sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
70265fe9ac3bb30e882971babf683671a1f80845a4ce9e3f782594d3089605d8 | Python | 3,468 | 106 | # -*- coding: utf-8 -*-
# python standard library inputs
import os
# external inputs
import numpy as np
from nibabel.freesurfer.io import read_geometry, write_geometry
def remove_vertex_outliers(input_surf, input_ind, n=5, overwrite=True):
"""Remove vertex outliers.
This function removes outlier ve... |
1a7053a9323dbac42c4fc8c98e5e9898a12f4215e349f46e2da03e752bab1642 | Python | 3,469 | 80 | """Known-answer controls, and the threshold they set.
A match rate means nothing without knowing what the pipeline scores when the
answer is "no match". These controls supply the floor, and the floor is what the
tracking threshold has to clear.
**The shift control must move the ROIs only.** An earlier control transla... |
6f5527fb7ada00925076d78f556fc17ddeeb3dc833c97d4c051a96a275f77921 | Python | 3,469 | 113 | #!/usr/bin/env python
import storm_control.sc_library.halExceptions as halExceptions
import storm_control.hal4000.testing.testActions as testActions
import storm_control.hal4000.testing.testing as testing
import storm_control.test as test
#
# Check the default parameters.
#
class ParamTest1Action(testActions.GetPar... |
445c8ac8042dfd185a07deb70c967d993585f7f195860a4da1de0068b75e2ed9 | Python | 3,471 | 93 | # coding=utf-8
"""
Tests for deepreg/dataset/load.py in pytest style
"""
from typing import Optional
import pytest
import yaml
import deepreg.dataset.load as load
from deepreg.dataset.loader.unpaired_loader import UnpairedDataLoader
from deepreg.registry import DATA_LOADER_CLASS, REGISTRY
def load_yaml(file_path: ... |
940b8ae8ede53665be61999da8cf998a27502c9c535ce4ae6f4c79a845a8b317 | Python | 3,471 | 94 | import json
from chemgraph.agent.llm_agent import ChemGraph
from chemgraph.utils.get_workflow_from_llm import get_workflow_from_state
import argparse
import datetime
def get_query(
reaction: dict,
query_name: str = "enthalpy",
temperature: float = 298,
pressure: float = 101325,
method: str = "mace... |
1e563ee782b9a63a8f54e5a8467862b4b269c92ed86f24b5de0750e0c8b70f88 | Python | 3,472 | 111 | """
SPDX-License-Identifier: MIT
SPDX-FileCopyrightText: © 2022 Renaud Bastien, Stephane Sanchez <stephane.sanchez@ut-capitole.fr>
Université Toulouse Capitole - Institut de Recherche en Informatique de Toulouse
Real Expression Artificial Life (REVA) Research Team
https://www.irit.fr/departement/calcul-intensif-simulat... |
6972ade1db96212c223a824e014dafd8be2a08b02db4e08fcaa0be9d7527389c | Python | 3,475 | 94 | import json
from chemgraph.agent.llm_agent import ChemGraph
from chemgraph.utils.get_workflow_from_llm import get_workflow_from_state
import argparse
import datetime
def get_query(
reaction: dict,
query_name: str = "enthalpy",
temperature: float = 298.15,
pressure: float = 101325,
method: str = "m... |
9a669437ccd32890a28f6ebd3c384ea1cb2601c01b9645979790f1a8f90931d8 | Python | 3,475 | 119 | # -*- coding: utf-8 -*-
# external inputs
import numpy as np
from numpy.fft import fft, ifft, fft2, ifft2, fftshift
def regrid_zero_2d(data_array, nx_new, ny_new):
"""Regrid zero 2D.
This function loads a two-dimensional numpy array and performs spatial
interpolation using zero padding in spatial frequ... |
bbf15a346ab5c85565011b839cdf3fe3208006562724abc5e2fa258509b413ff | Python | 3,475 | 103 | #@ File (label="Reconstruction file (Leave empty for demo)", style="file", required=false) recFile
#@ Float (label="Area per point (spatially calibrated units)^2", value=100) boxArea
#@ String (label="Color mapping:", choices={"mpl-viridis.lut", "mpl-plasma.lut", "mpl-inferno.lut", "cool.lut", "Cyan Hot.lut"}) lutName
... |
7444205a20111d30b61f1497330bd9436e34051a788b6cfab0ac84dad255df68 | Python | 3,476 | 94 | from ..base_loss import *
from .tensor_models import *
import torch as th
import torch.nn.functional as functional
logsigmoid = functional.logsigmoid
softplus = functional.softplus
sigmoid = functional.sigmoid
class HingeLoss(BaseHingeLoss):
def __init__(self, margin):
super(HingeLoss, self).__init__(mar... |
6c614ea901288cb97a0381fdc27815e5801a7dd9a3fdf8298065412ddabc558e | Python | 3,477 | 100 | """OpenRouter endpoint (OpenAI-compatible).
Owns ``openrouter:`` prefix stripping, the ``OPENROUTER_API_KEY`` credential
(never ``OPENAI_API_KEY``), the higher default token budget, and the restricted
optional-parameter set. Logic moved verbatim from ``models/openrouter.py``.
