sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
770799d961a863848b30720e86c829ae9c5087a57335a8b5ea020d3ecdfc74a9 | Python | 10,398 | 273 | import torch
from base.base_fits_manager import BaseFitsManager
from .tracker import MetricTracker
class Baseline_Fits_Manager(BaseFitsManager):
'''
Baseline fits managers
'''
def __init__(self, config, train_data_loader, valid_data_loader=None, test_data_loader=None):
'''
Initialize t... |
34140fdde39ff3995da4f63824d882ec5d64f81fae6cbc30594770c288492e1a | Python | 10,403 | 230 | """Output parity for the midsagittal-fitter speedups.
The optimisations here are pure caching: work that was repeated on an array
that never changes within a fit is done once and passed down. The whole value
of that is conditional on the answer being IDENTICAL, so the parity claim is
tested directly rather than a... |
640433c5a68de45942dec48cc86345751fffdcf29fa61005eeb3ecda6f6e3497 | Python | 10,403 | 243 | # -*- coding: utf-8 -*-
"""
Created on Dec 12 2022
@author: BIONICS_LAB
@company: DZNE
"""
import sys
sys.path.append('../')
import matplotlib.pyplot as plt
from scipy.signal import butter, lfilter
import h5py
import pandas as pd
import LFP_Denoising as LFP_denoising
import Spikes_Denoising as Spikes_Denoising
import... |
ddc01439fcd4fb7fc35ea87c85bd3f655fc5d9987bc78a68713ec18bf6b9bf20 | Python | 10,403 | 198 | # -*- coding: utf-8 -*-
"""
Created on Dec 12 2022
@author: BIONICS_LAB
@company: DZNE
"""
import numpy as np
import os
import h5py
import matplotlib.pyplot as plt
"""change these parameters based on different datasets"""
SpikesMax = 15 # (Hz) - maximum acceptable Spikes Rate(Spikes events/min)
SpikesMi... |
63a6274da2d38554adf84321b17bc26b0f964e819b866f3578e06d6cd16043eb | Python | 10,404 | 246 | import pandas as pd
import numpy as np
import math
from copy import deepcopy
from kipoi.data import Dataset, kipoi_dataloader
from kipoi_conda.dependencies import Dependencies
from kipoi.specs import Author
from kipoi_utils.utils import default_kwargs
from kipoiseq.transforms import ReorderedOneHot
deps = Dependencie... |
ca5604fcc4d5a13e7d24352c537738fc177516b8ec48ea9f41585e7979cd7a63 | Python | 10,404 | 271 | import os
import yaml
import numpy as np
from tqdm import tqdm
from typing import Dict, Any, List
import logging
import torch
import tensorflow as tf
from tensorflow import keras
import numpy as np
from huggingface_hub import hf_hub_download
from fastglioma.inference.run_inference import FastGliomaInferenceSystem
fro... |
1cc0053afe9091087a9314db9e29f773a0dd0fedbe3c542c43ee5ef2b64deaf7 | Python | 10,405 | 270 | """Aalen–Johansen estimation for right-censored competing risks."""
import numpy as np
from numpy.typing import ArrayLike
from SurvivalEVAL.nonparametric_estimator.util import _predict_step
class AalenJohansenCompetingRisks:
"""
Estimate survival and cause-specific cumulative incidence functions.
The e... |
65d7aa9e885c43d1f2a898b8eccc78a3d034a3a9925f7e375e551ae079b18170 | Python | 10,405 | 254 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# 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 applicab... |
63d93346f1be3b4720a46b4e25fbc3ef284060ee3920019a77d8c55c30ad87f0 | Python | 10,410 | 239 | """Module for PREP pipeline."""
import mne
from mne.utils import check_random_state
from pyprep.find_noisy_channels import NoisyChannels
from pyprep.reference import Reference
from pyprep.removeTrend import removeTrend
from pyprep.utils import _set_diff, _union # noqa: F401
class PrepPipeline:
"""Early stage pr... |
1bf5d39e7a9a6c4983191e98ea0260bd7aa51f0e210a7e562829c8b63474aa8a | Python | 10,411 | 229 | from __future__ import print_function,division
import sys
import os
import glob
import pandas as pd
import numpy as np
import argparse
import topaz.utils.star as star
import topaz.utils.files as file_utils
from topaz.utils.conversions import mirror_y_axis
from topaz.utils.data.loader import load_image
name = 'conve... |
d205138f820405ad3eacb5a0b38bc6ce94d3a8ea5783d3a4ecfbe67a105af571 | Python | 10,411 | 268 | """
Generates a ListTomoParticle object from a input STAR file
Input: - STAR file for pairing STAR files with particles and particles shapes
Output: - A ListTomoPaticles pickled object for every STAR file row
"""
################# Package import
import os
import numpy as np
import scipy as sp
import ... |
542f6478d9be8945a4de375d0ced64d95af832dea398bfcc50dbb7dbc0140f29 | Python | 10,415 | 267 | import sys, gzip, bisect
def sortedFlankingPositionsByDistToTargSite(targetPos, flankingPositionsToExamine, desiredNumPositions, physLen):
i = 1
sortedFlankingPositions = []
while len(sortedFlankingPositions) < desiredNumPositions:
lPos = targetPos - i
rPos = targetPos + i
if lPos >... |
726119f16dc544b8f0e3aa4385500b7147ff921fd01301e4399a8bf0484533cc | Python | 10,416 | 293 | import logging
import math
import os
import pandas as pd
from cirrocumulus.diff_exp import DE
from cirrocumulus.ot.transport_map_model import read_transport_map_dir
from cirrocumulus.util import dumps
from .data_processing import get_filter_str, get_mask, get_selected_data
from .envir import (
CIRRO_DATABASE_CLA... |
3addb3bd85cef8f9acf8f113f9bcec4241194583bcbce3f4f5dbd5244f2e5700 | Python | 10,418 | 246 | #!/usr/bin/env python
