sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
0ef6aab515daa4e2415fb0bfd4323e1dd766c65bba72de7a1a59706172ccbc2f | Python | 10,258 | 280 | """
Script for calculating self consistency TM scores
"""
import argparse
import functools
from glob import glob
import os
import logging
from pathlib import Path
import multiprocessing as mp
import json
from typing import *
import numpy as np
import pandas as pd
from matplotlib import pyplot as plt
import seaborn as... |
6b73c6ffed2846f5f91b4d79bd80f487618e939336c75391b98d881d5d06b6ce | Python | 10,263 | 231 | """Bundle assembly: what ships, what it is called, and whether it can be built twice.
The legacy release script gathered a bundle with ``cp *.txt``, which would have swept in seven side
tables the shipped zip does not contain -- so the script that produced the release was not the one
that defined it. These tests asser... |
def47e1dfb2f406bedfb45bcbf86d1c1f5aa9fe35849e8168750ecd1b49a9df6 | Python | 10,264 | 245 | """mass_ss.py: Defines the MASS class that manipulates the MASS database."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
import time
import numpy as np
from sleeprnn.common import constants
from sleeprnn.data import utils
from sleeprnn.data ... |
fd3b3247d66926fb1b2488d76c79742620efc93158437129fe62026241fdcc90 | Python | 10,272 | 290 | """The optimizer, scheduler and EMA flags, checked where they take effect.
Seven flags that every training run carries and no test asserted anything about.
They all end up as a number inside an optimizer, a scheduler or the moving
average, and none of them changes whether a run succeeds, so a flag that stopped
being r... |
237e45db646c3943d1bd8eea228aa9c325773b70b84498514c25fcc4235b8051 | Python | 10,276 | 309 | # import os
# import pdb
# import re
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from scipy import signal
def supply_zero_value_by_former(x):
# to replace the zero value by the previous valid keypoints
new_x = x.copy()
for each_kpt in x.columns:
for zero_value_index in ... |
a0041eeccc9da1bd7ad93ba20e49db4470d53d2e0dec3f8f165c78670c09f77d | Python | 10,281 | 200 | """Publication year for every ``reference.id`` in the database, resolved once and committed.
The dashboard plots records by year. Until now it resolved PubMed ids by calling NCBI eutils at
render time and covered everything else with a literal fourteen-entry table inside the Rmd, last
updated in 2021. Measured on the ... |
fdd31cfb755a7e083f278cc987ef2635a646f032e27d54d7bc4bc4503f342bc2 | Python | 10,288 | 268 | """
Implementation of the decorator using a Encoder-Decoder architecture.
"""
import math
import logging
import torch
import torch.nn as tnn
import torch.nn.utils.rnn as tnnur
from reinvent.models.model_parameter_enum import ModelParametersEnum
logger = logging.getLogger(__name__)
class Encoder(tnn.Module):
"... |
a46a4ceab69017c535c6b451ff2d922c8e11aa513784c6496e3970b76ba62243 | Python | 10,291 | 329 | from __future__ import annotations
import logging
from itertools import product
from typing import Literal, Optional, Union
import pandas as pd
from neuron import h
from tqdm import tqdm
from src.cells.pv_nrn import get_pv, get_pv_mixed, mut, set_nrn_prop, set_stim
from src.constants import (
CURRENT_LABEL,
... |
1f325c23aedc4f577ce91b96b8db9619ec3c92715925a3a8c20b4e9f199f7f89 | Python | 10,295 | 250 | import sys
import os
import math
import numpy as np
import torch
import torch_geometric
from torch_cluster import radius_graph
from torch_scatter import scatter
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
from utils import get_iso_permuted_dataset
from e3nn.nn.models.gate_points_2101 im... |
7a15f93a34131bd6b6fbdb274f6eb59d6dee984f28ab3b100b4c77a632b0d2ba | Python | 10,296 | 286 | import tensorflow as tf
import numpy as np
tf.keras.backend.clear_session()
class featureExtraction(tf.keras.layers.Layer):
def __init__(self, chans, F, T, D, use_bias=False, **kwargs):
super(featureExtraction, self).__init__(**kwargs)
self.conv1 = tf.keras.layers.Conv2D(filters=F, kernel_size=(T, ... |
ffb0ac46fdb86c89a46b29bf20fb35cb749bfca14ddf9992df6af034666a43b8 | Python | 10,310 | 291 |
import os
import random
import time
from functools import partial
from pathlib import Path
import numpy as np
import torch
import webdataset as wds
import yaml
from torch import optim
import mlspm.data_loading as dl
import mlspm.preprocessing as pp
import mlspm.visualization as vis
from mlspm import graph, utils
fro... |
e6facb95c964e2cfb5894e56d4ec66a4d6ecfea8cdd337fb4240c3914c6d5665 | Python | 10,313 | 177 | # Copyright (c) 2019, NVIDIA CORPORATION. All rights reserved.
