Datasets:
OpenScientificCodeRegistry
/
Database

Dataset card Data Studio Files
xet
 Community
1
sha256
stringlengths
64
64
language
stringclasses
28 values
size
int32
1
491k
lines
int32
1
23.2k
content
stringlengths
1
200k
be71933512c97e070dea8e17dd11c8c310d945ea68943d1a1b44b61c9c20458f
Python
239
10
# This file is part of connectome-manipulator. # # SPDX-License-Identifier: Apache-2.0 # Copyright (c) 2024 Blue Brain Project/EPFL import connectome_manipulator.connectome_comparison.properties as test_module def test_null(): pass
010fbbbcfd279903039ea5a56188470d679509b73ef93241e2995ab852ae093f
Python
240
8
""" The `common_mice` schema is maintained by another package and is included here for ease of reference. DO NOT create new tables here. """ import datajoint as dj schema = dj.schema('common_mice', locals()) schema.spawn_missing_classes()
5a4f2c56bd9d59ecb88fa491dc23f01ec370f6fc49ad4065aa234510c1fd4a6e
Python
240
4
#!/usr/bin/env python3 import sys, runpy sys.argv = ['evaluate_ensemble_and_generate_distillation_data.py', '--dataset', 'DeepSTARR'] + sys.argv[1:] runpy.run_path('evaluate_ensemble_and_generate_distillation_data.py', run_name='__main__')
89f4844609dcbef68cb0c11d8e7a87c8abae1d2db6193c39a76ba62e72672bf2
Python
240
4
#!/usr/bin/env python3 import sys, runpy sys.argv = ['evaluate_ensemble_and_generate_distillation_data.py', '--dataset', 'lentiMPRA'] + sys.argv[1:] runpy.run_path('evaluate_ensemble_and_generate_distillation_data.py', run_name='__main__')
9ada55d119794c048f4489d06736fb898867129544ca27a4f9a8fef4831d02bc
Python
240
10
from os.path import join, dirname from subprocess import call from sys import exit, argv def main(): exe_path = join(dirname(__file__), "../bin/dynamont-NTC") exit(call([exe_path] + argv[1:])) if __name__ == "__main__": main()
0d85528dca80361ad340d46c958cc94f3e847391b91790bb4d0d01fab332779c
Python
241
7
# -*- coding: utf-8 -*- """This sub-package provides utility functions used throughout the package """ #:copyright: Copyright 2015 by Christoph Kirst, The Rockefeller University, New York City #:license: GNU, see LICENSE.txt for details.
479a02648fed10205efd6f0bf0ca7ea3fcb0f01cf17ef6bba6e366afc9949919
Python
241
9
from setuptools import setup,find_packages setup(name = "NER_Biomedical", version = "1.0", description = "NER_Biomedical project", author = "Son Ba", author_email = "bagiangson2001@gmail.com", packages=find_packages() )
54dfbc252ed71480d4f0cdfdf516ecfbe44efd0f6c3c64b158e7039f2906c91b
Python
241
4
P={'B': {'E': -0.510825623765990, 'M': -0.916290731874155}, 'E': {'B': -0.5897149736854513, 'S': -0.8085250474669937}, 'M': {'E': -0.33344856811948514, 'M': -1.2603623820268226}, 'S': {'B': -0.7211965654669841, 'S': -0.6658631448798212}}
98256ab0598f2b06708e05d99e67b0078336afaef71f8570f7de1c413e77d0dd
Python
241
10
# Copyright (C) CVAT.ai Corporation # # SPDX-License-Identifier: MIT class BadFunctionError(Exception): """ An exception that signifies that an auto-detection function has violated some constraint set by its interface. """
d853a57514da0a5c1213894f1cc22ba6a6d7981ddf8a71194d1f4b5297bc5147
Python
241
10
# This file is part of connectome-manipulator. # # SPDX-License-Identifier: Apache-2.0 # Copyright (c) 2024 Blue Brain Project/EPFL import connectome_manipulator.connectome_comparison.connectivity as test_module def test_null(): pass
4a51ba763b52b9d988510b7000225cce1f4551f17698eeff34917f0ba6fdfc39
Python
242
11
'''Like ogopogo, osteoporosis is elusive''' __all__ = ( '__version__', 'version_info', ) from pbr.version import VersionInfo _v = VersionInfo('ogo').semantic_version() __version__ = _v.release_string() version_info = _v.version_tuple()
4b2f4b5b373a067792ac94efe6ca12371313cbbd0216423b45c7fc5b1ab5dc60
Python
242
3
# from .PASTE import pairwise_align, center_align # from .helper import kl_divergence, intersect, match_spots_using_spatial_heuristic, filter_for_common_genes # from .visualization import plot_slice, stack_slices_pairwise, stack_slices_center
8732fadd171ee9591984fe0b7229bd2ca8da762c5a406f3a9caa8f864ec8912d