"""
from __future__ import annotations
f... |
cdb213869e66889b7e7a41160f9395d7d0975d59f476e58c45b0775587e341d4 | Python | 3,477 | 109 | import sys
from datetime import datetime
from colorama import Fore
from tqdm import tqdm
class bcolors:
HEADER = '\033[95m'
OKBLUE = '\033[94m'
OKGREEN = '\033[92m'
OKPURPLE = '\033[0;35m'
OKADVISORY = '\033[1;36m'
WARNING = '\033[93m'
FAIL = '\033[91m'
ENDC = '\033[0m'
BOLD = '\033... |
1990be1dfca692d14cfcf27dffb89d8a9c9c6e45d996105cd6eb9d841e72f668 | Python | 3,478 | 96 | from abc import ABC, abstractmethod
from pathlib import Path
from typing import Union, Optional
import numpy as np
from auxiliary.io import read_image, write_image
class Defacer(ABC):
def __init__(
self,
masking_value: Optional[Union[int, float]] = None,
):
"""
Base class for d... |
3f70b1c0abe4e8dee009e61398be605f6ff924f51564987adb0a040b35934343 | Python | 3,478 | 113 | from dataclasses import dataclass, field
from typing import Literal
class BaseConfig(dict):
"""Dict that also supports attribute access (recursively)."""
def __init__(self, *args, **kwargs):
super().__init__()
self.update(*args, **kwargs)
def update(self, *args, **kwargs):
for k,... |
7670585872577ded339036ff7318df4c2d52a3aac20ac529147d88b2ac3e73c9 | Python | 3,478 | 90 | # -*- coding: utf-8 -*-
"""
Functions to remove background in images
The main routine subtracts a morphological opening from the original image
for background removal.
"""
#:copyright: Copyright 2015 by Christoph Kirst, The Rockefeller University, New York City
#:license: GNU, see LICENSE.txt for details.
impor... |
968f2507b7d6d26e4d5aa2082f95eee9de30a84ea5d5c710b9e66cedda81c014 | Python | 3,478 | 92 | import argparse
import os
import os.path as osp
import time
import numpy as np
import torch
import torch.nn.functional as F
from sklearn.metrics import f1_score
import pandas
import json
import torch_geometric.transforms as T
from torch_geometric.nn import ChebConv, GCNConv # noqa
from tqdm import tqdm
parser = argpar... |
da94de29613d495384ec8ae4a24031149798e1a541b96bca0d7323da6a70b098 | Python | 3,478 | 95 | '''ResNeXt in PyTorch.
See the paper "Aggregated Residual Transformations for Deep Neural Networks" for more details.
'''
import torch
import torch.nn as nn
import torch.nn.functional as F
class Block(nn.Module):
'''Grouped convolution block.'''
expansion = 2
def __init__(self, in_planes, cardinality=32... |
91bc126ad3ca8efd0b544bdf729ab363f2fcbc57db59357d00e72f2c27e65bb9 | Python | 3,479 | 76 | from brainscore_vision import load_dataset, load_metric
from brainscore_vision.benchmark_helpers.neural_common import TrainTestNeuralBenchmark, average_repetition, filter_reliable_neuroids
from brainscore_vision.metrics.regression_correlation.metric import ALPHA_LIST
from brainscore_vision.utils import LazyLoad
BIBTE... |
d7300cff5e8c4a30040c8855637383b7314a52d90717a07eb1a7d5d7eb4a8044 | Python | 3,479 | 102 | import pyBigWig
import numpy as np
def read_chrom_sizes(fname):
with open(fname) as f:
gs = [x.strip().split('\t') for x in f]
gs = [(x[0], int(x[1])) for x in gs if len(x)==2]
return gs
def get_regions(regions_file, seqlen):
# regions file is assumed to be centered at summit (2nd + 10th col... |
fed91b86f92b51ede6dde3b73414dc3d390a540e3465c8c442cc36223222113d | Python | 3,479 | 86 | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import numpy as np
from ultralytics.utils import LOGGER
def onnx_calibration_reader(dataset, transform_fn, input_name: str = "images", batch: int = 0):
"""Create an ONNX Runtime calibration data reader from an Ultralytics calibration dataloader... |
3fe61c54202443c7f8886ee6cd8a4fda6358341e0038f2ddbc146e25364fd9f6 | Python | 3,481 | 74 | # Copyright 2025 BDP Ecosystem 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
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... |
43e90e9ddc6c227f0bcf919254550c24a5c9d1efdbb117ec5ab6a3e6f9f4b1eb | Python | 3,481 | 99 | """
Convert the original SeisT detection/picking weights (https://github.com/senli1073/SeisT, ``pretrained/seist_*_dpk_*.pth``)
into the SeisBench weights format.
The original checkpoints were trained on the DiTing dataset at 50 Hz with windows of 8192 samples.
The state dict layout of :py:class:`seisbench.models.Seis... |
8d0ac97d065588287bffb7cbedee0e28e30c8cad692f2b1bf76eb1d8f283fa92 | Python | 3,481 | 129 | import numpy
import tqdm
from sklearn.manifold import TSNE
class _Transform:
def __init__(self):
pass
def fit(self, X):
return self.transform.fit_transform(X)
class tSNE(_Transform):
def __init__(self):
super().__init__()
self.transform = TSNE(n_components=2, verbose=1,... |
96c3e340c42b4530ebbe1ea16dee0255890444a959db8d73da1e5650f0cff67b | Python | 3,482 | 89 | import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from sklearn.svm import SVC
from sklearn.metrics import accuracy_score, confusion_matrix, precision_score, recall_score, f1_score
from sklearn.preprocessing import StandardScaler
import time
from sklearn.decomposition import PCA
import torch
cla... |
b5e89666e8e46f1859c074dec3e3889bb06df2666d0c747510b444e31b7bf339 | Python | 3,482 | 103 | import argparse
import os
from pathlib import Path
import pandas as pd
from tqdm import tqdm
import seisbench.data as sbd
def transcode(data_in, data_out):
dataset_args = {"missing_components": "ignore"}
try:
# Check if dataset is available in SeisBench
dataset = sbd.__getattribute__(data_in... |
9e5d869454545fb3eab1940f1d5efd7b342d4f05ed4241b31ada4cc67ee2b846 | Python | 3,483 | 96 | from importlib import resources
from pathlib import Path
import pandas as pd
import pickle
import numpy as np
from sklearn.preprocessing import StandardScaler
def get_base_path():
return resources.files('resources')
def get_MIST_nii_path():
base_path = get_base_path()
return Path.joinpath(base_path, 'MIST1... |
a83ac8992aa98104ebe8b33976c873857900d7fedca90e8e1b7ebdae37b19883 | Python | 3,483 | 89 | """Get interpretation of PCs and cluster centroids.
