraphFeaturizerMixin:
atom_featu... |
59b7bfab4903cb8f048988a7ea94d99aed96b3328087031801df5618212f4721 | Python | 853 | 24 | import json
import unittest
from pathlib import Path
REPOSITORY = Path(__file__).resolve().parents[1]
class ClassicalModelSelectionConfigTests(unittest.TestCase):
def test_all_comparison_models_use_five_fold_grid_search(self):
config = json.loads((REPOSITORY / "config" / "analysis_config.json").read_tex... |
94aa5b2b2d54c039a4dbddcf671a1fd9bce30a499b927cc059544e9fc7033d71 | Python | 854 | 30 | import json
import jinja2
from jinja2.ext import Extension
def toml_string(item: str):
"""Encode string for inclusion in toml.
Technically encodes as json, a (mostly) strict subset of toml, with some encoding
fixes
"""
return json.dumps(item, ensure_ascii=False).replace("\x7f", "\\u007f")
def ... |
3175c37892d75693222805195aef46a587a84ad35c9f9be8ed93cbfdc2d07a0c | Python | 855 | 32 | #!/usr/bin/env python
#
# Copyright (c) 2014 10X Genomics, Inc. All rights reserved.
#
"""Utils for math operations."""
from __future__ import annotations
from collections.abc import Iterable
def NX(lengths: Iterable[int], fraction: float) -> int:
"""Calculates the N50 for a given set of lengths."""
length... |
f0b8a153fa2b79b04693903a4250405cd2bade3f810fc1eccdc759684c6f7940 | Python | 857 | 25 | import trimesh
import numpy as np
meshes = [
'avg_template_abdomenct1k_registered/registered_liver.ply',
'avg_template_abdomenct1k_registered/registered_kidney_left.ply',
'avg_template_abdomenct1k_registered/registered_kidney_right.ply',
'avg_template_abdomenct1k_registered/registered_spleen.ply',
... |
b127ab26105d730deef9d34ffc32f1779e612d2ab4b28885eaf91bcdc6d395f7 | Python | 858 | 25 | """
URL configuration for config project.
The `urlpatterns` list routes URLs to views. For more information please see:
https://docs.djangoproject.com/en/4.2/topics/http/urls/
Examples:
Function views
1. Add an import: from my_app import views
2. Add a URL to urlpatterns: path('', views.home, name='home'... |
9b48d113e42ab5a25542f12856440000bf42db23e84306734a56383075607959 | Python | 864 | 19 | # 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... |
0e9a5f0d56eee49e5afb55a8a4a17a0c0de3c62e0aba164fa29ce408cfc3f07c | Python | 865 | 19 | #!/usr/bin/env python
# Copyright 2016-2021 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... |
50ed4281006ee507e066f49fe8188032a1fff486415e8843c7db6e768cbac5c2 | Python | 866 | 20 | import click
from plugcli.params import Option
N_PROTOCOL_REPEATS = Option(
"--n-protocol-repeats",
type=click.INT,
help="Number of independent repeat(s) to be run per execution of a transformation using the ``openfe quickrun`` command.\n\n"
"For example:\n\n ``--n-protocol-repeats=3`` means ``openfe ... |
592fd4a1040adeb5516b6e49bccb5cfd41c6bc02ac7199c7ab786dd5ab191305 | Python | 870 | 29 | import os
from unittest import mock
import pytest
from click.testing import CliRunner
from openfecli.commands.test import test
def mock_func(args):
print(os.environ.get("OFE_SLOW_TESTS"))
@pytest.mark.parametrize("slow", [True, False])
def test_test(slow):
runner = CliRunner()
args = ["--long"] if slo... |
f739844e4f7833ea28a08f3467c0c24f10e0372dfac7dce2841857c2b6185072 | Python | 873 | 31 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
from plugcli.params import NOT_PARSED
from openfecli.utils import import_thing
def import_parameter(import_str: str):
"""Return object from a qualname, or NOT_PARSED if not valid.