Python
242
5
# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license from .base import add_integration_callbacks, default_callbacks, get_default_callbacks __all__ = "add_integration_callbacks", "default_callbacks", "get_default_callbacks"
a2eed45e16a02b9ebd7bafa9f53f6df0a4fa0ffcb26cfeecac9877aafbfac6db
Python
242
6
# Copyright (C) CVAT.ai Corporation # # SPDX-License-Identifier: MIT # Backward compatibility stub; TODO: remove when it's safe from cvat.apps.engine.media_io.frame_provider import * # pylint: disable=unused-import, disable=wildcard-import
e6ab90f51842c35759ba8c409918bebe468bbe90eacc34778eb751e05d17c844
Python
242
8
import pytest import brainscore_vision @pytest.mark.travis_slow def test_has_identifier(): model = brainscore_vision.load_model('Hojin_Jang_ResNet50_Strong_blur') assert model.identifier == 'Hojin_Jang_ResNet50_Strong_blur'
4a7a645eae19c1c18e5a165afedf14163249ba360e41f9f4d8308a9f0dbb08ae
Python
243
4
from .base_tester import BaseTester from .global_embedding_space import GlobalEmbeddingSpaceTester from .global_twostream_embedding_space import GlobalTwoStreamEmbeddingSpaceTester from .with_same_parent_label import WithSameParentLabelTester
1cac653d552c6e0cb4092044a2aa81ed0d1b70dd21656eb36578231a05e43570
Python
244
8
import pytest import brainscore_vision @pytest.mark.travis_slow def test_has_identifier(): model = brainscore_vision.load_model('Zejin_Lu_dvd_s_imagenet_resnet50') assert model.identifier == 'Zejin_Lu_dvd_s_imagenet_resnet50'
5a869addf14a6c0c94b30c0779fca41bcc20a00fb2f167d7757056bf1496d412
Python
244
8
import pytest import brainscore_vision @pytest.mark.travis_slow def test_has_identifier(): model = brainscore_vision.load_model('convnext_tiny_imagenet1k_TA_GELU') assert model.identifier == 'convnext_tiny_imagenet1k_TA_GELU'
5cc0d5e24c40ee1cc82a9dfd35e71a1c6a4db7834f3ded55adec8374fb4c9f1a
Python
244
8
import pytest import brainscore_vision @pytest.mark.travis_slow def test_has_identifier(): model = brainscore_vision.load_model('convnext_tiny_imagenet1k_HANDsum') assert model.identifier == 'convnext_tiny_imagenet1k_HANDsum'
8e7e79df016ce3f402e2ccf97b43888a2b04228e2c5f8e23d62e5a544d496b1e
Python
244
8
import pytest import brainscore_vision @pytest.mark.travis_slow def test_has_identifier(): model = brainscore_vision.load_model('convnext_tiny_imagenet1k_GELU_PS') assert model.identifier == 'convnext_tiny_imagenet1k_GELU_PS'
95b7c37f2a2c0607d6025b051f13189df633179b80eb816725f1969bb9ef43a5
Python
244
8
import pytest import brainscore_vision @pytest.mark.travis_slow def test_has_identifier(): model = brainscore_vision.load_model('Zejin_Lu_dvd_p_imagenet_resnet50') assert model.identifier == 'Zejin_Lu_dvd_p_imagenet_resnet50'
a5ba8e87d17d9e47b5725350c40216a365993732e73b64133cfdc45596863a23
Python
244
8
import pytest import brainscore_vision @pytest.mark.travis_slow def test_has_identifier(): model = brainscore_vision.load_model('convnext_tiny_imagenet1k_HAND_PS') assert model.identifier == 'convnext_tiny_imagenet1k_HAND_PS'
e0eb75f687099773b4ae542425796843a2a048da816ad04fb4a721f37b3d8faa
Python
244
8
from typing import TypedDict, Annotated from langgraph.graph import add_messages from langgraph.managed.is_last_step import RemainingSteps class State(TypedDict): messages: Annotated[list, add_messages] remaining_steps: RemainingSteps
e17cad989548464545252f6e6dd68d7b452d79db1aadd6e54c9fdc28905c01e4
Python
244
8
import pytest import brainscore_vision @pytest.mark.travis_slow def test_has_identifier(): model = brainscore_vision.load_model('Zejin_Lu_dvd_b_imagenet_resnet50') assert model.identifier == 'Zejin_Lu_dvd_b_imagenet_resnet50'
b0ec3d17ebcd7522f4c032abcf01a60f639f53c5caee2451590095b5d52b8923
Python
245
8
from . import brain_generator from . import brain_generator from . import estimate_priors from . import labels_to_image_model from . import metrics_model from . import model_inputs from . import training from . import fine_tuning_with_adversary
c4cbfd59251d3e1ae521347f4a9ff035c28eaeead618a1e72bc62cb65f665138