Figures 3A, 4A.
"""
import numpy as np
import pickle
from utils import get_closest_farthest_words, get_clusters_dicts, get_vector_top_bottom_word_projections, get_stimulus_word_embeddings, get_pssd
if __name__ == "__main__":
model_type = "fasttext"
pssd = ... |
d6bed62dce972fc1aa5abd4eede8a55bf89173ae5c318145a2b3ea54714aef1a | Python | 3,483 | 135 | """
Random Forest Regression with Train–Test Split
(Cortical Region-wise Analysis)
This script implements Random Forest Regression for EEG-based cognitive workload
estimation using a stratified cortical-region-wise analysis, as described in the study:
"Estimating Cognitive Workload in Robot-Assisted Surgery Using Tim... |
24114cb12e2bd874a5268b3a990760d856049ce5a7d95b8894fa9671c9e9a46b | Python | 3,484 | 38 | import numpy as np
from nilearn.image import load_img
import fire
from nilearn.plotting import view_img
from rich.progress import track
import matplotlib.pyplot as plt
base = "../bids_dataset/derivatives/"
theories = {
"symbolic": "./derive_theoretical_RDMs/symbolic/symbolic_sym_diss_mat.csv",
"IT": "... |
4c705928f545d065ffa049266090247e311a4ec88c7d175e297636c148a610f8 | Python | 3,484 | 93 | import glob
import os
import scipy
from nilearn.image import load_img, new_img_like, smooth_img
from nilearn.plotting import view_img, view_img_on_surf
from nilearn.glm.thresholding import threshold_stats_img
import numpy as np
import pandas as pd
from joblib import Parallel, delayed
from scipy import ndimage
impo... |
e4cc5edeb1af7f1341d716b845de8c29c93af07be75e5533bb284ea4b509ff15 | Python | 3,485 | 99 | from typing import Dict, List, Any, Optional
from abnumber import Chain # conda install -c bioconda abnumber
def _default_scheme(mt: str) -> str:
return "imgt" if mt.upper() == "TCR" else "chothia"
def _chain_letter(mt: str, which: str) -> str:
mt = mt.upper()
if mt == "TCR":
return "B" if which ... |
01ef2e809708da3a721697581cb9727b8e9bd7323a840a062e901ff9bb76e4ea | Python | 3,486 | 111 | import sys
import yaml
import os
import h5py
import numpy as np
save_ratevec = True
smoothingstyle = 'savgol'
pathpath,recfilename,regstr = sys.argv[1:]
regs_of_interest = [bla.strip() for bla in regstr.strip('[]').replace("'",'').split(',')]
badtimesdir = 'ZENODOPATH/preprocessing/bad_times_manual'
recid0 = os.pat... |
20519bfdf088499605c9fe3e13492db03b608ffb8e28f41b57c4fbfe7dd4d11c | Python | 3,487 | 96 | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import scanpy as sc
import ot
from sklearn.metrics.cluster import adjusted_rand_score
from typing import Optional, List, Union
import logging
class ClusterAnalysis:
"""Class for clustering analysis and evaluation."""
@staticmethod
... |
20992043476e6ea2de70fb55d18d89c1ba359230f19830ad63241408e6cb4ef1 | Python | 3,487 | 135 | #!/usr/bin/env python
#
# cleanup.py
#
# copyright F. Nedelec, December 14th 2007
"""
Scan recursively from current directory,
and clean up temporary cytosim files
Syntax:
cleanup.py [walk=1] [commit=1] directory-list
Example:
cleanup.py data*
F. Nedelec, April 2013
"""
import sys, os... |
a05d175731ad3ad226b1d3a4c1750eaf440e436a73f2c8eb2a2b7b4208824234 | Python | 3,487 | 102 | from __future__ import annotations
from typing import Final
import numpy as np
import numpy.typing as npt
from ._model import ORIENTED_RECTANGLE_POINT_COUNT
from ._model import Shape
def _is_full_oriented_rectangle(shape: Shape, /) -> bool:
return (
shape.shape_type == "oriented_rectangle"
and ... |
98ac7154e88ec08f6ba998982bb5b3696ff5a7542c893e94cbe804f514088d17 | Python | 3,489 | 103 | import ast
import numpy as np
from nems.registry import layer
from .base import Layer
class NumPy(Layer):
"""Applies a NumPy operation to inputs.
Parameters
----------
operation : str
Name of `np.{operation}` to apply to data, ex: 'concatenate'.
op_args : N-tuple; optional.