#
# This work is licensed under the Creative Commons Attribution-NonCommercial
# 4.0 International License. To view a copy of this license, visit
# http://creativecommons.org/licenses/by-nc/4.0/ or send a letter to
# Creative Commons, PO Box 1866, Mountain ... |
f751c2b9444374d81c82cc7d31d4aa48c44284fa53b15a8728209020a0f63eef | Python | 10,317 | 236 | import numpy as np
from numpy.random import multivariate_normal
from scipy.stats import ortho_group
from sklearn.metrics import r2_score
from typing import Optional
from theory_simulation.regression import regression_performance
from theory_simulation.utils import fsolve_bounded_monotonic, project_onto_subspace
class... |
e8b18753dbc9247eea9b2299b4e04f88c08cd0788a661c52d8f4d7393ab7255d | Python | 10,321 | 264 | import sys
import json
import os
import time
import six
import argparse
import glob
import re
import modelhouse
import torch
from metroem import loss, augmentations
from metroem.alignment import aligner_train_loop
from metroem.dataset import MultimipDataset
import torch.multiprocessing as mp
from torch.nn.parallel i... |
0fe962de81afdeff925150092682953b6449accaf1d7275d728e5b3db44aea17 | Python | 10,330 | 326 | import argparse
import logging
import os
import pathlib
import re
from typing import Any, Dict, List, Optional
import attr
import snakemake
# We define Path here in addition to pathlib to put both variables in globals()
# This way, users specifying a path type in their config.yaml can indicate
# either Path or pathli... |
32997f7864be1d07f2a14ab01a1aedb957dec9d2e9d19ddad7fa9b90ebe2c865 | Python | 10,351 | 321 | import os
from glob import glob
import sys
from processing import *
from tqdm import tqdm
import pandas as pd
from scipy.stats import spearmanr, ttest_ind
import seaborn as sns
import anndata
import scanpy as sc
import umap
import matplotlib.pyplot as plt
from sklearn.metrics import accuracy_score
from sklearn.prepro... |
5f96f0820ea8a277048dc8daa09768a0d2e31f06b71ddaa9dec4b26c141f07cf | Python | 10,364 | 320 | # copyright (c) 2023 PaddlePaddle Authors. All Rights Reserve.
#
# 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 at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... |
ff6286264b9470f0257e7c19acca0682c18c5b3d8d916765c36d71f84bc27838 | Python | 10,364 | 242 | #!/usr/bin/python3
###
# Master controller for the TreeMaze. It communicates with the arduino through serial port.
# Receives data through GPIO inputs and serial.
###
import threading
from MazeHeader import *
PythonControlSet = ['T2','T3a','T3b','T3c','T3d','T3e','T3f','T3g','T3h','T4a','T4b','T4c','T4d', 'T5Ra','T... |
0d59b41ccb0e6cc574370a521837a7ef07f0f028c8ae1369791892d5f9ec530d | Python | 10,369 | 251 | #### python_ncut_lib.py
# Copyright (C) 2010 R. Cameron Craddock (cameron.craddock@gmail.com)
#
# This script is a part of the pyClusterROI python toolbox for the spatially
# constrained clustering of fMRI data. It provides the library functions for
# performing normalized cut clustering according to:
#
# Stella Yu and... |
1321ff23b2737227b1695ec412ea33eb0b1d0f245399f39e9738dee0ce6a2cd5 | Python | 10,374 | 209 | import os
os.environ['CONDA_DLL_SEARCH_MODIFICATION_ENABLE'] = '1' #DLL bug in my environment - might be unnecessary for most other people
import openslide
import xml.etree.ElementTree as ET
from PIL import Image, ImageDraw
from skimage.measure import label, regionprops
from scipy.ndimage import binary_erosion, maximu... |
c39518b7f6b2dd3861fa9e2ad0c80dcde95355bc888b76e0c933a242463d0250 | Python | 10,374 | 297 | # Copyright (C) 2020-2022 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
from bisect import bisect
import matplotlib.pyplot as plt
import numpy as np
import torch
from privacy_meter.audit import Audit
from privacy_meter.constants import InferenceGame
from privacy_meter.dataset import Dataset
from privacy_me... |
5a77ea4aa0c04bf0b22f6def7e0a9695cecd5f2705a2b20b7f0dc48833d1984e | Python | 10,378 | 229 | import numpy as np
from numpy.random import randint
from scipy.special import softmax
from sklearn.metrics import confusion_matrix, classification_report
from sklearn.model_selection import StratifiedKFold, KFold
import os
def dotProductLit(df, literature_sequences, literature_labels, random_seed: int = None):
"""... |
75cb44256550e4a090a8a9f2e0f650ff7e1e90afcb0a3e859d7f75babfe4e9b9 | Python | 10,381 | 296 | # Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
#
# 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 at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appli... |
9b3221cec3a894d3a3294a4de6eaea3865c4f1053e92c2fc578cf37f6c72833d | Python | 10,381 | 222 | """The AIRR export: schema conformance, the value mappings, and the two source paths agreeing."""
from __future__ import annotations
from pathlib import Path
import airr as A
import polars as pl
import pytest
from airr.schema import RearrangementSchema as RS
from vdjdb.emit import airr
from vdjdb.schema import AIRR_... |
a836c949970da0164001a5eb547a1853a38c2e24061b5792b8fbf0f2172c1e9c | Python | 10,390 | 299 | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from argparse import Namespace
from pathlib import Path
from typing import Dict, Optional
from fairseq.data import Dictionary
def get_config... |
3f6d0dd9d70ea2284c8abc321980de05d6987934100fc7ece714bcddbfeafb99 | Python | 10,394 | 283 | # Copyright 2020-2025 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
import logging
import pytest
import os
import shutil
import random
from metaflow import Step
from tests.end_to_end.utils.wf_common_fixtures import (
fx_local_federated_workflow,
fx_local_federated_workflow_prvt_attr,
fx_local_fe... |
153402639737de34829e64401e99c52074ce9b1262bea2d6b9ecc8c3d0683181 | Python | 10,403 | 212 | '''
Module focused on the implementation of the MultiBox Loss Function.