Python
245
7
# encoding : utf-8 """This module implements functionailty for converting to and from miniscoPy objects (https://github.com/PeyracheLab/miniscoPy). Specifically we may want to convert to and from their trace class, and perhaps others, too. """
df4afcd0b4eaf9858108e7ae27a8a74af58cefb630d615a9e74066e799525dc7
Python
245
7
""" Data structures and tools for working with Position Weight Matrices (PWMs). TODO: Some of the packages in this directory are actually command line programs that provide no library functions and should be moved to the scripts directory. """
2928cf7e669fab37d782907046246df5cc092c7a2a55c61c1e2922f7c00f8249
Python
246
7
"""__init__.py.""" from splotch.inference import run_nuts, run_svi from splotch.registration import register from splotch.utils import get_input_data, savagedickey __all__ = ["get_input_data", "register", "run_nuts", "run_svi", "savagedickey"]
958c88024ea482597c50f448d0c00179f8ef08692815b562a20dfb6f03825f27
Python
246
7
# encoding : utf-8 """This module implements functionailty for converting to and from Brian objects (https://brian2.readthedocs.io/en/stable/) Specifically we may want to convert to and from their trace class, and perhaps others, too. """
b4435d9dc19a82a8f764bdb81fa59003139f1cb3845db5f934b808d14a6500d6
Python
246
10
import glob import os from pathlib import Path md_files = glob.glob("../*/*.md") for md_file in md_files: new_parts = list(Path(md_file).parts[:-1]) + ["readme.md"] new_file_name = Path(*new_parts) os.rename(md_file, new_file_name)
bc28ed02d4e2cd1f643dc2373e974437736f68d79c5233a0ad2c1f21a476840a
Python
246
12
"""Runs the production web interface for ADMET-AI (Gunicorn).""" from flask import Flask from admet_ai.web.app import app from admet_ai.web.run import setup_web def build_app(*args, **kwargs) -> Flask: setup_web(**kwargs) return app
d37ea6919d351c9df726966cb8b558b9d5e0eb44a264e3364b4998d243102f5e
Python
246
10
from os.path import join, dirname from subprocess import call from sys import exit, argv def main(): exe_path = join(dirname(__file__), "../bin/dynamont-NT-banded") exit(call([exe_path] + argv[1:])) if __name__ == "__main__": main()
dfdbfbe3bd121fa81c08466735861468724bce1a7e5f2e7ae40a010a6aea8bee
Python
246
4
from diffxpy.testing.utils import constraint_matrix_from_string, constraint_matrix_from_dict, \ constraint_system_from_star from diffxpy.testing.utils import design_matrix from diffxpy.testing.utils import view_coef_names, preview_coef_names
e3e284bf6f586f474c6a55a31f39707e2a496737b6addb7d0e5019c498eb7eb5
Python
246
10
""" Numerical constants relevant for IVIM. """ import numpy as np # Gyromagnetic constant ybar = 42.577e6 # Hz/T y = 2 * np.pi * ybar # rad/s/T # Diffusion coefficient of blood Db = 1.75e-3 # mm2/s, see Ahlgren et al 2016 NMR in Biomedicine
08dc4494a680aae47ec09ffcb064cd556627ffa8f3ac76c416620506657f94a3
Python
247
8
import pytest import brainscore_vision @pytest.mark.travis_slow def test_has_identifier(): model = brainscore_vision.load_model('cvt_cvt-w24-384-in22k_finetuned-in1k_4') assert model.identifier == 'cvt_cvt-w24-384-in22k_finetuned-in1k_4'
0e9cae056261a324c7b14d90a4c9b9c232090f9302bab8c5355ce2a8ad978d0d
Python
247
8
"""Utilities for FastSurfer crop management.""" from .ensure_fastsurfer_crops_exists import ( ensure_fastsurfer_crop_exists, ensure_fastsurfer_crops_exists, ) __all__ = ['ensure_fastsurfer_crop_exists', 'ensure_fastsurfer_crops_exists']
b638939e1e497220c84bae58643600e382d2dff041723beaa3ff366d772064c7
Python
247
8
from tests.utils import pytest_importorskip def test_qtquickcontrols2(): """Test the qtpy.QtQuickControls2 namespace""" QtQuickControls2 = pytest_importorskip("qtpy.QtQuickControls2") assert QtQuickControls2.QQuickStyle is not None
fb78311d815c7ffd6e43c928a177c11eb4bd1ce364d11fb849a46ab196a02bea
Python
247
4
from kinescope.prediction.train import train_and_evaluate, load_features_and_labels from kinescope.prediction.models import get_model, SUPPORTED_MODELS __all__ = ["train_and_evaluate", "load_features_and_labels", "get_model", "SUPPORTED_MODELS"]