P... |
1cfbbacff273d4612f9b67b47aed6a5ac7dbcc59aaa1e67d852281c414e1059d | Python | 3,490 | 115 |
import numpy as np
import brainscore_vision
from brainscore_core.supported_data_standards.brainio.stimuli import StimulusSet
from brainscore_core.supported_data_standards.brainio.packaging import package_stimulus_set_locally
from brainscore_core.supported_data_standards.brainio.assemblies import DataAssembly
from bra... |
503bc02faceb0fd5ea9f7a264bca4743fc89012c987e261e93f6f64c9158b600 | Python | 3,490 | 114 | #!/usr/bin/env python3
import arbor as A
from arbor import units as U
import numpy as np
import pandas as pd
import seaborn as sns # You may have to pip install these.
class single_recipe(A.recipe):
def __init__(self, dT, n_pairs):
A.recipe.__init__(self)
self.dT = dT
self.n_pairs = n_pa... |
5ec868883db64d31fb1397bcdf7d86056eea3093bc4fd8217fed3c3503b845fa | Python | 3,490 | 106 | # src/utils/early_stopping.py
"""
EarlyStopping 模块
------------------
封装训练过程中的早停机制，独立于其他工具文件，便于单独配置与调参。
类 EarlyStopping
---------------
监控单个指标（如验证集损失或验证集 MCC），在指标在
patience 个连续 epoch 内未改善时，触发 early_stop=True。
每当指标改善时自动保存当前最佳模型权重。
使用示例
--------
from src.utils.early_stopping import EarlyStopping
early_stopper = Early... |
832575322de6cf118932b9a99c2e892b0ffb32a6dbe6b13a89433cfdfdf799cd | Python | 3,490 | 114 | #!/usr/bin/env python
"""Direct EnsembleLauncherBackend demo on an HPC compute node.
5-molecule thermo screen via the EnsembleLauncher orchestrator,
managed mode (the backend starts and tears down the orchestrator
itself). Must run inside ``qsub -I`` on Polaris or Aurora, in a venv
where ``ensemble_launcher`` is insta... |
99916dcb0c7bc5ee43326c2155461920b997bf2aab5749d51d199d7addf53318 | Python | 3,490 | 110 | #!/usr/bin/env python3
import os
import gzip
import urllib.request, urllib.error, urllib.parse
import inspect
import unittest
import logging
import bt2face
import btdata
import subprocess
from optparse import OptionParser
class TestLargeIndex(unittest.TestCase):
"""
Main fixture for large inde... |
159c2ec2f0a78a1bea6d3e0f7066fb19f2c0205818f09fdb9fa9ecddb35cd846 | Python | 3,491 | 91 | """Tests for the `morphometrics validate` command."""
import numpy as np
import pytest
mrcfile = pytest.importorskip("mrcfile")
from click.testing import CliRunner
from surface_morphometrics.validate import validate_cli, _present_label_values
def _write_seg(path, values):
"""Write a tiny segmentation MRC contai... |
c225d8c776d931d582608f0740bbec1d8f10fadf093901110143db8c419ede97 | Python | 3,491 | 109 | # -*- coding: utf-8 -*-
# python standard library inputs
import os
import datetime
# external inputs
import numpy as np
import nibabel as nb
from nighres.registration import apply_coordinate_mappings
# local inputs
from ..io.get_filename import get_filename
from ..utils.resample_volume import resample_volume
def a... |
d0637bcc9da36e18806a1e28f9a2947d2fccbeaba80f603320c317ac124afb77 | Python | 3,491 | 99 | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
"""Build and smoke-validate export test virtual environments from the exporter registry."""
from __future__ import annotations
import argparse
import os
import shutil
import subprocess
import sys
from pathlib import Path
import psutil
REPO = Path(_... |
becd0740e2397e11007fa21a692d8a2fac3baa92a05b54a1264b91d06dc63e85 | Python | 3,492 | 78 | # #!/usr/bin/env python
# encoding: utf-8
'''
@author: Yang Sui
@contact: yangsui@uw.edu
@ Prerequisite:
module load annotsv/3.4
AnnotSV -SvinputFile annotSV.input.bed -svtBEDcol 4 -candidateGenesFile NDDgene.txt -promoterSize 500 -REreport 1 -outputFile truvariSVsanno
'''
import pandas as pd
import numpy as np
# r... |
3c9b7bb3b8f6fbe4edcce39b278015a55a1bbff1314ad0d5b58c26efbc0070b9 | Python | 3,493 | 84 | import torch
from tqdm import tqdm
from dataset_tool import fast_merge
import numpy as np
from transformers import pipeline, T5Tokenizer, T5EncoderModel
import os
user,tweet=fast_merge(dataset="Twibot-20")
user_text=list(user['description'])
tweet_text = [text for text in tweet.text]
feature_extract=pipeline('featu... |
57f783c949bea81c3b7ca907fbd9b7937827a881adcb9a6ae0c6208ede546af7 | Python | 3,494 | 93 | import json
from chemgraph.agent.llm_agent import ChemGraph
from chemgraph.utils.get_workflow_from_llm import get_workflow_from_state
import argparse
import datetime
def get_query(
reaction: dict,
query_name: str = "enthalpy",
temperature: float = 298,
pressure: float = 101325,
method: str = "mace... |
5bd295d592bd9b747d3b60a1b1019b2b42187f091d1ed4b40510ea719b91628b | Python | 3,494 | 79 | # A script to visualize the ERF.