... |
27e14d18bd2e133e4a79d80515ac299cd2461dc7841b5e7c755cec44e4465172 | Python | 874 | 26 | # Copyright (c) Facebook, Inc. and its affiliates.
from .batch_norm import FrozenBatchNorm2d, get_norm, NaiveSyncBatchNorm, CycleBatchNormList
from .deform_conv import DeformConv, ModulatedDeformConv
from .mask_ops import paste_masks_in_image
from .nms import batched_nms, batched_nms_rotated, nms, nms_rotated
from .roi... |
8b61f11c22bbf01ff071ea1af5aa9360f34b7b32e7d264cd7d8a6d59610ff4a6 | Python | 874 | 30 | """
Backend wrappers for inference engines.
This module provides unified interfaces for different neural network backends:
- DeepD3: TensorFlow-based spine segmentation
- nnU-Net: PyTorch-based semantic segmentation
- CSBDeep: CARE denoising for image restoration
Each backend runs in an isolated subprocess to avoid d... |
3efbfaa61fed9e8f9bbda3c964b089c10ff4ccea93a79c08115e50857d1bc010 | Python | 879 | 15 | #python diffExprStringify.py "L:\promec\TIMSTOF\LARS\2025\250805_Kamila\DIANNv2p2\report rq.ha..gg_matrix.tsv4118ISNS0.10.50.1BioRemGroups.txt4LFQvsntTestBH.csv" Log2MedianChange PValueMinusLog10
import pandas as pd
import numpy as np
import sys
fileName=sys.argv[1]
#fileName="L:\\promec\\TIMSTOF\\LARS\\2025\\250805_K... |
c823443c832341b3b7d99b314f5c9bf8356189fb33633afa729b07d69f74d427 | Python | 880 | 26 | # -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates.
from detectron2.config import CfgNode as CN
def add_tridentnet_config(cfg):
"""
Add config for tridentnet.
"""
_C = cfg
_C.MODEL.TRIDENT = CN()
# Number of branches for TridentNet.
_C.MODEL.TRIDENT.NUM_BRANCH = 3... |
abdf0e6216b7c6efaf8feb5de443e3d1904d21247ad55a545340e4b8eb7c1993 | Python | 881 | 31 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Jun 1 14:05:26 2022
@author: schmidtfa
"""
#%% imports
from cluster_jobs.head_movement_camcan import MovementJob
from plus_slurm import JobCluster, PermuteArgument
from os import listdir
#% get jobcluster#
job_cluster = JobCluster(required_ram='4G',
... |
a78b3e9b8d4a32319ce56b10375cf6db4b4fd6bc7c250a8887206a393a05b42e | Python | 882 | 25 | # Copyright (c) Facebook, Inc. and its affiliates.
import unittest
from densepose.structures import normalized_coords_transform
class TestStructures(unittest.TestCase):
def test_normalized_coords_transform(self):
bbox = (32, 24, 288, 216)
x0, y0, w, h = bbox
xmin, ymin, xmax, ymax = x0, ... |
09568555345094b0051b6ecab84e1d5ad9ef7f88ba91cfd79696835af2d52dc9 | Python | 890 | 34 | import os
import sys
import anndata as ad
import torch
# 获取当前脚本的绝对路径
current_dir = os.path.dirname(os.path.abspath(__file__))
# 获取父目录（模型定义脚本）的路径
parent_dir = os.path.dirname(current_dir)
if parent_dir not in sys.path:
sys.path.append(parent_dir)
from config import MethyAnnoConfig
from main import *
my_config = M... |
905ab9a7909078f859665b8a7c1f0fd9a551c5950be2a3cf7ac1c4d5bc1053d7 | Python | 890 | 27 | import setuptools
with open("README.md", "r") as f:
long_description = f.read()
setuptools.setup(
name="garnetff",
version="1.0.0",
author="Joe G Greener",
author_email="jgreener@mrc-lmb.cam.ac.uk",
description="Garnet biomolecular force field",
long_description=long_description,
long_... |
4d8e913c6db651bcf83fad63fbb25e4ae62b9abca76aa17b502c766ddfeffc9a | Python | 893 | 27 | # Copyright (c) Facebook, Inc. and its affiliates.