02e9dfb4450ce651e9bd95f1b672d0f2dd202fd1ec285d67b3630f4c4f4538a0
Python
248
8
import pytest import brainscore_vision @pytest.mark.travis_slow def test_has_identifier(): model = brainscore_vision.load_model('convnext_tiny_imagenet1k_HAND_crop') assert model.identifier == 'convnext_tiny_imagenet1k_HAND_crop'
3a4cf1cb1fef86aabde4fc115661872baacca23a74165de5e7989aec5264ed91
Python
248
8
import pytest import brainscore_vision @pytest.mark.travis_slow def test_has_identifier(): model = brainscore_vision.load_model('convnext_tiny_imagenet1k_GELU_crop') assert model.identifier == 'convnext_tiny_imagenet1k_GELU_crop'
638c676ff1af201a2aead9897fd4baa3bca4582fd7135b1510c8166f256bb4e5
Python
248
11
import datetime __version__ = "0.1.0" __author__ = "Thomas Sanchez" __copyright__ = f"{datetime.date.today().year}, {__author__}" __email__ = "thomas.sanchez@unil.ch" __url__ = "https://github.com/Medical-Image-Analysis-Laboratory/fetmrqc_sr"
a3a97d30b0038cbc3cc4327424cc122f27b76b95c3670e3781ac2c1b5e9a3c37
Python
248
8
import pytest import brainscore_vision @pytest.mark.travis_slow def test_has_identifier(): model = brainscore_vision.load_model('convnext_large_clip_laion2b_finelayers') assert model.identifier == 'convnext_large_clip_laion2b_finelayers'
c33ca7ec0f7a69ae850683af69eee38ac810709ad4cd6fb8ea8826e60b22d773
Python
248
8
import pytest import brainscore_vision @pytest.mark.travis_slow def test_has_identifier(): model = brainscore_vision.load_model('convnext_tiny_imagenet1k_APGD_GELU') assert model.identifier == 'convnext_tiny_imagenet1k_APGD_GELU'
e98f8c56e4c20f04baa46fe1f9ca704129111b165c78796e179715be6d88bc33
Python
248
5
from brainscore_vision import benchmark_registry from .benchmark import Gifford2022 benchmark_registry['Gifford2022.IT-ridge'] = lambda: Gifford2022('IT', 'ridge') benchmark_registry['Gifford2022.IT-ridgecv'] = lambda: Gifford2022('IT', 'ridgecv')
1bde9e44e9772c99b1650b15b0198ecf30fb2a58e1c1de64543671bcd526b62d
Python
249
7
"""Surface Morphometrics: quantification of membrane surfaces from cryo-ET. See https://github.com/baradlab/surface_morphometrics and the `morphometrics` command line interface (defined in `surface_morphometrics.cli`). """ __version__ = "2.0.0b6"
4d89718d78517021daabf373f022c8d4d659b644bc13ad6f83e9973111b29e58
Python
249
11
import datetime def start_time(): return datetime.datetime.now() def end_time(): return datetime.datetime.now() def run_time(time_start, time_end): print("Total running time is:") print((time_end - time_start).seconds)
5b67887236914021ea82a8cff568eb601f48f1cba5285d57a9a1da7d8e807318
Python
249
7
import pytest import brainscore_vision @pytest.mark.travis_slow def test_has_identifier(): model = brainscore_vision.load_model('deit3_base_patch16_224_fb_in22k_ft_in1k') assert model.identifier == 'deit3_base_patch16_224_fb_in22k_ft_in1k'
654671ef923f105ca0e40e95bfb966b79de18a6acbbe6c908c024aa35fbd4d77
Python
249
10
import dtiplayground.dmri.common as common logger=common.logger measure_time=common.measure_time Color=common.Color get_uuid=common.get_uuid object_by_id=common.object_by_id get_timestamp=common.get_timestamp from .atlasbuilder import AtlasBuilder
a6dda867216d980029ef4a9d77891abe69d82e84a313da4c71b5411a9d29b930
Python
249
9
# Left empty as part of 2023 models migration import pytest import brainscore_vision @pytest.mark.travis_slow def test_has_identifier(): model = brainscore_vision.load_model('effnetb1_272x240') assert model.identifier == 'effnetb1_272x240'
694b0daf5b44a1e5aa094912b97334b5011d51d84729a5236bfe75df0ba2ba51
Python
250
11
from .parameter import ( Parameter, SEQUENCE_TAGGER_PARAMETERS, TRAINING_PARAMETERS, DOCUMENT_EMBEDDING_PARAMETERS, ) from .param_selection import ( SequenceTaggerParamSelector, TextClassifierParamSelector, SearchSpace, )
876650750c312bddc290aa499d07c340f509cc33116268c3e8ae3e72955178c4
Python
250
8