# ================================================================
# Copyright (C) 2022 Yufeng Liu (Braintell, Southeast University). All rights reserved.
#
# Filename : find_break_crossing.py
# Author : Yufeng Liu
# Date : 2022-04-01
# Description :
#
# =========... |
dc5791ef6b32d5e9e82021b47c0699ab1468a8447cb60ff536b3c0ef2b5cd32c | Python | 10,418 | 330 | """HDL generators for VHDL and Verilog code generation.
This module provides concrete implementations for generating VHDL and Verilog code.
Each generator encapsulates language-specific factories and provides a unified interface.
"""
from enum import Enum, auto
from typing import Literal, Protocol, overload
from ela... |
6e06db7b14054afb84cd2e733f5cd4e43381a4992cd6497932c220aae004974b | Python | 10,419 | 284 | ##
import APT_interface
import h5py
import tensorflow as tf
from multiResData import *
import localSetup
import os
import PoseUNet
import subprocess
import copy
import json
import copy
from matplotlib import cm
import matplotlib.pyplot as plt
import APT_interface
import datetime
import ast
import argparse
import pic... |
becf67ec683ebe03bdb35973b1dd15206f40288fd5ac72090d9bc7ef269286e8 | Python | 10,426 | 266 | """Tests for regtools.ccf_boundary_editor.io."""
from pathlib import Path
import numpy as np
import pytest
def _two_region_annotation():
ann = np.zeros((3, 30, 30), dtype=np.int32)
ann[:, :, :15] = 1
ann[:, :, 15:] = 2
return ann
def _dragged_state_for_slice(annotation, z):
fro... |
e989727029d1314cfd1f0cf3cdd97bd94fc9d564190ea242456bec32f84f241c | Python | 10,426 | 281 | import torch
from torchvision import transforms
from torch.optim import *
from models import *
import numpy as np
from torchvision import datasets
from torch.utils.data import DataLoader
from torch.autograd import Variable
import torch.nn.functional as F
import os
from utils import Logger, AverageMeter, accuracy, mkdi... |
271c046f55850a06764833ba51fbbc8049faee5027e55ec8f9da806fad41a058 | Python | 10,427 | 266 | import SimpleITK as sitk
import pandas as pd
import tempfile
import numpy as np
import boto3
import nibabel as nib
import os
import botocore
from data.constants import *
from exceptions.exceptions import *
def readCSVS3(data_key):
'''
args: data_key - string containing path to csv file within the ... |
a4cca2d67da77dda3bc732d586674ebc8cb520db76ec76ea849363eef31c5a52 | Python | 10,429 | 292 | """Cache Management
"""
import hashlib
import json
import logging
import os
from pathlib import Path
from typing import Any, Dict, List, Optional
from pip._vendor.packaging.tags import Tag, interpreter_name, interpreter_version
from pip._vendor.packaging.utils import canonicalize_name
from pip._internal.exceptions i... |
a6ddf0520f75c03091d7db8fbee7d298f5e774d4ea3f9c8ad2cb3175fd07ceba | Python | 10,432 | 248 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon May 22 12:39:05 2023
@author: felipe
"""
import sys
import os
directoryKNP='../../'
sys.path.append(os.path.abspath(directoryKNP))
import plot.networks as pltn
import analysis.connectivityMatrices as connectivityMatrices
import numpy as np
import matpl... |
7fd9c62563517795ad42525c2e4410e43fa7d7501da5b18a691f3406bc769df4 | Python | 10,434 | 311 | import os
import numpy as np
from scipy.spatial.distance import squareform, pdist
from scipy.stats import spearmanr
import seaborn as sns
import matplotlib.pyplot as plt
import matplotlib.cm as cm
from utils import build_morpho_dict, make_dir, mannwhitneyu_print, \
null_color, pickle_load, plot_mor... |
808a4cc9cd5888ad815cb9f6b9e2e78e569403e1a3a2cd31adb4d3ff610f98db | Python | 10,434 | 355 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# 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 applicab... |
f9dce5440758b3951d421b90e3d80a7da9e0d6b54972bc465aee6a47c83abb94 | Python | 10,434 | 259 | # Node-group asset "ID Outline" (CompositorNodeTree), dumped by nodebpy.assets.dump_library.