'''
import torch
import torch.nn as nn
import numpy as np
from smithers.ml.utils_objdet import cxcy_to_xy, find_jaccard_overlap, cxcy_to_gcxgcy, xy_to_cxcy
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
class ... |
fbc2c627738c38c6641e182431e353c689f37d973b22d2f363ffb8399a2a513e | Python | 10,404 | 275 | # This file is a part of the `nequip` package. Please see LICENSE and README at the root for information on using it.
import copy
import tempfile
import pathlib
import subprocess
import os
import sys
import uuid
import torch
from omegaconf import OmegaConf, open_dict
from nequip.data import AtomicDataDict
BEST_CHECK... |
96d138b8c7bc834e4b6c2b9a631ea68bfb9f35d766f109711be9ebbb2b3c40c6 | Python | 10,407 | 268 | import torch
import numpy as np
import os
import pandas as pd
import scipy.sparse as sp
import random
from torch_geometric.data import download_url
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
class POKEC():
r"""Pokec is a social network dataset. Two `different datasets <https://github.co... |
fa9ae3209704829730dd82aa0816598c719bff81d3e1d277dccafd9f6c043760 | Python | 10,410 | 259 | # -*- coding: utf-8 -*-
#
#
# PyRates software framework for flexible implementation of neural
# network model_templates and simulations. See also:
# https://github.com/pyrates-neuroscience/PyRates
#
# Copyright (C) 2017-2018 the original authors (Richard Gast and
# Daniel Rose), the Max-Planck-Institute for Human Cogn... |
252e85f078ec2fafe8d00e80226b5869914e919c599916f8c20f8b8259ba62a5 | Python | 10,413 | 385 | """
MOL METHODS
====================
Compendium of methods for SMILES parsing and molecular metrics handling.
This module is mainly a reorganization of Gabriel Guimaraes and Benjamin
Sanchez-Lengeling's original implementation (http://github.com/gablg1/ORGAN).
Carlos Outeiral has cleaned up and documented the code,... |
475f02e307ea0293c71d74af50825e47e76579bc10e1779afe2542f96f563edc | Python | 10,416 | 177 | # Copyright (c) 2019, NVIDIA CORPORATION. All rights reserved.
#
# This work is licensed under the Creative Commons Attribution-NonCommercial
# 4.0 International License. To view a copy of this license, visit
# http://creativecommons.org/licenses/by-nc/4.0/ or send a letter to
# Creative Commons, PO Box 1866, Mountain ... |
1032a258dbf4bdad005992d8f5a7fd26a5d8f9f78ace92c6bf4eb72ebe594ccc | Python | 10,417 | 306 | import numpy as np
from torch import nn, Tensor
import math
from torch.nn import functional as F
from typing import Optional, Dict, Tuple, Union, Sequence
from .transformer import LocationPreservingVit
from .mobilenetv2 import InvertedResidual
from .base_module import BaseModule
from ..misc.profiler import module_prof... |
1df50885f692143e4b2ccec4a06b7e310759b3ec66d4b8fee10c5dc33aa506df | Python | 10,431 | 331 | import pytest
import geomstats.backend as gs
from geomstats.test.data import TestData
class NumpyRaisesTestData(TestData):
def raises_test_data(self):
data = [
dict(autodiff_func=gs.autodiff.value_and_grad),
dict(autodiff_func=gs.autodiff.jacobian),
dict(autodiff_func=... |
bf1e22bcb9eef85d40a2ddcd46d672338009d8b833ad4c7cd8da8e09b4b5b9d3 | Python | 10,441 | 321 | # Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
#
# 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 at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appli... |
0f725d402c42f518d463fc0eb6cd91bf2bfd86889b9830dd73f2331a4450368b | Python | 10,449 | 225 | # Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
#
# 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 at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appli... |
5d080e9e323dd33b9cc76c95e5b6d438e9abdcab34721c6193522587b9cddc91 | Python | 10,451 | 262 | import warnings
import numpy as np
warnings.simplefilter('always', UserWarning)
# ----------------------------------------------------------------------------------------------------------------------------------------------------
# Generate Stimulus
# -----------------------------------------------------------------... |
808f305d2b8d7c5cb2ab0ceaa52f885b6f9b105a8092221959c6deb3b2972a9b | Python | 10,452 | 243 | import os, glob, numpy as np, shutil, matplotlib.pyplot as plt, cv2.cv2 as cv2, seaborn as sns
import tensorflow as tf, keras
from tensorflow.keras.callbacks import ModelCheckpoint, EarlyStopping
from tensorflow.keras.preprocessing.image import load_img, img_to_array, ImageDataGenerator
from tensorflow.keras.layers im... |
15ac52edfe91d6a24503e935a117b107b85ba191f0b74836707a17574b2ebca1 | Python | 10,453 | 261 | # Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
#
# 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 at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appli... |
6660cc00f1c62b2663bc39f9c1c732dbcc3cfd1db5c6ca190b9953b50e8f6886 | Python | 10,453 | 211 | # Generated by Django 4.1.1 on 2022-10-02 16:56
from django.db import migrations, models
import django.db.models.deletion
import django.utils.timezone
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='CellType'... |
8eb2dde5e44fe5d3f2e60eb123f7db38a8a57d2c5931503ac1f7c77a278be7c5 | Python | 10,456 | 286 | """Define and apply the versioned SanPy JSON payload stored in NWB scratch."""