import torch
from detectron2.config import CfgNode
from detectron2.solver import LRScheduler
from detectron2.solver import build_lr_scheduler as build_d2_lr_scheduler
from .lr_scheduler import WarmupPolyLR
def build_lr_scheduler(cfg: CfgNode, optimizer: torch.optim... |
cf1e2468358d91501c3a0844d45dd51233666e497d9c113dd5d876477f1a54f0 | Python | 893 | 40 | import argparse
import sys
from aln_from_csv import aln_from_csv
from calc_distances import calc_distances
def get_args():
parser = argparse.ArgumentParser()
parser.add_argument(
"--input-dir",
"-d",
help="Directory where alignments reside (required).",
required=True,
)
... |
e0a648d7875ae44c17ffb9af200ab0e1dab263c4f29678075db7a6819a243031 | Python | 893 | 22 | from typing import List
from batchgenerators.transforms.abstract_transforms import AbstractTransform
class MaskTransform(AbstractTransform):
def __init__(self, apply_to_channels: List[int], mask_idx_in_seg: int = 0, set_outside_to: int = 0,
data_key: str = "data", seg_key: str = "seg"):
... |
f1854f287caa384a5fc2fd8cfcc206d368163665ea56913f0eed9663d4b517fb | Python | 895 | 26 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates.
import numpy as np
import os
from pathlib import Path
import tqdm
from PIL import Image
def convert(input, output):
img = np.asarray(Image.open(input))
assert img.dtype == np.uint8
img = img - 1 # 0 (ignore)... |
bfd8b39679e5ab18c059dfe97cef2fdab689d7714d1c74f0ae6ec182cf845aa9 | Python | 896 | 19 | # 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... |
807531a4f74c188f9bd0e7f93f6f40a5716cdc84c3507777049539bdb14746a3 | Python | 901 | 22 | # Copyright 2011-2014 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 obtain a copy of the Licen... |
89b5b9d1fa222b2c254c214a1480c583222db9c06935ec5acb9edf97a5752c73 | Python | 901 | 22 | # Copyright 2011-2014 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 obtain a copy of the Licen... |
f466d1a58bc1a4404c1d8485a733857a3c2730ee46b8ada9e38864ef112c0916 | Python | 903 | 31 | # Copyright (c) Facebook, Inc. and its affiliates.
# pyre-unsafe
from typing import Optional
from detectron2.data import DatasetCatalog, MetadataCatalog
from ..utils import maybe_prepend_base_path
from .dataset_type import DatasetType
CHIMPNSEE_DATASET_NAME = "chimpnsee"
def register_dataset(datasets_root: Optio... |
14fc6960e7764c89a76fe3729dabcbf6e15190bed4edbc9deab1f3f9edeb2ddd | Python | 904 | 31 | import torch
class CoordStage(object):
def __init__(self, n_embed, down_factor):
self.n_embed = n_embed
self.down_factor = down_factor
def eval(self):
return self
def encode(self, c):
"""fake vqmodel interface"""
assert 0.0 <= c.min() and c.max() <= 1.0
b,c... |
e19ee6aaa78037e7d71c6d1d877ca9f3735c5c0129ef6ab5fc51cb59d46d9bb3 | Python | 907 | 24 | from typing import List
import numpy as np
def collate_outputs(outputs: List[dict]):
"""
used to collate default train_step and validation_step outputs. If you want something different then you gotta
extend this
we expect outputs to be a list of dictionaries where each of the dict has the same set o... |
ec10c503b2426f67ae960e13e20f8c064ba42c91d0caba49408cf7cbc16f31bc | Python | 911 | 28 | import pytest
from typing import Sequence
import numpy as np
import xarray as xr
from hsnn import ops
from ._utils import get_data
@pytest.mark.parametrize("test_input, expected", get_data('get_submask'))
def test_get_submask(test_input: Sequence, expected: Sequence):
mask = ops.get_submask(*test_input)
ass... |
ab3db6dad44eb4e86cfe7f77f44340e43651401975fc46db099e40c0abd18920 | Python | 914 | 42 | import sys
#export
import os, argparse, sys, datetime
import seaborn
from matplotlib import pyplot
import numpy, scipy
from katmap.utilities import NamedTuple
from spliceformats.utilities import IndexedDirectory
from katmap.commandline import MakeConfigCommandParser
from katmap.mikesmaps import find_rmats_path_by_... |
b8e0e91344288bf34549f16df0130e3ecefeaa852cafd9438e99345ce8a40269 | Python | 914 | 22 | import numpy as np
import scipy.io as io
from scipy.stats import pearsonr
def calculate_p_corr_matrix(data, lines, output_paths):
(rows, cols) = np.shape(data)
correlation_matrix = np.zeros((cols,cols))
p_value_matrix = np.zeros((cols,cols))
for i in range(cols):
for j in range(i+1, cols):
... |
4967183c188e6c045a6f2577f58de98922e4e85f6dc76c00929f8b06c6bb0d69 | Python | 916 | 34 | import argparse
from ..models import MODEL_REGISTRY
from torchinfo import summary
from eeg_visual_classification.utils.lib import (
extract_model_options,
)
parser = argparse.ArgumentParser(description="Summarize model")
# Model type/options
parser.add_argument(
"-mt",
"--model_type",
default="lstm",
... |
66b45d629a2cad7c8ca8bba66d403c248c9d7a877bf4fe5bb6140974968ae3b9 | Python | 917 | 30 | from typing import Any, Callable, Literal, Optional
from warnings import deprecated
from src.parameters import Parameters
from ..value_formatter import ValueFormatter
@deprecated("Use SearchSpace instead.")