# Rebuild the library with nodebpy.assets.build_library (nodebpy build).
# _build_group() is the source of truth: the docstring, __init__ and accessors are regenerated from it on the next dump.
from typing import TYPE_CHECKING
... |
ba26fcdcf4eab5cf3eb86ae87b178f347503121c865c903908cc68384d22b132 | Python | 10,436 | 268 | """
Generates a ListTomoParticle object from a input STAR file
Input: - STAR file for pairing STAR files with particles and particles shapes
Output: - A ListTomoPaticles pickled object for every STAR file row
"""
################# Package import
import os
import numpy as np
import scipy as sp
import ... |
607c1175d24f67749420130ba04e694857d5ff42352ed578698f2969eca1503d | Python | 10,437 | 281 | #!/usr/bin/env python
#================================================================
# Copyright (C) 2023 Yufeng Liu (Braintell, Southeast University). All rights reserved.
#
# Filename : ds_matrix_condense.py
# Author : Yufeng Liu
# Date : 2023-02-08
# Description :
#
#============... |
215566012c0ffc8dd843666ec5e9f434be3c717f35e978971c9da733bc3e5084 | Python | 10,439 | 288 | import logging
import os
import random
import string
import time
import unittest
import neurolib.utils.paths as paths
import neurolib.utils.pypetUtils as pu
import numpy as np
import pytest
import xarray as xr
from neurolib.models.aln import ALNModel
from neurolib.models.fhn import FHNModel
from neurolib.models.multim... |
7baa2889cbfed16d00e72af3198476b5b540ad0afec6280156cc30145e3a9b2e | Python | 10,439 | 179 | # Copyright 2020 Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany
#
# 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
#
# ht... |
716f8ef7ee6e775a809ad06db6b3b3859cdecbc9f338d96bba5f862b6c61bf3f | Python | 10,441 | 251 | print("GRAF is running..")
import os
import torch
import argparse
import errno
import warnings
base_path = os.getcwd() + '/'
dataset_name = 'sampledata'
folder_ext = 'GRAF_results/'
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
warnings.filterwarnings("ignore", category=FutureWarning)
warnings.... |
886b273369f12a5a7bd3632550ca49e88f9e953c89f0f2ab1d2ab5d7868b8223 | Python | 10,443 | 362 | # -*- coding: utf-8 -*-
#
# louvain documentation build configuration file, created by
# sphinx-quickstart on Fri Oct 21 11:26:44 2016.
#
# This file is execfile()d with the current directory set to its
# containing dir.
#
# Note that not all possible configuration values are present in this
# autogenerated file.
#
# A... |
69395e7625190671e0a155674d21afd9ccd3bf8d4fc02d08ee0d6ef8a71faebf | Python | 10,446 | 212 | from typing import Callable, List, Dict, Optional, Literal, Tuple
import torch
from torch import nn
from .base import AtomicModule
from ..layer import EmbeddingLayer, RadialLayer, ReadoutLayer
from ..layer.equivalent import NonLinearLayer, GraphConvLayer, SelfInteractionLayer
from ..utils import find_distances, _scatte... |
9137c7229966820094f396cc5f96dc57ee16ca43102e886e9d001a49a33ab84d | Python | 10,448 | 312 | import torch
import torch.nn as nn
import torch.utils.model_zoo as model_zoo
model_urls = {
'resnet18': 'https://download.pytorch.org/models/resnet18-5c106cde.pth',
'resnet34': 'https://download.pytorch.org/models/resnet34-333f7ec4.pth',
'resnet50': 'https://download.pytorch.org/models/resnet50-19c8e357.pt... |
791db4d3da9382da98bc0a3a12c459e7e080eb6912e102a06bc863de55d00ed5 | Python | 10,449 | 335 | from cgi import print_arguments
from statistics import mode
from traceback import print_tb
from matplotlib.pyplot import axis
import tensorflow.keras as keras
import tensorflow as tf
from function import *
from model import call_model
import argparse
from scipy.stats import pearsonr
'''
入力を受け取る
'''
parser = argparse.... |
eb9f959d2659b25ddd0a5a42c089b4e9f87a242cf73b84baebff50c6e06e77ba | Python | 10,453 | 260 | import os
import argparse
from tqdm import tqdm
import pickle
import torch
import torch.nn as nn
import torch.optim as optim
import numpy as np
import math
import random
import pandas as pd
from sklearn.metrics import mean_absolute_error, r2_score, accuracy_score, roc_auc_score, f1_score
from dataset import MicroData... |
f5fee5d3ad9a9aebd1005efe0969f1e96672fbec9b25c82236fac5df8c2befa8 | Python | 10,453 | 340 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# 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 applicab... |
23c6f3ff8600371545def7a3eecc6684fe604439d89b09d2503b23392aec7fcf | Python | 10,454 | 227 | """Singleton checker that validates reserved HED tag usage rules loaded from reserved_tags.json.