import pytest import brainscore_vision @pytest.mark.travis_slow def test_has_identifier(): model = brainscore_vision.load_model('convnext_tiny_imagenet1k_TA_HANDsum') assert model.identifier == 'convnext_tiny_imagenet1k_TA_HANDsum'
e9dd3d2a6416a5e2bcf3a4ff942240f1317c071a7f5d49aa2c246f9ff0833ba7
Python
250
9
"""Command-line wrapper; run from any working directory.""" import sys from pathlib import Path sys.path.insert(0, str(Path(__file__).resolve().parents[1])) from openplant.rebuild import main if __name__ == "__main__": raise SystemExit(main())
7370f04ea4d5de25537f4b0a7061f12b6610c33477d926f4d5d7294903495b6d
Python
251
9
"""Command-line wrapper; run from any working directory.""" import sys from pathlib import Path sys.path.insert(0, str(Path(__file__).resolve().parents[1])) from openplant.validate import main if __name__ == "__main__": raise SystemExit(main())
7f0f4a6bca137f6e0db2e1e0142768a71ee3346d9e28e1479566f466e14c8037
Python
251
6
"""Protocol builders: the sole construction sites for LangChain chat clients. Each protocol module owns exactly one client class. Endpoints prepare fully formed keyword arguments and hand them here; these builders add no endpoint-specific logic. """
666acc2212c720ad42415e2eb5b6d73c798a15eebd8f0f616ef1b6bbeb5a6fa2
Python
252
7
from pathlib import Path BASE_DIR = Path(__file__).resolve().parents[3] # Root directory of the project EMBEDDING_DIR = BASE_DIR / "PDB_db/embeddings" DISK_DIR = Path("/disk18T3/Yitao/project_1") FULL_EMBEDDING_DIR = DISK_DIR / "embeddings/protein"
e6f74ece10d83bf596fde8f5b5a872eb85912e1d73fc837ccbf0fe3306d39e63
Python
252
7
from .checkpointer import Checkpointer from .cumulator import Cumulator from .utils import (get_data_root, flatten_dict, get_lr, count_parameters) from .load_tpc_wedges import load_tpc_wedges
2b004a131fe0a667e459fabd5d9ce04b1daf0dd0e9c2e6620845721545cd25d1
Python
253
7
import pytest import brainscore_vision @pytest.mark.travis_slow def test_has_identifier(): model = brainscore_vision.load_model('convnext_base_fb_in1k_gram_aligned_dinov3') assert model.identifier == 'convnext_base_fb_in1k_gram_aligned_dinov3'
8e045d52f65c37196758957f2e154194069d00769253bb400afbe04251de87e8
Python
253
11
""" Tools for masking out specific sites in aligments by various criteria, for example masking CpG sites or sites with low sequence quality. """ from bx.align.sitemask.core import ( Masker, MaskPipeline, ) __all__ = ["MaskPipeline", "Masker"]
168446f54728f2a27bf5b3a098c0fa87c31e4e03c63f4bdafa7c715a83caf612
Python
254
12
import numpy as np def calc_kappa (length,delta): return (pow(length,4)-pow(delta,4)) / (12.0*pow(length,2)) def main (): cell_length = 20.0 delta = 30.0 print("Kappa = %.10lf" % (calc_kappa(cell_length,delta))) if __name__ == "__main__": main()
0826601f641a5e4c675215b27c187418b8913a4076ed7d4b69385fd52ce02b18
Python
255
8
import pytest import brainscore_vision @pytest.mark.travis_slow def test_has_identifier(): model = brainscore_vision.load_model('effnetb1_cutmix_augmix_sam_e1_5avg_424x377') assert model.identifier == 'effnetb1_cutmix_augmix_sam_e1_5avg_424x377'
0fb8672da94c46b7d6a349d4d60888cdb1053aabc4c55a57e4913d1acb39d3d6
Python
255
11
from django.apps import apps if apps.is_installed("silk"): from silk.profiling.profiler import silk_profile # pylint: disable=unused-import else: def silk_profile(name=None): def profile(f): return f return profile
33f5934158249376c96fc04c2e1a9d7b12c4c477cd446c485a28a0315c185dfe
Python
256
8
import pytest import brainscore_vision @pytest.mark.travis_slow def test_has_identifier(): model = brainscore_vision.load_model('convnext_tiny_imagenet1K_torchvisionV1') assert model.identifier == 'convnext_tiny_imagenet1K_torchvisionV1'
5af3c1007d3e6576a55c94308156d3726d0b1ce0f3b8689f084df10f3fc7025f
Python
256
8
import pytest import brainscore_vision @pytest.mark.travis_slow def test_has_identifier(): model = brainscore_vision.load_model('convnext_tiny_imagenet1k_APGD_HANDmean') assert model.identifier == 'convnext_tiny_imagenet1k_APGD_HANDmean'
005703bca01547e13605963f1a8a2b94a2e8dbf55ba696910359a2578e5e04a8
Python
257
7