# Scaling Up Your Kernels to 31x31: Revisiting Large Kernel Design in CNNs (https://arxiv.org/abs/2203.06717)
# Github source: https://github.com/DingXiaoH/RepLKNet-pytorch
# Licensed under The MIT License [see LICENSE for details]
# -----------------------------------------------------... |
e93832a13e4f1b16304d61aa47f4e08d648995939419776d7c0532a8ddbb84e0 | Python | 3,494 | 116 | from collections.abc import Sequence
from typing import TYPE_CHECKING
import pytest
from eir import train
from tests.test_modelling.test_modelling_utils import check_performance_result_wrapper
if TYPE_CHECKING:
pass
def _get_survival_output_configs(type_: str) -> Sequence[dict]:
if type_ == "discrete":
... |
610acee4fdec1316d7caaf9f8f9a59e4cd27f61745a7add7f78769cbf18a6136 | Python | 3,496 | 191 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Process markers_MB-KCc-KCn files
"""
import os
import mbflim.utils as ut
import mbflim.image.image_processing as pro
import mbflim.image.image_set_processing as setpro
import mbflim.visualization as vis
#%% Parameters
study = 'MB-KCc-STn' # 'MB-KCc-KCn' or 'MB-KCc... |
90da10365d7f56a59ec699fc949387c0bc1e7f2506b2bd93bf4ea95aaaeab60d | Python | 3,496 | 112 | from spine_fitter import SpineFitter
from spine_metrics import SpineMetricDataset
from typing import List, Tuple, Union, Callable, Set
from ipywidgets import widgets
from matplotlib import pyplot as plt
from sklearn.cluster import DBSCAN, KMeans
from sklearn.metrics import silhouette_score
import numpy as np
from sklea... |
930d3ce1db50e47c6f4794c00a28a8373ed42875ef70b7d7f669d2ae420fbefb | Python | 3,496 | 124 | """
Download the demo data and sort them into train, val and test in h5 files
"""
import os
import shutil
import zipfile
import h5py
from scipy import ndimage
from tensorflow.keras.utils import get_file
PROJECT_DIR = "demos/grouped_mask_prostate_longitudinal"
os.chdir(PROJECT_DIR)
DATA_PATH = "dataset"
ZIP_FILE = "d... |
86f530b50537f283489b35efe2ce99d37b03875039244460ef0fc1855c97e08f | Python | 3,497 | 116 | #!/usr/bin/python
# -*- coding: latin-1 -*-
# =============================================================================================
# Librairies importation
import numpy as np
import nrrd
import sys
import os
# =============================================================================================
... |
3a8b29e44077982d3ab4c450961cae6acf1dd29a229b1ba8b58bff58615acd18 | Python | 3,498 | 104 | import torch
import matplotlib.pyplot as plt
def post_synaptic_weight(thetas, p_exc):
n_e = int(thetas.shape[1] * p_exc)
exc = thetas[:, :n_e]
inh = thetas[:, n_e:]
exc_sum = exc.sum(1)
inh_sum = inh.sum(1)
exc = torch.where(inh_sum > exc_sum, exc.T, exc.T * inh_sum / exc_sum).T
inh = torc... |
7caa1d83fdcfb8a2e536d091caa6c2f5ebef4903132a2febd9ab9e94a4f064e5 | Python | 3,499 | 112 | import numpy as np
import pandas as pd
import pytest
from pandas.testing import assert_frame_equal
from eir.interpretation.interpretation_utils import get_long_format_attribution_df
def test_get_tabular_attribution_df_basic():
input_data = {
"feature1": [0.1, 0.2, 0.3],
"feature2": [0.4, 0.5, 0.6... |
3cfd6fbabf418720c3dbad72f8e0fc8838a2e5c5ab941f4d3d01d34925a528da | Python | 3,501 | 80 | # -*- coding: utf-8 -*-
################################################################################
## Form generated from reading UI file 'new_annotation_dialog.ui'
##
## Created by: Qt User Interface Compiler version 6.4.2
##
## WARNING! All changes made in this file will be lost when recompiling UI file!
#####... |
e56239c4d90f84f086478804ddb90a73fd3e9b84b972e6eff64f8cbf59f72263 | Python | 3,501 | 119 | # Copyright 2017 Calico LLC
#
# 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
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, ... |
0d503a794ae7c0c95ef456d591605771bb1437f9a294a71a044a36796978ffc5 | Python | 3,502 | 122 | #!/usr/bin/python3
#
import os
import sys
import argparse
import shutil
import numpy as np
from uac import utils
# Create the parser
my_parser = argparse.ArgumentParser(description="Calculation of labels using laplace solves and landmarks")
# Add the arguments
my_parser.add_argument("target_path", metavar="path", ty... |
2812afb1ae44fdeddf8d599eee94431f3ff85d91089cc3a748e29e30483b851b | Python | 3,502 | 73 | import numpy as np
import OptimalBattery.util as ut
import os
import OptimalBattery.evaluate as ev
import Functional_Fusion.atlas_map as am
from Functional_Fusion.dataset import DataSetMDTB
from IndividualParcellation.global_config import *
import OptimalBattery.construct as ct
import OptimalBattery.plot as plot
import... |
3c9883cbe93071f59f6cf6616b28cdf527c0f5ff430cbc855d83b6e6b50c6004 | Python | 3,502 | 84 | # -*- coding: utf-8 -*-
"""
DoG filter module
"""
#:copyright: Copyright 2015 by Christoph Kirst, The Rockefeller University, New York City
#:license: GNU, see LICENSE.txt for details.
import sys
from scipy.ndimage.filters import correlate
#from scipy.signal import fftconvolve
from ClearMap.ImageProcessing.Filter.F... |
4774a3df3a250aeb9e75415027eb35592e81e76e6136ab7d10326840d95695d1 | Python | 3,504 | 93 | """
AssociationStore: Persists input→output directory associations per user.
Stored in ``~/.musclex/directory_associations.json``, keyed on the
canonical absolute path of the input directory.