``hed/validator/data/reserved_tags.json`` is a verbatim copy of ``reserved_tags.json`` as published by the HED
specification (section 3.2.8, defined in Appendix A.6). The ``reserved_tags.yaml`` workflow fails when the copy... |
86dafb3007dffa1ec4c06a8217be74d7571165028c204b90f789dd8c103f1670 | Python | 10,458 | 328 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# 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 applicab... |
9977937f0a100e39c8ebf0f50c60feb921f04c4f1b7ac723d38f3526c289b953 | Python | 10,458 | 283 | import os
import os.path as op
from functools import reduce
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import mne
from scipy import stats
from params import BIDS_ROOT as bids_root
from params import TEMPLATE as template
from params import PLOT_DIR as plot_dir
from params import EXTENSION... |
4d9efd011e3c1711e04f23d1bef2db3f9a22624221e59bca7bdba2de0cebdf9d | Python | 10,459 | 268 | """
Generates a ListTomoParticle object from a input STAR file
Input: - STAR file for pairing STAR files with particles and particles shapes
Output: - A ListTomoPaticles pickled object for every STAR file row
"""
################# Package import
import os
import numpy as np
import scipy as sp
import ... |
af297c7d8d6e2b19831bac516600b17396d76a00386bff0c9d34284593c505f0 | Python | 10,459 | 347 | #!/usr/bin/env python
# coding: utf-8
# ## Analysis of feature selection results
#
# We tried a few different feature selection methods for mutation prediction:
#
# * mean absolute deviation
# * pan-cancer univariate f-statistic (on training data, separate samples into mutated/not mutated and do an f-test)
# * media... |
4f8e85bc2252bd82f2b906b94f608973a73661eb627475f627c2268481d634c1 | Python | 10,463 | 314 | import numpy as np
import pandas as pd
import pytest
import scanpy as sc
from anndata import AnnData
import pertpy as pt
@pytest.fixture
def adata(rng):
X = rng.random((69, 50))
adata = AnnData(X)
perturbations = np.array(["control", "target1", "target2"] * 22 + ["unknown"] * 3)
adata.obs["perturbati... |
6eb1348616506a5f89e6af7af1eec9617a6620fe34945b06a6da68582fe59d61 | Python | 10,463 | 267 | # -*- coding: utf-8 -*-
from __future__ import annotations
from typing import List, Optional, Tuple
import torch
import torch.nn as nn
from supar.modules.dropout import SharedDropout
from torch.nn.utils.rnn import PackedSequence, pack_padded_sequence
class CharLSTM(nn.Module):
r"""
CharLSTM aims to generat... |
9b96a9fb04df3e11f111f28da45e4e6f04611debd17cc56736458e17b5896486 | Python | 10,467 | 271 | import csv
import os
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
from matplotlib.colors import LogNorm, Normalize
# Given a dataset stats and results path, load in the DataFrame, merge and filter
def extract_dataset(stats_path, results_path, filter_by, parseparams_f,... |
50e11bf0ffef5bac72a96d05378e97a91e2471637a37bec833fafacd470d93a9 | Python | 10,471 | 375 | from __future__ import division
import numpy as np
import scipy
import scipy.signal
import scipy.optimize
import scipy.special
from scipy.special import factorial
__all__ = ["Morlet", "Paul", "DOG", "Ricker", "Marr", "Mexican_hat"]
class Morlet(object):
def __init__(self, w0=6):
"""w0 is the nondimensio... |
1c8aecf3684993582c796caa2b3a0fad1dc84be80e9d827f8673a6fbb8cab6fc | Python | 10,473 | 257 | import torch
from torch.utils.data import Dataset, random_split, DataLoader
from pytorch_lightning import LightningDataModule
from typing import Any, List, Type
# local imports
from ..colors import Color, Grey
from ..textures import Texture
from ..stimuli import Stimulus
from ..shapes import LShape, TShape, PlusShape, ... |
2f9665135a1b61e162d4be2dce19065928e9b9f2fe71f3b24cca914c41140a64 | Python | 10,474 | 219 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# 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 applicab... |
5b5aa5c213dff21d836bb8b88ccc44fdfdbd3701b09a37c8d44a42730fb8d622 | Python | 10,475 | 313 | ################################################################################
# Copyright (c) 2021-2024, Lawrence Livermore National Security, LLC.
# Produced at the Lawrence Livermore National Laboratory.
# Written by D. Jones <djones@llnl.gov> and UCSD collaborators in listed in CONTRIB.md
#
# All rights reserved.... |
36a6e2a65e74edf16e475f8cfc56d734442959a3ef6f340b61e275660af70032 | Python | 10,477 | 317 | import dill
import numpy as np
import argparse
from collections import defaultdict
from sklearn.metrics import jaccard_score
from torch.optim import Adam
import os
import torch
import time
from models import SafeDrugModel
from util import llprint, multi_label_metric, ddi_rate_score, get_n_params, buildMPNN
import torch... |
bbdafcd76cdbad726e8050f1ac8a3f191c2f3356fd250787361e15e0fc858ca5 | Python | 10,477 | 257 | import torch
from torch.utils.data import Dataset, random_split, DataLoader
from pytorch_lightning import LightningDataModule
from typing import Any, List, Type
# local imports
from ..colors import Color, Grey
from ..textures import Texture
from ..stimuli import Stimulus
from ..old_shapes import LShape, TShape, PlusSha... |
2add8cbfd29353eb63a1403c9ab865b359624045643287090c39144e917437cd | Python | 10,481 | 265 | """ Dispatch logic for all BIFROST tools
Execute using the 'bifrost' executable installed by setuptools
"""
import argparse
import sys
from bifrost.util import SubcommandHelpFormatter
def main():
parser = argparse.ArgumentParser(
description="BIFROST: template building and cross-modal registration",
... |
120ef8dd40ffbbf25c52a2aeb8fbf5e2d9605da94a0b412b445aab747e5655fd | Python | 10,484 | 327 | import numpy
from collections import namedtuple
from time import sleep
import sys
import time #@@@
import numpy as np
from scipy import misc
import cv2
import os
try:
import gi
gi.require_version("Gst", "1.0")
gi.require_version("Tcam", "0.1")
from gi.repository import Tcam, Gst, GLib, GObject
except I... |
9b5c9b6e4181d2099af8eb18edc343cc8fdb3532e89465ddaafcef31e4a90dea | Python | 10,484 | 253 | #!/usr/bin/env python
import os
import argparse
import sys
sys.path.append(os.path.dirname(__file__)+'/..')