__title__ = 'CellDetection' __version__ = '0.4.9' __author__ = 'Eric Upschulte' __email__ = 'e.upschulte@fz-juelich.de' __license__ = 'Apache License, Version 2.0' __summary__ = 'Cell Detection with PyTorch.' __url__ = __uri__ = 'https://celldetection.org'
18846c2d847e913e09271ee5878659005181663d1a79ba24b94d00ec96e30d50
Python
257
7
# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license from .predict import DetectionPredictor from .train import DetectionTrainer from .val import DetectionValidator __all__ = "DetectionPredictor", "DetectionTrainer", "DetectionValidator"
f5f64a5f9ff3531d74a32427ef871dac652d05f2cfd3955cae51ea2ab8d45c31
Python
257
17
from .sfcn import ( SFCN, BinarySFCN, CategoricalSFCN, MultiTaskSFCN, RegressionSFCN, sfcn_factory, ) __all__ = [ 'SFCN', 'BinarySFCN', 'CategoricalSFCN', 'MultiTaskSFCN', 'RegressionSFCN', 'sfcn_factory', ]
0d306f2de7f45d1f3fd18c2bf8c2d8066544955a2cee66761360199e2920a96b
Python
258
9
import torch import torch.nn as nn import numpy as np def Cifar100_fine2coarse(labels): class_interval = 5 coarse_label = labels/class_interval coarse_labels = torch.tensor(coarse_label.floor(), dtype=torch.long) return coarse_labels
b44583abf1137cc9b2252419dbb522aa66b053ba5ebbe4f099845c260ee612f3
Python
258
12
from .evaluate import Evaluator from .dataset import NodePropPredDataset try: from .dataset_pyg import PygNodePropPredDataset except ImportError: pass try: from .dataset_dgl import DglNodePropPredDataset except (ImportError, OSError): pass
c6bc3214a7f78319162bb19b832c206e5e8bcd24b7fa265c6fdd073074c03497
Python
258
8
import pytest import brainscore_vision @pytest.mark.travis_slow def test_has_identifier(): model = brainscore_vision.load_model('Zejin_Lu_dvd_baseline_imagenet_resnet50') assert model.identifier == 'Zejin_Lu_dvd_baseline_imagenet_resnet50'
e8815da201f10e360fab980e556f8b097d7c4fef229872ef9404423a54fd7e6d
Python
258
12
from .evaluate import Evaluator from .dataset import LinkPropPredDataset try: from .dataset_pyg import PygLinkPropPredDataset except ImportError: pass try: from .dataset_dgl import DglLinkPropPredDataset except (ImportError, OSError): pass
023c07a294c50de7b6c8df085a3b3993c096a1713f6913b323b35ecbb27c4516
Python
259
8
import pytest import brainscore_vision @pytest.mark.travis_slow def test_has_identifier(): model = brainscore_vision.load_model('cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4') assert model.identifier == 'cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4'
02db6b384e444643bb58b23e91f15ba1603ec47f2fb391050cdafe9b6e07abd6
Python
259
9
from tests.utils import pytest_importorskip def test_qt3dlogic(): """Test the qtpy.Qt3DLogic namespace""" Qt3DLogic = pytest_importorskip("qtpy.Qt3DLogic") assert Qt3DLogic.QLogicAspect is not None assert Qt3DLogic.QFrameAction is not None
a9443c2680725378143f6a0a7d98ed103f2a71a5dd58349b697d082ec737eb97
Python
259
8
import pytest import brainscore_vision @pytest.mark.travis_slow def test_has_identifier(): model = brainscore_vision.load_model('cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4') assert model.identifier == 'cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4'
d95dac35deae98dc551072bb7da0838de815f5e207d3ba67de2b41113def7e55
Python
259
11
from setuptools import find_packages, setup REQUIREMENTS = [i.strip() for i in open("requirements.txt").readlines()] setup( name="src", packages=find_packages(), version="0.1.0", python_requires=">=3.11", install_requires=REQUIREMENTS )
dcb75032f9851e6d87c80b31520c2f517574951abba85cd6fa19b0814018586c
Python
260
9
from importlib.metadata import PackageNotFoundError, version try: __version__ = version("pydesigner-dwi") except PackageNotFoundError: try: __version__ = version("pydesigner") except PackageNotFoundError: __version__ = "0+unknown"
757141ab32f9219acf3bedd8fc6a848e3fc6472f42a756c85ebef2152c21e616
Python
261
10
import pytest from brainscore_vision import load_stimulus_set @pytest.mark.private_access def test_num_elements(): stimulus_set = load_stimulus_set('BarbuMayo2019') assert len(stimulus_set) == 17261 assert len(set(stimulus_set['synset'])) == 104