from __future__ import annotations
import math
from typing import Any, Literal
import numpy as np
from pydantic import BaseModel, ConfigDict, Field, model_validator
from sanpy.bAnalysisResults import AnalysisResults
from sanpy.bDetection... |
67d96e1e82fb1a601d1a43b1ead2677c81f04a19cf4ae4a5706050d7f02df840 | Python | 10,463 | 272 | # -*- coding: utf-8 -*-
#
#
# PyRates software framework for flexible implementation of neural
# network model_templates and simulations. See also:
# https://github.com/pyrates-neuroscience/PyRates
#
# Copyright (C) 2017-2018 the original authors (Richard Gast and
# Daniel Rose), the Max-Planck-Institute for Human C... |
d13fcd967e1aa71c63805224c663b0258913542a4b8ac40cad65c6456120c15e | Python | 10,463 | 213 | import math
import torch
from torch import Tensor
import torch.nn as nn
import copy
from torch_geometric.utils.loop import add_remaining_self_loops
from ..models.utils import subgraph
from ..models.models import GraphSequential
from .base_explainer import WalkBase
EPS = 1e-15
class GNN_LRP(WalkBase):
... |
889a73bb24bb943831056f8520935cd814e707643759c8be89d16f0282b8cf02 | Python | 10,464 | 249 | """One training step on a committed anchor, reduced to a comparable digest.
A loss-decrease smoke test and a final-error table cannot see a gradient bug
the size of initialisation noise: both stay green while `d(loss)/d(theta)` is
wrong in a way that only slows convergence. This module produces the thing
that can see ... |
9d52b7922084aebddfe4d720e8cc8c450d0f2bf2a9c9a24d077497faddd48479 | Python | 10,466 | 298 | import os
aff = os.sched_getaffinity(0)
print(
"**********************before import torch******************************" + str(aff)
)
import torch
print(
"**********************after import torch******************************"
+ str(os.sched_getaffinity(0))
)
os.sched_setaffinity(0, aff)
from DeepPurpose... |
4cddc7f9aa5c74f9746c19dfa2de1b39a767ce17ba69444c247c543ea38cc498 | Python | 10,467 | 272 | # -*- coding: utf-8 -*-
#
#
# PyRates software framework for flexible implementation of neural
# network model_templates and simulations. See also:
# https://github.com/pyrates-neuroscience/PyRates
#
# Copyright (C) 2017-2018 the original authors (Richard Gast and
# Daniel Rose), the Max-Planck-Institute for Human C... |
e030d825875664d7cfa01be33b063133fad03e17c6019b44265758ff5c82adf9 | Python | 10,474 | 303 | import time
from threading import Thread
import pylsl
import numpy as np
from ._stream import StreamEEG, StreamMarker
from .. import logger
class StreamReceiver:
"""
Class for data acquisition from LSL streams.
It supports the streams of:
- EEG
- Markers
Parameters
----------
... |
fc02a54108282971a736e0095d3fbc8b4065d15aba771c541fc3a16fe3cae271 | Python | 10,479 | 199 | import sys
import os
import numpy as np
from sklearn import metrics
from .model import GeneSGAN
from .utils import highest_matching_clustering, parse_validation_data, n_sig_calculation
from .clustering import Gene_SGAN_train
__author__ = "Zhijian Yang"
__copyright__ = "Copyright 2019-2020 The CBICA & SBIA Lab"
__credi... |
c0fc78a35352c504e23d7249eca68ee25ddb655c10cbfcb061cb7ac85c29066b | Python | 10,483 | 258 | import copy
import math
import torch
import torch.nn as nn
import torch.nn.functional as F
import rdkit
import rdkit.Chem as Chem
from .mol_tree import MolTree
from .nnutils import create_var
from .jtnn_enc import JTNNEncoder
from .jtnn_dec import JTNNDecoder
from .mpn import MPN
from .jtmpn import JTMPN
from .dataut... |
07bce02e9faf61d5d1f5c7214b3611723b3ee784246897236c27eb62820e6b31 | Python | 10,487 | 334 | import hashlib
import os
import time
import numpy as np
from PymoNNto.Exploration.StorageManager.StorageManager import *
from PymoNNto.Exploration.UI_Base import *
from PymoNNto.Exploration.Network_UI.Basic_Tabs.Helper.syntax import *
class Behavior_Parser_Object:
md5_hash=''
code=''
name=''
tags=None... |
7b26f999611127622c524855c845af469703faddf90fd9ad18ab90025e897b6e | Python | 10,487 | 326 | import numpy as np
from data import indicator_basis, ou_process
from utils import allclose_sign, allclose_trajs, allclose_trajs_sign
import pytest
import ref_corr
import ivac
def make_data(ns, dt, nbins):
"""Generate featurized data for testing."""
return [indicator_basis(ou_process(n, dt), nbins) for n in n... |
240c542314a1ccf359d7e435bcc0a9047ed69ad3e5bcc95c66086980432d9ac0 | Python | 10,507 | 189 | """Score a motif clustering, and score legacy's the same way, on one cohort.