from maggie import score, utils, visual
import numpy as np
import pandas as pd
from Bio import Seq
import requests
if __name__ == "__main__":
parser = argparse.ArgumentParser(description='MAGGIE framewo... |
077ae8b588c0ecf606e7b050d80f8a353bf4025ef6b960c6e34104377ee1b972 | Python | 10,489 | 304 | #!/usr/bin/env python
import sys
import re
from datetime import datetime,timedelta
import argparse
from enum import IntEnum
import getpass
parser = argparse.ArgumentParser(description='summary matlab proceeses in top log.')
parser.add_argument('top_log')
args = parser.parse_args()
topfile = args.top_log
# ========... |
6c2a43043df97277084c2f658df87136a6881717c1b278ee17782438942639f7 | Python | 10,489 | 261 | from Functions.f_SignalProcFuncLibs import *
def confidence_ellipse(x, y, ax, color, n_std):
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.patches import Ellipse
import matplotlib.transforms as transforms
"""
Create a plot of the covariance confidence ellipse of *x*... |
6777549ee441aa6eeeec1eb68ced12a07ba1c8d74d6abfba9bd9a4fdcc3c4e8b | Python | 10,492 | 238 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# 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 applicab... |
6c712bf2da3410814f034fc3848c1e69702fade82508a92e3fb712b3d448496c | Python | 10,493 | 289 | #
# Tests for argument_processor module
#
# Copyright © 2026 Ernst Strüngmann Institute (ESI) of the Max Planck Society
#
# SPDX-License-Identifier: BSD-3-Clause
#
from unittest.mock import patch, MagicMock
from acme.argument_processor import ArgumentProcessor
class TestArgumentProcessor:
"""Test suite for Argum... |
49eb809ffe24940d43fd0bb650b10103a9b135605435f734fc5c37d530676867 | Python | 10,496 | 191 | import cv2
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from matplotlib.patches import Ellipse
from scipy.spatial.distance import cdist
class mol_property:
def __init__(self, img, pixel=None, offset_x_nm=0, offset_y_nm=0, len_nm=None) -> None:
if pixel is No... |
da454171f49476ae168410599c6bf56837e5cc950bb14896796a4820c34ee0d9 | Python | 10,496 | 238 | #!/bin/env python3
"""
Command Line Interface
-----------------------
Perform some common tasks for analysing ``ithildin`` results from the command line.
"""
import click
import warnings
from typing import Union
@click.group()
def tools():
pass
@tools.command()
@click.argument("stem", required=True, type=str)
... |
b8203131db3303a208c4f1e94bc58c72bff663f4a28a1aa1e4bf7578c6e1ff7d | Python | 10,500 | 331 | """
=================
Run the full PREP
=================
In this example we show how to run PREP with ``pyprep``. We also compare
:class:`~pyprep.PrepPipeline` with PREP's results in Matlab.