class Parameter[T]:
def __init__(
self,
name: str,
values: list[T],
label... |
a321392cc0ad8e3e0bb51ab7e84ea3a611cc688062f9d268a8ac14e96bf5afd2 | Python | 918 | 27 | import os
import matplotlib.pyplot as plt
from nilearn import plotting
from tristan_pipeline.io.params import *
import nibabel as nib
space = "MNI152NLin2009cAsym"
for moco_label in list(mocos.keys()):
group_img = nib.load(os.path.join(os.path.join(grp_dir,"stats"),
f"group_... |
5450a897c04b1f7648f3b2943f6ee6ac2fa28a948193d1fbb7999e303bbc8b47 | Python | 921 | 23 | import pandas as pd
from config import COUNTRIES, INPUT_PATH, NON_PREDICTORS, OUTCOME
def load_modeling_data() -> tuple[pd.DataFrame, pd.DataFrame, pd.Series]:
if not INPUT_PATH.exists():
raise FileNotFoundError(
"Required modeling dataset not found: data/CleanedData.csv. "
"The p... |
2eb6919f6424b2082b48f3f503de496f4bfd47f4c5ed931bfebda3cbf0bc9984 | Python | 922 | 33 | from typing import Optional
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.colors import CenteredNorm, to_hex
def _array_to_hex(
array: np.ndarray,
palette: str = "viridis",
center: Optional[float] = None,
) -> np.ndarray:
"""
Convert an array of values to a hex color palette.
... |
ad799f6c23258c438ebfceb77de4b19ca4337d3119ef446c3e7121a86946f3d5 | Python | 923 | 25 | # This script is part of navis (http://www.github.com/navis-org/navis).
# Copyright (C) 2017 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... |
d80f06a63a8d78c5b9d63c018b9a9b6242669f8ab90c725a7d92a7240d23ef4e | Python | 925 | 23 | from pathlib import Path
import json
import pandas as pd
from sklearn.metrics import accuracy_score, precision_recall_fscore_support
ROOT = Path(__file__).resolve().parents[1]
pred_path = ROOT / "experiments/predictions/model_predictions.csv"
df = pd.read_csv(pred_path)
y_true = df["fine_intent"].astype(str)
y_pred = ... |
ea89aa8c8c8b54b45856931f59ee49b77242e380672e678435388f4a11d6877f | Python | 925 | 28 | import sys
from pathlib import Path
import torch
SCRIPTS = Path(__file__).resolve().parents[1] / "scripts"
sys.path.insert(0, str(SCRIPTS))
from shap_model import MeanPVEnsemble, PlausibleValueModel
def test_plausible_value_wrapper_exposes_each_pv_model_and_preserves_ensemble_mean():
model = MeanPVEnsemble(in... |
5a0cfb7f24f9d7b304e4f9f23c91c7cfeb7c840a4127d42b41585d6dee574152 | Python | 928 | 28 | import pytest
import torch
from chemprop.nn import ConstrainerFFN
@pytest.mark.parametrize("fp_dim", [2, 100, 300, 600])
def test_constrainer_forward(fp_dim):
batch = torch.tensor([0, 1, 1, 3, 3, 3])
rows_per_group = torch.bincount(batch)
b = len(batch)
t = 3
m = batch.max().item() + 1
fp = ... |
911b24d6e621bdbddd1d0c21cf8993c285ceac14d8647308889c2a3048c3c4ec | Python | 928 | 27 | import jinja2
from jinja2.ext import Extension
from snakebids.jinja2_ext.toml_encode import toml_string
def format_poetry(item: str):
"""Format a pip style dependency specification for a poetry pyproject.toml.