Phase 11's acceptance criterion is a comparison, and both sides have to be scored identically on
identical rows. So this module does two things: turn a ``cluster_members``-shaped file into the
``(label, cluster)`` frame :mod:`vdjdb.validate.m... |
5760ad7d21a1a6e1e8f236191178f76bcf4007e7c23417b2dd10695400af441f | Python | 10,507 | 366 | import os
aff = os.sched_getaffinity(0)
print('**********************before import torch******************************'+str(aff))
import torch
print('**********************after import torch******************************'+str(os.sched_getaffinity(0)))
os.sched_setaffinity(0, aff)
from DeepPurpose import utils, dataset... |
6a251d31e7d8810af4c2b4d2e9b77f1e69b8672295aefa68fe692b8f5715c2d5 | Python | 10,510 | 366 | import os
aff = os.sched_getaffinity(0)
print('**********************before import torch******************************'+str(aff))
import torch
print('**********************after import torch******************************'+str(os.sched_getaffinity(0)))
os.sched_setaffinity(0, aff)
from DeepPurpose import utils, dataset... |
7a04502e8bf659fb65ed414646869b3ea0d6a1745211848685939bb1edb2b397 | Python | 10,514 | 268 | import argparse
import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
import matplotlib as mpl
from types import SimpleNamespace
import sys
import copy
from pathlib import Path
from cobrawap.pipeline.utils.neo_utils import analogsignal_to_imagesequence
from cobrawap.pipeline.utils... |
3868de85fb38c95fac4b0dca62a9fc89993f8a2147dececb78385c135434fda1 | Python | 10,515 | 284 | import matplotlib.pyplot as plt
import numpy as np
import pickle
import pandas as pd
import seaborn as sns
from scipy import stats
import xlsxwriter as xw
import seaborn
patient_list = ['402','8902','11002','16202',
'21902','26102','30802',
'32702','45402','46702','50802',
'52302','53402','55202','56402',... |
a0a831e86bc55d17dad600518f709c75b45c4da694b276c336162bed66bccfe7 | Python | 10,521 | 286 | """
Tests for Shared Response Model (SRM) algorithms.
Testing philosophy: Property-based tests with mathematical invariants
rather than golden outputs (following BrainIAK, PyMVPA, Hypertools best practices).
Based on research documented in claude-guidelines/srm-hyperalignment-testing-strategy.md
"""
import pytest
im... |
89eb28498064dc7dc869d48ed973a05e9495680caa14b38c428e8ee501635f17 | Python | 10,523 | 359 | """
dFC class
Created on Jun 29 2023
@author: Mohammad Torabi
"""
import numpy as np
from .dfc_utils import (
SW_downsample,
node_info2network,
node_labels2networks,
rank_norm_dFC_dict,
visualize_conn_mat_dict,
)
################################# DFC class ######################################
... |
f9ce9ad22836f04f0e8bc04238341f9d40e777bb4785fac58ec97f497dc5e2c9 | Python | 10,528 | 228 | import numpy as np
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.model_selection import StratifiedKFold
from sklearn.metrics import confusion_matrix, classification_report
from sklearn import preprocessing, linear_model, model_selection, svm, tree, ensemble, neighbors
import pick... |
24a994d0473f22838dd9ba5751a998d448d711ce6351ce342339a8e65b387e1e | Python | 10,545 | 286 | from PymoNNto.NetworkCore.Base_Attachable_Modules import *
from PymoNNto.NetworkBehavior.Recorder.Recorder import *
import copy
blue = (0.0, 0.0, 255.0, 255.0)
red = (255.0, 0.0, 0.0, 255.0)
green = (0.0, 200.0, 0.0, 255.0)
yellow = (255.0, 255.0, 0.0, 255.0)
purple = (255.0, 0.0, 255.0, 255.0)
aqua = (0.0, 255.0, 255... |
f28db706880a6074b4df48f3e460556adab8c43a6021bc7ddd48625b407d385c | Python | 10,548 | 310 | import logging as log
import os
import cv2
import numpy as np
import pandas as pd
import torch
from collagen import Compose, ApplyTransform, Normalize
from solt import core as slc, transforms as slt, data as sld
def parse_metadata(entry, metadata):
n_segments = 4
mean_bmi = 28
mean_age = 60
mean_woma... |
3eb0c53189e4f08387275956776b36c5ac2533038fe45421da35aa10a7b00c40 | Python | 10,554 | 273 | # Copyright 2020-2025 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
import os
import logging
import tempfile
import tests.end_to_end.utils.exceptions as ex
import tests.end_to_end.utils.helper as helper
import tests.end_to_end.utils.ssh_helper as ssh
log = logging.getLogger(__name__)
# Define the Collabo... |
c55a7d39b7eaabf21ff3d12fa00b92fc33a70e7c1e4eab0546e0e6eeb7b7d102 | Python | 10,560 | 298 | import os
import torch
import numpy as np
from abc import ABC
from typing import Union, Optional, Iterable, Dict
from .nodes import Nodes
from .topology import AbstractConnection
class AbstractMonitor(ABC):
# language=rst
"""
Abstract base class for state variable monitors.