We use sample EEG data from Physionet EEG Motor Movement/Imagery Dataset:
`https://physionet.org/content/eegmmidb/1.0.0/
<htt... |
b5068084b779945113a1e9cb6f00cff526827eb90ac3be9d1b0ee3af9713f0c4 | Python | 10,504 | 346 | import cocotb
import pytest
from cocotb.clock import Clock
from cocotb.triggers import RisingEdge, Timer
from cocotb.types import LogicArray
from cocotb.utils import get_sim_time
import elasticai.creator_plugins.adders as adders
import elasticai.creator_plugins.mac_delta as mac_delta
import elasticai.creator_plugins.m... |
753e704ee0e69466048425de416611456cdaa509c627818dcb093df9e75db89c | Python | 10,507 | 233 | import torch
from core.utils import convert2cpu
def parse_cfg(cfgfile):
blocks = []
fp = open(cfgfile, 'r')
block = None
line = fp.readline()
while line != '':
line = line.rstrip()
if line == '' or line[0] == '#':
line = fp.readline()
continue
... |
78671bad014aa3d3ecba95932845c3448e2eeb1531688f4f6db06ad220b2acde | Python | 10,509 | 515 | from __future__ import annotations
from typing import Iterable
import numpy as np
import pandas as pd
# ======================================================================
# DEFAULT COLUMN NAMES
# ======================================================================
DEFAULT_CLUSTER_COLUMN = "cluster"
DEFAULT_P... |
5bf4166a7a1de81cebec565ac27349c9537a7b98a1276e79f16297b9d8c54f6a | Python | 10,511 | 315 | from __future__ import annotations
from typing import Iterable
import pandas as pd
from joblib import Parallel, delayed
from sklearn.base import BaseEstimator
from sklearn.utils._estimator_html_repr import _VisualBlock
from sklearn.utils.metaestimators import _BaseComposition
from cuppa.constants import DEFAULT_FEATU... |
553d96deb5f649c36cc5f6ff9f36b1732d82a05da9271add88a77030e10a7aa6 | Python | 10,515 | 274 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# 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 applicab... |
ba5a3a6d632ae482f36d270b7ac24bedc55708c1d2b02df063d06f7e72be414b | Python | 10,515 | 357 | from __future__ import annotations
import logging
from pathlib import Path
from typing import TYPE_CHECKING
import numpy as np
from quacc.utils.dicts import Remove
if TYPE_CHECKING:
from typing import Any
from ase.atoms import Atoms
from quacc.types import Filenames, SourceDirectory
LOGGER = logging.... |
e71c162696862c6326edf2cf8998b8f7b9ecea848e4842925bb37147d87d78e7 | Python | 10,520 | 282 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Jan 31 15:56:34 2023
@author: daltonm
"""
import numpy as np
import pandas as pd
import matplotlib
import h5py
from scipy.ndimage import gaussian_filter
from functools import reduce # forward compatibility for Python 3
import operator
from importlib i... |
961d3a856225729bc80bb48be573b9292b950365324f9c670eb31ca3342f531d | Python | 10,525 | 285 | """
Unit tests for regtools/registration/core/laplacian/utils.py
Covers:
- laplacianA1D
- laplacianA2D
- laplacianA3D
"""
import numpy as np
import scipy.sparse
import pytest
# ===========================================================================
# laplacianA1D
# ========================... |
fb5cfde6da10056294c2b9015df23b6eeb863a0eb294f21f5fb3275bd89e02bd | Python | 10,529 | 255 | import os,sys
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
import tensorflow as tf
import logging
logging.getLogger('tensorflow').setLevel(logging.ERROR)
#
# define my own activations to help the gradient optimizer
def dfh_tanh(x):
return tf.math.tanh(x)*tf.constant(0.98, dtype=x.dtype) + x*tf.constant(0.02,dtype... |
685fd4642a47fdcd57563e3aeadf1c3cb0484d16aa877525b5d810f0c1a26032 | Python | 10,530 | 260 | """
Set of tests for Wong-Wang model.
"""
import unittest
import pytest
import numpy as np
import xarray as xr
from jitcdde import jitcdde_input
from neurolib.models.multimodel.builder.base.constants import EXC
from neurolib.models.multimodel.builder.wong_wang import (
WW_EXC_DEFAULT_PARAMS,
WW_INH_DEFAULT_PAR... |
40cf824a95c2bbbb92231e14bca4f852a55172136acc598adf94f1066642a410 | Python | 10,532 | 262 | # -*- coding: utf-8 -*-
import numpy as np
def calc_point2point(predict, actual):
"""
calculate f1 score by predict and actual.
Args:
predict (np.ndarray): the predict label
actual (np.ndarray): np.ndarray
"""
TP = np.sum(predict * actual)
TN = np.sum((1 - predict) * (1 - actu... |
d321b789403aca5b850fe2860b06e2f2db84e24c45407f1217acc413d49ab362 | Python | 10,532 | 238 | #!/bin/env python3
"""
Command Line Interface
-----------------------
Perform some common tasks for analysing ``ithildin`` results from the command line.
"""
import click
import warnings
from typing import Union
@click.group()
def tools():
pass
@tools.command()
@click.argument("stem", required=True, type=str)
... |
bfd86a61637111aef54669add4a0506c5996c164ce2d55ef2f75600e3934d51c | Python | 10,536 | 339 | """
(*)~---------------------------------------------------------------------------
Pupil - eye tracking platform
Copyright (C) 2012-2020 Pupil Labs
Distributed under the terms of the GNU
Lesser General Public License (LGPL v3.0).
See COPYING and COPYING.LESSER for license details.
------------------------------------... |
b9b1f610b2ea6f428948a2468966834ba7bf1d3d10c545be4827c0f66349b957 | Python | 10,539 | 323 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# 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 applicab... |
b53432b2d0184359138a6432c1f5a27d243af41703cd76cb7aacc210e4d26f8b | Python | 10,542 | 225 | """Download the Allen Mouse Brain CCF **2022** annotation and register it as a
selectable atlas variant.