Only supports urls (prefixed with @) and version specifiers. No markers or extras.
The package... |
7dd3e4979116958ef479bbcda80823eeaa26edf9cf0e4a81652276f8b862162e | Python | 929 | 24 | """Import torch before RDKit to avoid a Windows DLL clash.
MolGpKa (the default protonation backend) needs PyTorch. On Windows, loading
torch *after* RDKit/MKL intermittently fails with ``OSError: [WinError 127]``
while loading ``shm.dll`` (an OpenMP/MKL DLL ordering issue). Importing torch
first, at process start, ke... |
f8436d1e6343d8e9496929fc38b747d45e2ed6b228cc27d2d22a3d58c820dd72 | Python | 930 | 24 | from pathlib import Path
import torch
from .utils.pca import PCAHandler
if __name__ == "__main__":
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
# Parameters
LAYERS = ["conv1", "layer1", "layer3", "avgpool"]
for layer_name in LAYERS:
print(f"Getting gram matrix of {... |
29beff3ce0b8b2881012092752255bae0c276a6fb68da9c72643a8e3054ddcf3 | Python | 934 | 26 | from torch.optim.lr_scheduler import _LRScheduler
class PolyLRScheduler(_LRScheduler):
def __init__(self, optimizer, initial_lr: float, max_steps: int, exponent: float = 0.9, current_step: int = None):
self.optimizer = optimizer
self.initial_lr = initial_lr
self.max_steps = max_steps
... |
d71367f34598c4fb1880cc6a911c352b9c1085d63981eb509d4f7c4c1b2ad6af | Python | 935 | 24 | # 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... |
d0a29b2dde8465ef982385429d18ed9b3d1afec24ed2702e2476f82c404cf3c2 | Python | 937 | 24 | # Copyright 2011-2014 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 obtain a copy of the Licen... |
73be567f0b68152dadddc8e59e6b270849839e5717eea37d3dea26938c1c8b98 | Python | 943 | 30 | import numpy as np
import numpy.typing as npt
import pandas as pd
__all__ = [
"labels_to_masks",
"get_target_ids",
"get_unique_id"
]
def labels_to_masks(labels: pd.DataFrame) -> dict[tuple[str, np.int64], npt.NDArray[np.bool_]]:
if 'image_id' in labels:
labels = labels.drop('image_id', axis=1... |
ba2bf1264a686bd5ecc320f145bba755e225d3464131fe4584fa3ecc5a70deed | Python | 950 | 25 | # Copyright (c) Facebook, Inc. and its affiliates.
import unittest
try:
# Caffe2 used to be included in PyTorch, but since PyTorch 1.10+,
# it is not included in pre-built packages. This is a safety BC check
from detectron2.config import get_cfg
from detectron2.export.c10 import Caffe2RPN
from dete... |
2b0815d93b5e116904bf6f26aa80bdd71fbaa2315ce5d5bc31f5f1ae3d0c2bec | Python | 951 | 25 | # Copyright 2011-2014 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 obtain a copy of the Licen... |
712a91335ef0d87f6e8ecc206729ac46d529f689e6d0a0a0ae974c5ba3e1b992 | Python | 952 | 35 | import torch
from torch.utils.data import Dataset
# Splitter class
class ValidationOnlySplitter(Dataset):
def __init__(self, dataset, split_path, split_num=0):
super().__init__()
# Set EEG dataset
self.dataset = dataset
# Load split
loaded = torch.load(split_path)
... |
2ce2feaf215515bd1b2999c75042066373ad04b1dcf455d8dc64f566ffc9971b | Python | 954 | 36 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
from plugcli.params import MultiStrategyGetter, Option
from openfecli.parameters.utils import import_parameter
def _atommapper_from_openfe_setup(user_input, context):
return import_pa... |
ec02b34dbf25d76dcb90422d62bb41b33c84bdb4cd6ecc86a8d4c274bfc20d02 | Python | 956 | 34 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
"""
Run absolute free energy calculations using OpenMM and OpenMMTools.