"""
class Monitor(Abstr... |
66ce66ea79cfb58a7cca8a969d4523445b74d80cb5a562243f9a14e985dc4613 | Python | 10,561 | 317 | import os
import copy
import numpy as np
import cloudvolume as cv
from cloudvolume.lib import Bbox
from torch.nn.functional import interpolate
from corgie import layers
from corgie import exceptions
from corgie.log import logger as corgie_logger
from corgie.mipless_cloudvolume import MiplessCloudVolume
from corgie.... |
90983401be46fb69fc0fd300d4d5331d087ddfd51b31368fce96e377e73300da | Python | 10,566 | 205 | import os
import torch
import hydra
from omegaconf import OmegaConf
from sklearn.metrics import roc_auc_score
from benchmarks.xgraph.gnnNets import get_gnnNets
from benchmarks.xgraph.utils import check_dir, fix_random_seed, Recorder, perturb_input
from benchmarks.xgraph.dataset import get_dataset, get_dataloader, SynG... |
ece158ac6d61aba4cfcadc14690f95c0bc94450c456be6697ba9becc040e6142 | Python | 10,569 | 288 | # Method signatures differ between Qt bindings, so overrides can't match them all
# pyright: reportIncompatibleMethodOverride=false
import logging
from importlib import metadata
from pathlib import Path
from qtpy import API_NAME
from qtpy.QtCore import Signal # type: ignore[reportPrivateImportUsage]
from qtpy.QtCore ... |
e3aded1d93264d67ce6eff1395efb7ead30d33537980e1670b067666208cb345 | Python | 10,578 | 239 | """Build the tiny ``MagneticScaleShiftMACE`` anchor by direct instantiation.
The magnetic family is a full parallel model stack -- its own models, its own
interaction and product blocks, its own derivative kernels
(``compute_forces_magforces``, ``compute_forces_virials_magforces`` in
``mace/modules/utils.py``), its ow... |
6188f0e86bda4e4eab0ea34bccf9cd5d86a3bb7ceb6f1b764d88bf0d254bc339 | Python | 10,581 | 245 | import os
import torch
import numpy as np
import pandas as pd
import pickle
from utils import resize, normalize, load_config, save_pickle, CustomSummaryTracker
import init_training
import argparse
def train(dataset, models, training_pipeline, logging, cfg):
# Unpack
trainloader = dataset['trainloader']
exa... |
9614eb5c05f40c0803afecf93fb4a8e463789db2f154534c5514f700c1c01a14 | Python | 10,583 | 333 | import os
import torch
import numpy as np
import argparse
import matplotlib.pyplot as plt
from torchvision import transforms
from tqdm import tqdm
from bindsnet.datasets import MNIST
from bindsnet.encoding import PoissonEncoder
from bindsnet.models import DiehlAndCook2015
from bindsnet.network.monitors import Monito... |
ef069f4c05e0ce3d14707bb17ab20ea856f29f3d4224c167d3f0cde60074f408 | Python | 10,584 | 289 | from typing import Optional, Tuple, List, Iterable
import os
import torch
import numpy as np
import shutil
import zipfile
from urllib.request import urlretrieve
from scipy.io import wavfile
import warnings
class SpokenMNIST(torch.utils.data.Dataset):
# language=rst
"""
Handles loading and saving of the... |
16befb013b99d5b068682bbb01562ad4d462ff998f00e06399a33f86801b2bb0 | Python | 10,585 | 250 | # This file is a part of the `nequip` package. Please see LICENSE and README at the root for information on using it.
import torch
import lightning
from lightning.pytorch.callbacks import Callback
import ase
from nequip.data import AtomicDataDict, to_ase
from nequip.data import (
_register_field_prefix,
regis... |
a608b4882920939998a311d62209223ef5970efb69a364c938ba88110eeb6adf | Python | 10,588 | 223 | # Modified from DeepMind repo https://github.com/deepmind/kfac-jax/2022
# Copyright DeepMind Technologies Limited. All Rights Reserved.
#
# 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 at
#
# ... |
ea85d7a406a3a2cb6ea551222ce8e7c4f36b24e42b5d718285661a7877d376ec | Python | 10,588 | 234 | """J calls the junction itself contradicts (#681).
A junction carries the J's own evidence: its 3' end is templated by the J germline, so a record's J
call can be checked against the sequence the same record reports. Match the junction's 3' end -
**the anchor excluded**, so a corrupt anchor cannot vote on its own diag... |
b866c235f87ad1d8bfab158d3cf3cd897d6ac5d6726c0610a90b23d4b0fc853f | Python | 10,589 | 254 | # Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
#
# 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 at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Un... |
3954adf4a764a93769f331cf77bb0f811e1aa6d31a5fd7d764347ae68fdd430c | Python | 10,591 | 282 | """
Tests for nltools.datasets module
This test file covers:
- download_nifti: Basic file downloading functionality
- fetch_neurovault_collection: Main collection fetching function
"""
import pytest
import polars as pl
import tempfile
import os
from unittest.mock import patch, MagicMock
from nltools.datasets import ... |
667c7be3638f305ded428d0c354c2f7b7850853f76dbd5296bc0f4d483e52564 | Python | 10,592 | 275 | import numpy as np
import scipy.sparse as sp
import tensorflow as tf
import os
import psutil
flags = tf.app.flags
FLAGS = flags.FLAGS
"""
Disclaimer: functions defined from lines 18 to 54 in this file come from
the tkipf/gae original repository on Graph Autoencoders. Moreover, the
mask_test_edges function is borrow... |
4bb4ef45e6a74f8d5c3f95dc5daef21662e88c56def39cb7569fc1e29df2feb5 | Python | 10,593 | 269 | from threading import Lock
from chromadb.segment import (
SegmentImplementation,
SegmentManager,
MetadataReader,
SegmentType,
VectorReader,
S,
)
import logging
from chromadb.segment.impl.manager.cache.cache import (
SegmentLRUCache,
BasicCache,
SegmentCache,
)
import os
from chromad... |
66bcf9390c1a7d51a4860712979d677b89cabc0edf95c64334dae291ae80dd7a | Python | 10,598 | 228 | """The identity invariants, as checks over a built directory.