Allen published a revised annotation in 2022 (finer/relabelled structures on the
SAME CCFv3 reference space as the 2017 release). Unlike 2017, they distribute it
ONLY at 10 µm - ``annotation/ccf_2022/annotatio... |
4c7ff74d667d6b7b4b46882e10a81ed5c99f5019f916baf4e680ba559e410c4e | Python | 10,545 | 365 | from tqdm import tqdm
import copy
import jax
import jax.numpy as jnp
import numpy as np
from tqdm import tqdm
import scipy.stats as ss
from collections import namedtuple
import pickle
import logging
from hippo.models.cscg import rargmax
logger = logging.getLogger(__name__)
eps = 1e-14
HMMParams = namedtuple(
... |
88c1d91441be2a7bb5a72ace93f9b2645d513fad557fb8f608e47b2942e0194e | Python | 10,545 | 287 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# 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 applicab... |
05c7ecf638bf0155e9c9b7596219097233e107ccb5fecbbc307530aa9d4d86bb | Python | 10,547 | 252 | import torch
import os
from pytorch_lightning import LightningDataModule
import numpy as np
from lib import utils
import pandas as pd
from torch.utils.data import DataLoader, Subset
def encode_features(df, scaler):
# df must has time index, and sensors as columns
t = df.index
num_sensors = df.shape[1]
... |
7e45265d3d2965a6627b34920c2ffcf2d91e981c96ec4462e948ca7fc8f88b3f | Python | 10,547 | 283 | """Patch SSL with HiDisc pretraining script.
Copyright (c) 2024 University of Michigan. All rights reserved.
Licensed under the MIT License. See LICENSE for license information.
"""
import yaml
import logging
from functools import partial
from typing import Dict, Any
import torch
import pytorch_lightning as pl
impo... |
dc0824e717730d48432bf8a0c0d2801dbef097636ab541237f1ceb53b94893db | Python | 10,547 | 276 | # coding: utf-8
import torch
import numpy as np
def point_form(boxes):
""" Convert prior_boxes to (xmin, ymin, xmax, ymax)
representation for comparison to point form ground truth data.
Args:
boxes: (tensor) center-size default boxes from priorbox layers.
Return:
boxes: (tensor) Conve... |
eaeb449f3455457b37095a7daacc804d0fbf7f521fa2041e7e7230d09a2e1eae | Python | 10,549 | 339 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# 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 applicab... |
da660b717ab2596179f71fdbbe9496167735f204d13579522988a1a4ce7de9d0 | Python | 10,554 | 285 | # encoding: utf-8
import _init_paths
import fire
import time
import pandas as pd
import os
import numpy as np
import torch
import torch.nn as nn
import torch.backends.cudnn as cudnn
import torchvision
import torch.nn.functional as F
from tqdm import tqdm
from collections import OrderedDict
from torch.utils.data impo... |
969c26a41db37c30e930ec9755c3964c537ad11b22d595ccc54067e5069eb236 | Python | 10,556 | 262 | """
Generates a ListTomoParticle object from a input STAR file (light particles version)
Input: - STAR file for pairing STAR files with particles and particles shapes
Output: - A ListTomoPaticles pickled object for every STAR file row
"""
################# Package import
import os
import vtk
import n... |
27c5624ae7f9e6a515dac0c7ff4db91acd4082234c7ea904c132edcbfd4720c4 | Python | 10,561 | 325 | # Node-group asset "Simulate on Faces" (GeometryNodeTree), dumped by nodebpy.assets.dump_library.
# Rebuild the library with nodebpy.assets.build_library (nodebpy build).
# _build_group() is the source of truth: the docstring, __init__ and accessors are regenerated from it on the next dump.
from typing import TYPE_CHEC... |
2fe9771d5171614ca7069a8f07b6b5c94a8f0d7f70f1b4d71a86fa0aafb9fc71 | Python | 10,562 | 349 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# 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 applicab... |
a13f10d8dbb46cfb9b05a93be7f9a78f9ef935efb5cfc00aec642124fed5869b | Python | 10,563 | 251 | # Node group "Score View Directions" (GeometryNodeTree), dumped by nodebpy.assets.dump_library.
# Rebuild the library with nodebpy.assets.build_library (nodebpy build).
# Shared by several assets, which import it; not an asset itself.
# _build_group() is the source of truth: the docstring, __init__ and accessors are re... |
d42f699374a42970808d404150ded59b7f3e025bf2d67a51013d09faaafc3f72 | Python | 10,565 | 265 | """
Joint image+points transforms for the point-reorient tool.
The functions in this module always transform an image array AND a matching
(N, ndim) point array by the same operation, so the spatial relationship
between them is preserved.
Convention
----------
- Image axis ``a`` (i.e. ``image.shape[a]``) cor... |
1f820791864e3522e34c267af02e039d31b1f8d60ed22645d22518dceefde80f | Python | 10,566 | 287 | """Testing CLI command check."""
import os
import subprocess
def test_no_file():
"""Tests for missing file."""