8a3690a59d8d598e57a7d71120b705be5e8d67b336ad6ec70d2c970aa04d81e9
Python
261
9
import pytest from brainscore_vision import load_stimulus_set @pytest.mark.private_access def test_num_elements(): stimulus_set = load_stimulus_set('imagenet_val') assert len(stimulus_set) == 50_000 assert len(set(stimulus_set['label'])) == 1_000
9abd1e3fd40867d30cbfa23eb9754e2de0f3d4954465008497f77f98215311b0
Python
261
8
from io import BufferedIOBase, BufferedReader from pathlib import Path from typing import BinaryIO, Union # IO Types PathLike = Union[str, Path] BufferLike: object = Union[bytes, BinaryIO, BufferedIOBase, BufferedReader] FileLike = Union[PathLike, BufferLike]
0cae1866dafff789663416f55ac9bcf1a26652f802314e15d23bb79c5f060860
Python
262
12
import os import nibabel as nib from pytest import fixture test_path = os.path.dirname(os.path.abspath(__file__)) data_path = os.path.join(test_path, 'fixtures') @fixture def nifti_image(): return nib.load(os.path.join(data_path, 'raw', 'esten.nii.gz'))
605d4d69288bbe9b3278f939a17f1ff36ecf5fb24809d46242b530cf376f951e
Python
262
8
# -*- coding: utf-8 -*- """This sub-package provides tools for the visualization of the alignment and analysis results """ #:copyright: Copyright 2015 by Christoph Kirst, The Rockefeller University, New York City #:license: GNU, see LICENSE.txt for details.
b83473721050410a35db36672527a71c9e729dd1c3529cd1f3674032b2c7b5ba
Python
262
11
from skbuild import setup from setuptools import find_packages setup( name='tomocupy_stream', version=open('VERSION').read().strip(), author='Viktor Nikitin', package_dir={"": "src"}, packages=find_packages('src'), zip_safe=False, )
11c385a78fe514f594e8c1ae7680cb0f12b9cfb605e2f0cfd96c4d772e058867
Python
263
7
# Copyright (C) CVAT.ai Corporation # # SPDX-License-Identifier: MIT from cvat.utils.django_database.contextmanagers import * # noqa: F403 from cvat.utils.django_database.types import * # noqa: F403 from cvat.utils.django_database.utils import * # noqa: F403
5a5899b740413ff03057fc0e6981106780fd477fd235658f607e89eaeb32f0fe
Python
263
11
""" BCE Model Module This module contains various neural network models for B-cell epitope prediction. """ # from .ReCEP import ReCEP # from .EGNN import EGNNLayer # from .dihedral import DihedralFeatures # __all__ = ['ReCEP', 'EGNNLayer', 'DihedralFeatures']
640d79b2f4f04b929814774f4cdacc50bb11ced8d64679030321fc5182634012
Python
263
9
# Left empty as part of 2023 models migration import pytest import brainscore_vision @pytest.mark.travis_slow def test_has_identifier(): model = brainscore_vision.load_model('AdvProp_efficientnet-b6') assert model.identifier == 'AdvProp_efficientnet-b6'
cf4322abb908f69282198931fb23c09a1ef1101b066d57842402e6436a92eaa3
Python
263
7
from .aliked import ALIKED # noqa from .disk import DISK # noqa from .dog_hardnet import DoGHardNet # noqa from .lightglue import LightGlue # noqa from .sift import SIFT # noqa from .superpoint import SuperPoint # noqa from .utils import match_pair # noqa
bed33d34e3b82cb44d54bd30cfdc43f886f7410967744b331c6055435c6de3f7
Python
264
7
from PyInstaller.utils.hooks import collect_dynamic_libs hiddenimports = [ "sklearn.metrics._pairwise_distances_reduction._datasets_pair", "sklearn.metrics._pairwise_distances_reduction._middle_term_computer", ] binaries = collect_dynamic_libs("sklearn")
97dda2dd3ae507b9af8a46d4da1776a7c2db3a458ab3d5efee3a5e0ad224e390
Python
266
9
from sharpy_track.view.RegistrationViewer import RegistrationViewer import sys from qtpy.QtWidgets import QApplication if __name__ == "__main__": app = QApplication(sys.argv) RegViewer = RegistrationViewer(app) RegViewer.show() sys.exit(app.exec())
d21f1bd4260c76453208819c97dec0e395ed47f596e00f148f3b56da9ec59fbf
Python
266
7
import os from util.config_vars import config from step3_2_manual_labeling.step3_2_manual_label_tk import ManualImageEvaluator def main(): csv_name = os.path.join(config.paths.csv.step3, "final_revision_data_groundtruth.csv") ManualImageEvaluator(csv_name)