Copyright 1999 Illinois Institute of Technology
Permission is hereby granted, free of charge, to any person obtaining
a copy ... |
a8a378329ec17d9bec8c26e35a0ff53c83fd0247a53afb6286f281cd7a83c9fc | Python | 3,505 | 104 | #!/bin/python
"""
python Py_write_dPCA_assign_fortran.py all.txt
Created by Diana Slough
Created on 1-5-2017
This program reads all.txt (from dPCA) and writes Assign.f90
"""
import sys,os
import numpy as np
import math
##########################################################
def read_lines(f):
lines=[]
f... |
b0b03bf7efb046d4d36b8cdc2dc852cf6eca2e7daaacbe76dcb98eb453245873 | Python | 3,505 | 93 | """
Register stimulation data to anatomical images
"""
import nibabel as nb
import numpy as np
import subprocess
import os
import glob
ROOT = "/Volumes/sDresBackUp/s1Anfunco/Nifti"
# Set subjects to work on
subs = ['sub-18']
# subs = ['sub-09', 'sub-10', 'sub-12', 'sub-14', 'sub-15', 'sub-16', 'sub-17', 'sub-18']... |
c8af0eec21066955740dea148085317d1680549ef8ea2434f3c0a26a0bc4d0cc | Python | 3,505 | 100 | """Connected clusters cluster size thresholding commandline interface."""
import os
import argparse
import numpy as np
from nibabel import load, save, Nifti1Image
from skimage.measure import label
parser = argparse.ArgumentParser()
parser.add_argument('filename', metavar='path',
help="Path to ni... |
3b6fdb78780f76d43377ef59728f87caecfe9602fe708f04de03f9eef2e579a0 | Python | 3,506 | 99 | from __future__ import annotations
import pytest
from PySide6 import QtGui
from pytestqt.qtbot import QtBot
from labelme._widgets._label_dialog import LabelDialog
def _make_dialog(qtbot: QtBot, /, *, flag_count: int) -> LabelDialog:
flags = {f"flag_{i:02d}": False for i in range(flag_count)}
dialog = LabelD... |
88a89cb7ce8efd1b1f66092d618992edb4102eb188e5fa2368b378534e752c57 | Python | 3,506 | 75 | """Test the functions in the yasa/sleepstats.py file.
The public ``transition_matrix`` and ``sleep_statistics`` functions are deprecated (see
``test_hypno.py::test_deprecated_functions``). These tests check the values of the shared
implementation used by :py:meth:`yasa.Hypnogram.transition_matrix`.
"""
import unittes... |
dd5413c62450fede9b72ef544c6ef9421742bba791c5c3d5d4d9241340003996 | Python | 3,506 | 116 | from collections.abc import Sequence
from typing import TYPE_CHECKING
import pytest
from eir import train
from tests.test_modelling.test_modelling_utils import check_performance_result_wrapper
if TYPE_CHECKING:
pass
def _get_survival_output_configs(type_: str) -> Sequence[dict]:
if type_ == "discrete":
... |
6539173c90863bc3afeacec43b8bfc37037585050f255b046bdb33ea4a441cc9 | Python | 3,507 | 83 |
from scipy import spatial
import numpy as np
def exponentiated_quadratic_kernel(xa, xb, sigma):
# L2 distance (Squared Euclidian)
sq_norm = (-0.5 / pow(sigma,2)) * spatial.distance.cdist(xa, xb, 'sqeuclidean')
return np.exp(sq_norm)
def _generate_gaussian_process_path(path_boundary, options, n_poll):
... |
6ee7b287de1935895d51ab3865a1d563784d8036b0d4f1a43557c27b9d795ab3 | Python | 3,507 | 96 | """Load Gemini models using LangChain."""
import os
from getpass import getpass
from langchain_google_genai import ChatGoogleGenerativeAI
from chemgraph.models.supported_models import supported_gemini_models
from chemgraph.utils.logging_config import setup_logger
logger = setup_logger(__name__)
def load_gemini_mode... |
ada91b733dd271bc8ca6768c1feeaed5b159b5b5b6f833295e4851a3ee9f9cd6 | Python | 3,507 | 85 | import sys
from pathlib import Path
import os
sys.path.append(str(Path(os.path.abspath(__file__)).parents[3]))
import argparse
import torch
from torch_geometric.nn import Node2Vec
from ogb.linkproppred import PygLinkPropPredDataset
from torch.utils.tensorboard import SummaryWriter
# limit load for the server
os.enviro... |
d07894087336b3808306d79ff02c90c49d97111092bf9843fee45b37463f8653 | Python | 3,508 | 104 | # Copyright 2024 Google LLC
# 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
# https://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, sof... |
fe1b50fe8b8c89b09e79e9a0d34f7bbfb9e3d78a9794502da52f47550c28a8d2 | Python | 3,508 | 99 | """ A dataset reader that extracts images from folders
Folders are scanned recursively to find image files. Labels are based
on the folder hierarchy, just leaf folders by default.
Hacked together by / Copyright 2020 Ross Wightman
"""
import os
from typing import Dict, List, Optional, Set, Tuple, Union
from timm.util... |
14b38d41d81a6b3a4bf9b41221d2101372c50490f6f0a03a7b7ad3e47a416790 | Python | 3,509 | 97 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Split a label image into multiple images where the name of the output images
is the id of the label (ex. 35.nii.gz, 36.nii.gz, ...). If the --range option
is not provided, all labels of the image are extracted. The label 0 is
considered as the background and is ignored... |
2c0b3fce074abd8b0be22142543a990fdc4117a7604f7d271b538d3649dd9ecf | Python | 3,510 | 81 | import sys
import os
import time
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import torch
import torch.nn as nn
import torch.optim as optim
from torch.nn import functional as F
import random
from sklearn import metrics
from collections import Counter
inpt_ = "mock_genomes.npy" #input genotyp... |
70bebaf7635a6196098aa81eb0384271d17f884aebec17e2b379da61364fb21e | Python | 3,510 | 66 | import numpy as np
import pickle
import pandas as pd
import fire
from rsatoolbox.inference import eval_fixed
from rsatoolbox.model import ModelFixed
from nilearn.image import new_img_like, load_img
from rsatoolbox.util.searchlight import evaluate_models_searchlight
theories = {
"symbolic": "./derive_theoretica... |
f25429e134396979ca53c1763b75b09fcdb88613221453c4dd32ceb9cf9d1d09 | Python | 3,510 | 85 | #!/usr/bin/env python3
"""Simulate a closed control loop and record it to a ``.tha`` file.