os.chdir(os.path.dirname(__file__) + '/data')
proc = subprocess.Popen(['swc', 'check', 'fail_no_file.swc'],
stdout=subprocess.PIPE,
stderr... |
31a8eba6d491c99d4ac34bfa4b216824e64a31debb26f4805192abd39acb4cf3 | Python | 10,566 | 288 | # -*- coding: utf-8 -*-
"""
Created on Tue Mar 29, 2016
Module:
poibin - Poisson Binomial Distribution
Author:
Mika Straka
Description:
Implementation of the Poisson Binomial distribution for the sum of
independent and not identically distributed random variables as described
in the reference [Ho... |
3b9861d334f65165eb324ecf8cbd170466bdb4ae131f441d80311e927902416e | Python | 10,566 | 290 | import pytest
from torch import nn
from elasticai.creator.file_generation.in_memory_path import InMemoryFile, InMemoryPath
from elasticai.creator.nn.integer.sequential.sequential import Sequential
@pytest.fixture
def sequential_instance(linear_layer_0, relu_layer_0, linear_layer_1):
layers = nn.ModuleList()
... |
a23367654ff7c0db92de52bb2fbc2bda17020c8a5b8e2e595192732cd3adbad7 | Python | 10,572 | 237 | from collections.abc import Sequence
import torch
from torch import nn
from torch import autograd
from torch_scatter import scatter_add
from torchdrug import core, layers, utils
from torchdrug.layers import functional
from torchdrug.core import Registry as R
from . import layer, geometry
@R.register("models.BindM... |
c0631ee3427c2821a04283342f28d112b986224bf66ec600ef54425d3843d311 | Python | 10,574 | 308 | from typing import TYPE_CHECKING, Optional
from .align import AlignMethod
from .box import ROUNDED, Box
from .cells import cell_len
from .jupyter import JupyterMixin
from .measure import Measurement, measure_renderables
from .padding import Padding, PaddingDimensions
from .segment import Segment
from .style import Sty... |
e6f39aa56002368d23f2202284e2e9d96cbbd9f33e17689e24f2b420b7ffbafa | Python | 10,574 | 300 | #!/usr/bin/env python3
"""
Script to process aromatic 13C-1H correlation maps.
Spectra should be recorded with the dedicated pulse programme
Written by D Flemming Hansen
April 2024, flemming.hansen@crick.ac.uk / d.hansen@ucl.ac.uk
Citation: VK Shukla, G Karunanithy, P Vallurupalli, DF Hansen
bi... |
92fe193510822aba863876db196943c6c606fbee1fe24c854e779a699edcee11 | Python | 10,576 | 266 | import torch.nn as nn
import math
import torch
import torch.nn.functional as F
from einops import rearrange
from einops.layers.torch import Rearrange
class PatchEmbedding(nn.Module):
def __init__(self,
num_electrodes: int,
hid_channels: int = 40,
dropout: float ... |
337adaf38e8db40af77a683390016a44fe70c35d6fdf45490feec078ed7780f6 | Python | 10,578 | 294 | """
Utilities for computing per-image evaluations on a FiftyOne dataset using the
Tensorflow Object Detection API.
**Note** importing this module requires an environment variable
`TF_MODELS_RESEARCH` that specifies the path to the
tensorflow [models/research directory](https://github.com/tensorflow/models/tree/master/... |
b3179b4602709b1034eb0aad9e8b3d3874e9a3a216772e4195cd7601684f9b0f | Python | 10,581 | 288 | """Testing CLI command check."""
import subprocess
import os
def test_no_file():
"""Tests for missing file."""
os.chdir(os.path.dirname(__file__) + '/data')
proc = subprocess.Popen(['swc', 'check', 'fail_no_file.swc'],
stdout=subprocess.PIPE,
stderr... |
428c05a60ee2b5c152d07ec1107e5621a45a70ae66476763034174eb0ad3b1fb | Python | 10,590 | 250 | import torch
import random
import sys
import time
import os
import argparse
import numpy as np
class Tee:
def __init__(args, fname, mode="a"):
args.stdout = sys.stdout
args.file = open(fname, mode)
def write(args, message):
args.stdout.write(message)
args.file.writ... |
20489e07a1cc5b4f37795d828d3afd4a15857b79a3306880d8b0c9a20621dae9 | Python | 10,592 | 202 | from pddlstream.algorithms.algorithm import parse_problem
from pddlstream.algorithms.common import add_facts, add_certified, SolutionStore, UNKNOWN_EVALUATION
from pddlstream.algorithms.constraints import PlanConstraints
from pddlstream.algorithms.downward import get_problem, task_from_domain_problem
from pddlstream.al... |
941d80fe8a7dc47ed1c24a724abe53da2312aca45cffa0cb1d4e7fc7ba10932a | Python | 10,592 | 265 | """Validation of the HED tags as strings."""
from hed.errors.error_reporter import ErrorHandler
from hed.errors.error_types import ValidationErrors
from hed.schema.hed_schema_constants import HedKey
from hed.validator.reserved_checker import ReservedChecker
from hed.validator.util.dup_util import DuplicateChecker
cl... |
fde4b08ff2a4942832e08b787ee5198ce23acbc99a827a972d8d2066215a361b | Python | 10,592 | 265 | import torch
import torch.nn.functional as F
import numpy as np
import ABIDEParser as Reader
import argparse
import random
from torch_geometric.data import Data
from sklearn.model_selection import StratifiedKFold
from scipy.spatial import distance
from model_RGAT import RGAT
from sklearn.metrics import roc_au... |
2d5f8562fc1431fef0ab2f27085cb811e53671975c688979a4fed00f0ac475a3 | Python | 10,594 | 462 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Create db from gdf files to be able to then select neuron spike times.
Best use case:
1. run simulation
2. create sqlite db of spike times with indexing
3. use this db many times
Creating index for db will dominate insertions for larger set of spike times.
[TODO] Che... |
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