"""
from .equil_binding_afe_method import (
AbsoluteBindingComplexUnit,
AbsoluteBindingProtocol,
Absolute... |
f7eb9878a7a69153d96aaa5dadcd7b6727d946b82b2dd28280c5706fc9f60585 | Python | 956 | 38 | import pickle
import subprocess
from datetime import datetime
def get_git_hash() -> str:
"""Get git hash as string"""
return subprocess.check_output(["git", "rev-parse", "HEAD"]).decode("ascii").strip()
def main_timer(func):
def function_wrapper():
start_time = datetime.now()
print(f'Sta... |
5a01551901323d4bc9c8afb0833bb8d1e4642a3225aaa8d85378e9528d7450f1 | Python | 963 | 29 | #
# Copyright (c) 2023 10X Genomics, Inc. All rights reserved.
#
"""Write out the html, depends on websummary."""
from __future__ import annotations
from cellranger.websummary.react_components import ReactComponentEncoder, WebSummaryData
from websummary import summarize
def write_html_file(filename: str | bytes, web... |
79d16a521a05c7ec8e3681992bc95cd1733aa1322a3495e6df17aacef94adc15 | Python | 967 | 34 | # Calculate backbone chemical shifts from a trajectory
# Arguments are the protein, the trajectory directory and the number of residues
import MDAnalysis as mda
import nmrgnn
import os
import sys
protein = sys.argv[1]
traj_dir = sys.argv[2]
n_res = int(sys.argv[3])
u = mda.Universe(
os.path.join("condensed_data"... |
56d6c34afd305c2ade04e890939a08d0094547f2432dd2969ef88f2b8fd836bb | Python | 968 | 30 | # Copyright (c) Facebook, Inc. and its affiliates.
# pyre-unsafe
from detectron2.structures import BitMasks, Instances
from densepose.converters import ToMaskConverter
class MaskFromDensePoseSampler:
"""
Produce mask GT from DensePose predictions
This sampler simply converts DensePose predictions to Bi... |
87ad592600ba931c022eff088c22cb8786be2718115b8d155069be4d1f886385 | Python | 968 | 33 | from typing import Dict, Tuple, TypeAlias, TypeVar
import numpy as np
import numpy.typing as npt
import pandas as pd
__all__ = [
"SpikeEvents",
"SpikeTrains",
"FiringRates",
"Recording",
"SpikePatterns",
"SynParams",
]
SpikeEvents: TypeAlias = Tuple[npt.NDArray[np.int_], npt.NDArray[np.float... |
4b584f63da4ae341471c958384fa465a4af7eaf308beb2c17b47540470d8750f | Python | 969 | 29 | import numpy as np
import numpy.typing as npt
__all__ = [
"multiplicative_jitter"
]
def multiplicative_jitter(
values: npt.ArrayLike, sigma: float, dt: float = 0.1,
seed: np.random.Generator | int | None = None
) -> npt.NDArray[np.float64]:
"""Applies multiplicative jitter according to a provided arr... |
42f96102c28264a212fbb121783c54cd434673107f19bcb5e977d75979b0f9f9 | Python | 970 | 25 | import time
from selenium import webdriver
options = webdriver.ChromeOptions()
options.headless = True
driver = webdriver.Chrome("/home/animeshs/bin/chromedriver", options=options)
driver.get('https://bluetid-mntnu.bluegarden.net/Kindis/mobil/worktime/clockin');
driver.save_screenshot('screen.png')
time.sleep(5)
import... |
ccc563583304637134bec06c991cdbb8445a9eb0886789e13cdc35e48d2ecc74 | Python | 971 | 25 | import time
from selenium import webdriver
options = webdriver.ChromeOptions()
options.headless = True
driver = webdriver.Chrome("/home/animeshs/bin/chromedriver", options=options)
driver.get('https://bluetid-mntnu.bluegarden.net/Kindis/mobil/worktime/clockout');
driver.save_screenshot('screen.png')
time.sleep(5)
impo... |
29e4320826d3197e4b73f827f87a16fa0e7ea773d56e62c21f0e5529ea7216a5 | Python | 973 | 36 | ### By Anoushka Joglekar
import sys
import pandas as pd
import time
start_time = time.time()
print("Creating Isoform X cell matrix")