``ROADMAP.md`` section 10.5 names seven. Six of them are properties of a build and live here; the
seventh, that a permuted chunk order changes no id, is a property of two builds and lives in
``tests/unit/test_identity_levels.py`` where it runs on a small fi... |
c0132dea411ec77943da9fddf0d9bd450b458e8e99cb84de961745bbcefdf7ab | Python | 10,599 | 279 | # -*- coding: utf-8 -*-
import sys
import os
import random
import subprocess
import numpy as np
"""
example running 10 reps of 10kb sims with migration from pop 1 to pop 2 (change donorPop to 2 to reverse the order):
python runAndParseSlim.py introg.slim 10 10000 1 introg.log 1> test.ms 2> test.log
output:
introg.log ... |
b934072830b0a1365e2fa08a0788430666c8c74fd81e42ffeef03a0d4d4fdc2e | Python | 10,601 | 204 | import os
import torch
import hydra
from omegaconf import OmegaConf
from sklearn.metrics import roc_auc_score
from torch_geometric.utils import add_remaining_self_loops
from dig.xgraph.method import GradCAM
from dig.xgraph.evaluation import XCollector
from dig.xgraph.dataset import SynGraphDataset
from dig.xgraph.util... |
c607718746afedf5e38cd88b8844cd9b5ed8d8b878512f46c66f407bd3296e31 | Python | 10,613 | 206 | #!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Thu Aug 3 19:21:51 2023
@author: benozzo
"""
import scipy.stats as stats
import numpy as np
from function_library import spearman_rank_permutation
def symm_level(ec, sparsified=False):
#compute the symmetry level by the spear corr row/col
#sparsif... |
531e8cb64f6a159024cb3bb04fa6dd259f81c6a4da725538d534acaa14093f3c | Python | 10,627 | 312 | # copyright (c) 2021 PaddlePaddle Authors. All Rights Reserve.
#
# 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 at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... |
c0a9d859315d658819314c25fad8d476aa5f8ec56e24bd44be226574e45dcbd0 | Python | 10,629 | 293 | # ==============================================================================
# Copyright 2025 Technical University of Denmark
# Author: Nikolas Borrel-Jensen
#
# All Rights Reserved.
#
# Licensed under the MIT License.
#
# Used for 2D data only: converting from high spatial/temporal resolutions to lower resolutions... |
0377abd2486bee1bd0e18fbb85f6992656e0a1d3ff78580060dde45d35c7623f | Python | 10,637 | 250 | import argparse
import torch
import torch.nn as nn
import torch.optim as optim
import pandas as pd
import numpy as np
from sklearn.model_selection import KFold
from sklearn.model_selection import train_test_split
from sklearn.metrics import precision_recall_curve, roc_curve, auc
from torch.utils.data import DataLoader
... |
c82c104a30ec92dae3b7655056d21f31f0df37a37d3de2f2f5f0b96d2434d29c | Python | 10,650 | 364 | """
These tests check Sniffles BND calls/leads against the HG008 and HG002 dataset.
Requires the BAM file to be present at the path specified in BNDLeadTestCase.bam_file. The BAM file should be indexed and contain the necessary tags (e.g. NM).
"""
from typing import Tuple
from unittest import TestCase
import pysam
f... |
06af0d19ae3734cafe50484edd02e6d53221ffdc4513a1eb386b50ff8601804b | Python | 10,651 | 315 | """Prepare and process graph-structured data.
Lead author: Hadi Zaatiti.
"""
import logging
import random
import geomstats.backend as gs
from geomstats.geometry.poincare_ball import PoincareBall
class Graph:
"""Class for generating a graph object from a dataset.
Prepare Graph object from a dataset file.
... |
575faa42a4f079cb2a3afc5f93cd25ce0ac6785c3d3ed3af0613621475b4ec7f | Python | 10,674 | 259 | """
Refer from https://github.com/rusty1s/pyg_autoscale/blob/master/torch_geometric_autoscale/models/base.py
"""
from typing import Optional, Callable, Dict, Any
import torch
from torch import Tensor
from torch_sparse import SparseTensor
from dig.lsgraph.method.FM import FeatureMomentum
from ..pool import AsyncIOPoo... |
dcf8953035066621c5795a16d9f71a40d91890b2cc03324ff5788ab77bdebf21 | Python | 10,706 | 303 | import os
aff = os.sched_getaffinity(0)
print(
"**********************before import torch******************************" + str(aff)
)
import torch
print(
"**********************after import torch******************************"
+ str(os.sched_getaffinity(0))
)
os.sched_setaffinity(0, aff)
from DeepPurpose... |
c610faf09b106b66aff288629d17dd4a3011bd62eddfffecafa64bcc28a521ed | Python | 10,717 | 209 | import os
import nibabel as nib
import pandas as pd
from tqdm import tqdm
def group_patient_visit(df):
# IDs = df['PTID'].unique().tolist()
# projects = ['axial', 'sagittal', 'coronal']
# rows = []
# for ID in IDs:
# row = {}
# missing_data = False
# for i, project in enumerat... |
62fee15a39f517f2761a794a22b1dceb4b62d673ff256010ee9756ad8632c959 | Python | 10,719 | 372 | """Wrapper around autograd functions to be consistent with backends."""
import autograd as _autograd
import autograd.numpy as _np
from autograd import jacobian
def _get_max_ndim_point(*points):
"""Identify point with higher dimension.