3cd1e518a9548dda675bc5fd2b7b523fe6f0a48468e7ee450f6a1f42dab37377
Python
267
10
from .ann_pemfc import PEMFC_ANN, PEMFC_ANN_Trainer from .epcdnn_vrfb import VRFB_ePCDNN, ePCDNN_VRFB_Trainer, PhysicsConstrainedLoss __all__ = [ 'PEMFC_ANN', 'PEMFC_ANN_Trainer', 'VRFB_ePCDNN', 'ePCDNN_VRFB_Trainer', 'PhysicsConstrainedLoss', ]
919dca6f4d475ba350104fa7b481f7a33dfdffdd7d89b2615292e61e7784324d
Python
267
9
from sharpy_track.view.RegistrationViewer import RegistrationViewer import sys from PyQt5.QtWidgets import QApplication if __name__ == "__main__": app = QApplication(sys.argv) RegViewer = RegistrationViewer(app) RegViewer.show() sys.exit(app.exec_())
98aaf7361b97e7c3c0f66592f4f465f56a9dc00d4f10f03da13bb928257623e4
Python
267
13
import gc import spotd.main_code_sec1 as spotae def train_model(cell_key): print("-------------S^2POTAE Model Training-----------------") spotae.main(cell_key) if __name__ == '__main__': cell_key = 'cell_type' train_model( cell_key)
b3ffce40239b547bf75c364e83dfeba9009a6ff9c88b415fc3699a40024753e2
Python
267
8
from argclz.commands import parse_command_args from .main_tactile_summary import TactileSummaryOptions parse_command_args( usage='python -m rscvp.behavioral CMD ...', description='Analysis of behavioral results', parsers=dict(bs=TactileSummaryOptions) )
e78f92398f53c8355497bb717255e8655469a263ff2c1240b10b5ab7cc2f16a6
Python
267
10
# Copyright (C) CVAT.ai Corporation # # SPDX-License-Identifier: MIT def to_cvat_mask(box: list, mask): xtl, ytl, xbr, ybr = box flattened = mask[ytl : ybr + 1, xtl : xbr + 1].flat[:].tolist() flattened.extend([xtl, ytl, xbr, ybr]) return flattened
693e05bbe59824b4792bc3b991a4738528702523d725e871aa5d895219178cfa
Python
268
11
from pathlib import Path import numpy as np path = Path(__file__).parent directory = str(path) layouts = path / "layouts" ctf275_channel_names = np.load(path / "ctf275_channel_names.npy") neuromag306_channel_names = np.load(path / "neuromag306_channel_names.npy")
d30fc4a1389bf83baf03cc35d755c94d75b2a293487fa71f752974b18c13b275
Python
269
10
from skeleton_keys.hist_tasks import create_layer_histograms from skeleton_keys.tasks import * from taskqueue import TaskQueue import sys queue = sys.argv[1] timeout = int(sys.argv[2]) with TaskQueue(qurl=queue, n_threads=0) as tq: tq.poll(lease_seconds=timeout)
e264c0817e81a5f0de254eea32e151c3163f84cc82cd81f6e4337edfb94c9e80
Python
269
7
from .DropConfig import DropConfig from .SampleAnnotation import SampleAnnotation from .submodules.MonoallelicExpression import MAE from .submodules.AberrantSplicing import AS from .submodules.AberrantExpression import AE from .submodules.RNAVariantCalling import RVC
f968bbe03a6f145797238451d9ccf682971958ee36acb3762ea0262badbceebc
Python
269
12
from sklearn.base import BaseEstimator, TransformerMixin class IdentityTransformer(BaseEstimator, TransformerMixin): def fit(self, X, y=None): return self def transform(self, X): return X def inverse_transform(self, X): return X
6defe81cea7126d3f7316ad58ce0fb3e505ad4c37222e62ddc322b2a2a33e6c3
Python
270
7
import os import ClearMap.Settings as settings filename = os.path.join(settings.ClearMapPath, 'Test/Data/ImageAnalysis/cfos-substack.tif'); import ClearMap.Visualization.Plot as plt import ClearMap.IO as io data = io.readData(filename, z = (0,26)); plt.plotTiling(data);
7e382f38b119c85cff2399b948d3ede454f8db0a9f9c9b9c34dd55f54d5a955a
Python
270
5
from builder.models.src.transformer.attention import * from builder.models.src.transformer.decoder import * from builder.models.src.transformer.encoder import * from builder.models.src.transformer.module import * from builder.models.src.transformer.transformer import *
82b3cd24771caa611e541612cb2fb45cb59fdd4b49818e50df164cce353435a8
Python
271
8
import pandas as pd def clip_negative_first_row(df: pd.DataFrame) -> pd.DataFrame: """Return a copy with negative values in the first row clipped to zero.""" clipped_df = df.copy() clipped_df.iloc[0] = clipped_df.iloc[0].clip(lower=0) return clipped_df