input_file = sys.argv[1]
all_info = [x.strip('\n').split('\t') for x in open(input_file).readlines()][1:]
print("Processing file with ",len(all_info)," entries")
gene_iso_names = [x... |
22843633d3e540970197c9e5f3e1781ac52d17b6cfa7c264337a71c5bf8d5510 | Python | 974 | 23 | import yaml
from pathlib import Path
from . import config
from .utils.pca import PCAHandler
if __name__ == "__main__":
# Parameters
LAYERS = config["layers"]
COMPONENTS = config["selected_components"]
for layer_name in LAYERS:
print(f"Processing {layer_name}")
pca_model_file_top_10 = ... |
c0bb60d5b79c602138be3a181a21c97f9ac9eedfc4a03273c307c2ca5064d506 | Python | 975 | 38 | import logging
from collections import OrderedDict
from functools import partial, wraps
from typing import Dict
import click
from click.core import Command
from .._steinbock import SteinbockException
logger = logging.getLogger(__name__.rpartition(".")[0].rpartition(".")[0])
class SteinbockCLIException(SteinbockExc... |
e195bc1f5cdfcf723b1a11c15e2539f15d11018bfcf20a758e18badca4b723fb | Python | 976 | 24 | from typing import Type
from nnunetv2.preprocessing.normalization.default_normalization_schemes import CTNormalization, NoNormalization, \
ZScoreNormalization, RescaleTo01Normalization, RGBTo01Normalization, ImageNormalization
channel_name_to_normalization_mapping = {
'ct': CTNormalization,
'nonorm': NoNo... |
3bdcfd0bae8ffdfc48114b0901afa9157e19588c53259338d45a11390b457984 | Python | 977 | 22 | # 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... |
dd31d7e3115674f491fb4fbde9da0833121793ca4aeec2c9413cbe73cfc6787e | Python | 978 | 29 | """The JSON audit report is written only when reporting is enabled."""
from __future__ import annotations
from pathlib import Path
from src.utils.models import RunReport
from src.workflow.pipeline import _write_report
def test_report_written_when_enabled(tmp_path: Path) -> None:
report = RunReport(input_file="... |
916f1d2de8e06e75a7b183e25efada57b5b23652095c6249aeecef3858f6485d | Python | 979 | 31 | import numpy as np
import numpy.typing as npt
from typing import Optional
from hsnn.analysis._types import RatesArray
def update_dict(dst: dict, src: Optional[dict] = None) -> dict:
src = {} if src is None else src
dst.update(src)
return dst
def get_bar_data(rates: RatesArray, nrn_id: int, masks: dict)... |
a7020ec4df5f8e4898fd20d1ab50e9cccab9af832d9241d9e166094e823a27e2 | Python | 979 | 34 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
import gufe
import pytest
from openfe.protocols import openmm_afe
@pytest.fixture
def benzene_complex_dag(benzene_modifications, T4_protein_component):
s = openmm_afe.AbsoluteBindingPr... |
80b9db0699c960bd40a3fa75b3ec67cbfa8a0ef5ab66369cd1d76a1d647f72c6 | Python | 980 | 38 | import os
import click
from openfecli import OFECommandPlugin
@click.command("view-ligand-network", short_help="Visualize a ligand network from a .graphml file.")
@click.argument(
"ligand-network",
type=click.Path(exists=True, readable=True, dir_okay=False, file_okay=True),
)
def view_ligand_network(ligand_... |
d914aa3ad433d02256b68dba776fff8eee6cdb1d28697caee1aa8bf14c1d4a89 | Python | 982 | 32 | """
nfml — Machine learning for ferroelectric nematic liquid crystals.
Property prediction (GNN and XGBoost) and de novo molecule generation (VAE).
Subpackages are imported lazily. ``import nfml`` on its own pulls in nothing
heavy, so a pure-XGBoost or pure-VAE workflow never pays for the parts it does
not use. Acces... |
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