A *closed loop* is the defining Thalamus use case: a value is measured, a rule
decides on an action, and that action feeds back and changes the value. In a live
pipeline you'd wire it as ``sensor -> ALGEBRA/TOGGLE (decide) -> o... |
3b6e30cd5df548985d359927dab24c0c7f0bc32611f0139f9b8a2d8ab6671079 | Python | 3,511 | 104 | import os
import lmdb
import pickle
from multiprocessing import Pool
from tqdm import tqdm
import numpy as np
import argparse
from multiprocessing import cpu_count
nthreads = cpu_count()
def inner_read(cursor):
key, value = cursor
data = pickle.loads(value)
if "y_relaxed" in data:
ret_data = {
... |
70d156b8142dca5b4c1b51b0303c05816f8ecd381db4c7010fa71cd21d5e7dea | Python | 3,511 | 101 | import torch
from torch.autograd import grad
from knn_cuda import KNN
import torchsort
def gradient(inputs, outputs, create_graph=True, retain_graph=True):
d_points = torch.ones_like(outputs, requires_grad=False, device=outputs.device)
points_grad = grad(
outputs=outputs,
inputs=inputs,
... |
4f4b5e85dca462894cf2b33c8f9f20d8220f6f27b3453d90351350f2991ea1e8 | Python | 3,512 | 111 | import numpy as np
import os
from typing import Union, List
# `List` instead of `list` for backwards compatibility
import h5py
import glob
from PIL import Image
import numpy as np
import os
__all__ = ['dump_npz', 'load_npz', 'tif_to_h5', 'tif_to_stack']
def dump_npz(filepath, data: dict, force=False, dry=False, compr... |
fee407c255d4630c00194fbe8a0d0868a31b23388b42f20e6857a20dce4013b7 | Python | 3,512 | 97 | import pdb
import os
import glob
import matplotlib.pyplot as plt
import sciplotlib.style as splstyle
import matplotlib as mpl
import natsort
from PIL import Image
import numpy as np
def combine_plots_across_div(recording_div_folders, plot_names=['FiringRateByElectrode.png'], fig=None, axs=None):
"""
Parameter... |
34fb268d643187897d12478442c6bd89fb06f512ecb0cef3aac98d9e148cea73 | Python | 3,513 | 104 | import sys
import os
import time
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import torch
import torch.nn as nn
import torch.optim as optim
from torch.nn import functional as F
import random
from sklearn import metrics
from collections import Counter
from captum.attr import (IntegratedGradien... |
5aed40ffd872bfce7337dd5f3a3440d4f21393712e5fd680be635a0f330f5ed0 | Python | 3,513 | 78 | import librosa
import matplotlib.pyplot as plt
import numpy as np
import soundfile as sf
import noisereduce as nr
class NoiseReduceFilter:
def __init__(self, mode='stationary', n_fft=2048, hop_length=512, win_length=None,
n_std_thresh_stationary=1.5, prop_decrease=1.0,
time_consta... |
29340d42df40220dc39e428ee415f06ced9e3673e80bcd0e536cd01e727c1efc | Python | 3,514 | 89 | # NOTE: 128-256GB CPU memory required to run this script.
import os
import time
import argparse
import os.path as osp
from tqdm import tqdm
import torch
import numpy as np
from torch_sparse import SparseTensor
from torch_geometric.nn.conv.gcn_conv import gcn_norm
from ogb.lsc import MAG240MDataset
from root import RO... |
399794018a5e6a87e3cecf8c62c29d1afbe1e0162edaf2ddd67baa157d96b048 | Python | 3,514 | 92 | import torch
from torch.utils.data import DataLoader
from tqdm import tqdm
class MinMaxScaler():
"""Transform features by scaling each feature to a given range.
Args:
min (FloatTensor): Per feature adjustment for minimum.
scale (FloatTensor): Per feature relative scaling of the data.
... |
019ea83fc076f263bd3c7d0e215bbb66e6b391bb0fb72e2a8c7f55411cd2fac2 | Python | 3,515 | 111 | import numpy as np
import torch
from torchvision.transforms import v2
class SelectChannels(object):
"""
Select subset of channels from image to be used.
# object: list(P["SELECTED_CH"])
"""
def __init__(self, selected_channels: list):
self.selected_channels = selected_channels
... |
127d907711f072f0b9a6311c5511fa024cfbd3c7b8cee0826cb4814c119ee384 | Python | 3,515 | 85 | import os
import glob
import numpy as np
import skimage.io as skio
import torch
from torch.utils.data import Dataset
import random
from natsort import natsorted
import json
class KidneyData(Dataset):
def __init__(self, root='data/', mode='train', separation='90_10', fold=0, all_zero_involved=False, transforms=None... |
5bc5137e5d41f597c6393f727342acc346b797b2d91d138bb2bcc7daf7e8028a | Python | 3,515 | 59 | import numpy as np
import sys
def pairwise_euclidean_distance(array_1, array_2):
'''Calculates the pairwise Euclidean distance between two arrays of points.'''