Same as `geomstats.vectorization._get_max_ndim_point`.
Parameters
... |
9799134390372421cac9c261ec839e211e896df5cc2521aa74c140d072fbac4f | Python | 10,719 | 248 | """Experiments for interpretability theory.
These experiments evaluate the ability of common interpretability methods
to infer the behaviour of real models on real data.
This class is used to store the base information needed to understand the
experiment. It will be inherited by downstream classes that instantiate it... |
2d17eb5c0041e11212a0c61761e7f91a55d5c311f6935f82e76447300ada7798 | Python | 10,729 | 246 | """Verify the rendered dashboard fragment before it reaches ``vdjdb-web``.
uv run python summary/check_summary.py [fragment.html] [--baseline summary/fingerprint.json]
uv run python summary/check_summary.py --write-baseline
There is no committed image baseline -- ``.gitignore`` excludes ``summary/*.html`` -- ... |
453c771fd0d0fdb813a2c82a2c5e8b1ba52dd9a4cdcb11018ea27b765cd3ae7e | Python | 10,729 | 319 | """Write and read one SanPy intracellular recording as an NWB file."""
from __future__ import annotations
from datetime import datetime
import json
import os
from pathlib import Path
import tempfile
from typing import Any
import numpy as np
from pydantic import BaseModel, ConfigDict, field_validator
from pynwb impor... |
3cf31a8a5a4b688254b1d4dcd6151ecde2ce01616df6c399f64c7a5a1c06041e | Python | 10,733 | 331 | #!python3
"""
Python 3 wrapper for identifying objects in images
Requires DLL compilation
Both the GPU and no-GPU version should be compiled; the no-GPU version should be renamed "yolo_cpp_dll_nogpu.dll".
On a GPU system, you can force CPU evaluation by any of:
- Set global variable DARKNET_FORCE_CPU to True
- Set ... |
406c8617bb661e664f7ea4653bfdeb29e2c54fc603e0e84a4bcbe3fc0856e80e | Python | 10,733 | 263 | import logging
import warnings
import numpy as np
from qtpy.QtCore import Qt, Signal # type: ignore[reportPrivateImportUsage]
from qtpy.QtGui import QKeyEvent
from qtpy.QtWidgets import (
QAbstractItemView,
QCheckBox,
QHBoxLayout,
QHeaderView,
QLabel,
QSpinBox,
QTableWidget,
QTableWidg... |
f40683c9a0b22334163b3e6405f396669282a7a01b05707bf6ddacbae7ffb94b | Python | 10,735 | 276 | import os
import numpy as np
import wandb
import pandas as pd
from wandb.apis.public import gql
import re
import json
api = wandb.Api()
def _get_runs(project_name, entity='schroedinger_univie'):
query = gql(
"""
query Runs($project: String!, $entity: String!) {
project(name: $project, entityName: $... |
49f2552c46507b69efaabe8ac30e4e7884a45058ddb3717dd80bf4d04d6cbac1 | Python | 10,744 | 284 | # -*- coding: utf-8 -*-
"""
Created on Tue May 18 12:25:43 2021
@author: nicol
"""
import os, glob, tqdm
from skimage.io import imread, imsave
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import rc
import matplotlib as mpl
import pandas as pd
import seaborn as sns
import scipy.ndi... |
7d04df042febe07680a20c0019e453a3c94e39c0d8578e3d6c68ced3b19cd9b6 | Python | 10,751 | 271 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# OS stuff
import os
import sys
import warnings
from pathlib import Path
# Computational stuff
import numpy as np
import matplotlib as mplb
import matplotlib.pyplot as plt
from matplotlib.gridspec import GridSpec, GridSpecFromSubplotSpec
from matplotlib import font_manag... |
5f9a6e30b02a165fdac9e7dfc148efd859f407edfcbff777b3d7492a0a9f46b2 | Python | 10,756 | 337 | from pathlib import Path
import imageio
import numpy as np
from split_dataset import EmptySplitDataset
from fimpy.loading import loading_function
from fimpy.pipeline.common import run_in_blocks
from fimpy.loading.utilities import _stack_from_tif, _imshape_from_tif
@loading_function
def load_volumetric(
data_dir,... |
a779ff8b34c4171bd1e16e9dd121961e0494bfa60e8e43ad4d876694e6c8bd02 | Python | 10,756 | 273 | import numpy as np
from numpy import ndarray
from scipy.spatial import KDTree
from model_angelo.utils.misc_utils import assertion_check
from model_angelo.utils.residue_constants import restype_3_to_index
class MatchToSequence:
def __init__(
self,
new_sequences,
residue_idxs,
seque... |
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