squared_distances = np.sum((array_1[:, np.newaxis] - array_2) ** 2, axis=2)
return np.sqrt(squared_distances)
def setup_stimulation_grid(pixel_size, stim_g... |
dfbcd376dd207d20143ccb705e3660e665b1fe2b688c954534e0d8475875721d | Python | 3,515 | 139 | from .message_passing import MessagePassing
from .simple_conv import SimpleConv
from .gcn_conv import GCNConv
from .cheb_conv import ChebConv
from .sage_conv import SAGEConv
from .cugraph.sage_conv import CuGraphSAGEConv
from .graph_conv import GraphConv
from .gravnet_conv import GravNetConv
from .gated_graph_conv impo... |
7d3a1697c781e8d8789196927714a6ab0153a4b5986ea3f876952cc9af6c52cb | Python | 3,517 | 120 | from pickle import FALSE
from datagenerator_pd import DataGenerator
from sklearn.metrics import confusion_matrix, accuracy_score, roc_curve, auc
from tensorflow.keras.utils import to_categorical
import matplotlib.pyplot as plt
import seaborn as sns
import SimpleITK as sitk
import pandas as pd
import numpy as n... |
5fd3ed8c60cc5e39643a133fcbc8e8fd68330e6ff04c067274d4c9b300f83774 | Python | 3,518 | 108 | import os
import pandas as pd
from sklearn.metrics import accuracy_score, roc_auc_score, f1_score, precision_score, recall_score
def lcs(dna: str) -> None:
global lcs_string
global user_list
global genes
cnt = 0
for user in user_list.keys():
if dna in user_list[user]:
cnt +=... |
9e5a476166e5905918d45077fc1d4c9fc5556b99d0822ccbf27f3399fcc5afdb | Python | 3,519 | 93 | from model import DeeProBot
from dataset import training_data,val_data,test_data
import torch
from torch import nn
from utils import accuracy,init_weights
from torch.utils.data import DataLoader
from sklearn.metrics import f1_score
from sklearn.metrics import matthews_corrcoef
from sklearn.metrics import precision_scor... |
c88d64d85d65f512f0fb34891e79680882189bf437e2e2d0dc7e215fff848e5b | Python | 3,519 | 102 | # Copyright 2024 DeepMind Technologies Limited
#
# 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 applicable law or agree... |
ecda4eb34b9ae474bdc7848db5e78de0e1e10b0b7b51ac95b1f35123e7e5640c | Python | 3,519 | 99 | import pytest
import warnings
import logging
from ase import Atoms
# Configure pytest-asyncio
#pytest_plugins = ("pytest_asyncio",)
# Test modules that require the optional ``academy`` extra guard themselves with
# ``pytest.importorskip("academy")`` at module top, so they skip cleanly (rather
# than erroring collecti... |
fef30a22e06dad490c9c4658197426f3707386833e5802278a9c54d7c50e4de5 | Python | 3,519 | 115 | import torch
import torch.nn as nn
from dataclasses import dataclass, field
from dgl.nn import GCN2Conv, GraphConv
@dataclass
class Args:
device: str = 'cpu'
epochs: int = 1000
lr1: float = 1e-3
wd1: float = 0.0
lambd: float = 1e-3
n_layers: int = 9
der: float = 0.5
dfr: float = 0.3
... |
9f8433bff72d8334e2dc358ba8fe532eb44ae1ddb5da45a1e6625164c1aa91d2 | Python | 3,520 | 96 | import numpy as np
from src.wrappers.OsipiBase import OsipiBase
from src.original.fitting.ETP_SRI.LinearFitting import LinearFit
import warnings
warnings.simplefilter('once', UserWarning)
class ETP_SRI_LinearFitting(OsipiBase):
"""WIP
Implementation and execution of the submitted algorithm
"""
# ... |
6b2e99d136f20b6b38167e2ba764bca01eaa1437e9d7de4b0f9f73cfad39725e | Python | 3,521 | 94 | import sys
import time
import getopt
from scipy.sparse import csr_matrix
from slice_dataframe import slice_dataframe
import anndata as ad
import pandas as pd
import numpy as np
from anndata import AnnData
#############################################################################
# usage
def gem_to_h5ad_usage():
... |
a942a902cb33afceaa4c643f88fede2071549a8b948eb7eac88b7fd063f0c983 | Python | 3,521 | 111 | #!/usr/bin/python
#
## @file
#
# Qt Widget for displaying color scales
#
# Hazen 3/09
#
from PyQt5 import QtGui, QtWidgets
import sys
## QColorGradient
#
# This class handles displaying a color scale based on the current color table.
#
class QColorGradient(QtWidgets.QWidget):
## __init__
#... |
d3ec7b3b48376ca8409c2c65db121e69ab41d1245f2c37dbc36b92155f40aec3 | Python | 3,521 | 103 | import os
import numpy as np
import yaml
import sys
pathpath = 'PATHS/filepaths_IBLTuning.yml'#
myrun = 'runIBLTuning_utypeP'
layers_allowed = ['5','6']
nshuff = 2000
signif_levels = np.array([0.05,0.01,0.001])
tuning_attr_names = ['stimTuned','choiceTuned','feedbTuned','taskResp']
blk_condition = 'detail'
pthr_cc... |
1ebc1306c330fa7fa3701bd1cb996908d405cbb01dbcaed1a1286493401d4630 | Python | 3,522 | 94 | import numpy as np
from sklearn.metrics import pairwise_distances
from tqdm import tqdm
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
def jaccard_distance_matrix(binary_matrix):
"""Compute sample-wise Jaccard distance matrix."""
return pairwise_distances(binary_matrix.T, metric='jac... |
853b7a69768319d8a7e5400504f78d170eb83220d804f1c2acc3529012f0e1d8 | Python | 3,522 | 96 | """Plot projection onto the primary tuning shift dimension.
Figure 4B.
"""
import matplotlib.pyplot as plt
import numpy as np
import os
import pickle
from utils import (
do_flip_colors_dict,
get_pssd,
get_voxel_to_fsaverage_mapper,
load_model_results,
num_fsaverage_vertices,
participant_names,... |
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