sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
398fef64aedaf1361ed18dcbad923bf83e7427f3e8b4de6877c6054888f41456 | Python | 4,518 | 118 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
"""Export a project's tasks individually, without images, to local zips AND to
a registered cloud storage.
By default every task in the project is exported; pass --task-id to export
only a specific subset. This is the SDK-only stand-in for what coul... |
575554cfe3fdddfe28f03a7858ad84c34994a8d0d58e7407a8951a20e17aa30a | Python | 4,518 | 133 | # -*- coding: utf-8 -*-
"""
Analysis of experimental ocular dominance columns
The purpose of the following script is to analysis ocular dominance columns and
estimate their column width and column spacing.
To do so, the power spectrum and the normalized autocorrelation (NAC) map are
computed and evaluated along diffe... |
6785c10add2482187cd1a64b425e81f8a29b97fa9d3792984898b5e525bddded | Python | 4,518 | 115 | import torch
import yaml
import torchvision.transforms as transforms
import pandas as pd
from data_loader import load_and_split_data, get_dataloaders
from DLmodels import create_model, train_model, evaluate_model
from sklearn.metrics import accuracy_score, f1_score, confusion_matrix, roc_auc_score
from ML_models import... |
b64c5de4e98a0d3fe2ff806c397ce5da48e2caae262e85968216c60f8ca30bec | Python | 4,518 | 128 | """Apply machine learning metrics to causal models for evaluation."""
import warnings
import numpy as np
import pandas as pd
from sklearn import metrics
NUMERICAL_CLASSIFICATION_METRICS = {
"accuracy": metrics.accuracy_score,
"precision": metrics.precision_score,
"recall": metrics.recall_score,
"f1":... |
77a2d4e65f4b40c9d65bcaebbca5afb48591ae1e2511828b0ab8e177ed379ad4 | Python | 4,519 | 151 | from __future__ import annotations
from collections.abc import Callable
from pathlib import Path
import pytest
from PySide6 import QtCore
from PySide6 import QtGui
from PySide6 import QtWidgets
from pytestqt.qtbot import QtBot
from labelme._app import MainWindow
from labelme._utils import apply_color_theme
from .co... |
65e88438869450f02fdbdadeb068c625f072369ded288dd382dc0c9bf17561bd | Python | 4,520 | 137 | import unittest
from deepgo.models import DeepGOModel, DeepGOGATModel
import torch as th
class TestDeepGOModel(unittest.TestCase):
@classmethod
def setUpClass(self):
self.batch_size = 4
self.input_length = 32
self.nb_gos = 32
self.nb_zero_gos = 32
self.nb_rels = 5
... |
0c2b2ad8206832b78dfdf57b66008720e9cf7358c0745fe93d3446a1245af0eb | Python | 4,521 | 169 | import os
import subprocess
import numpy as np
import pandas as pd
import abm as abm
from output_paths import artifact_dir
from bckground_distribution import (
get_interaction_matrix,
get_significant_lr_pairs,
pvalues_threshold,
save,
)
def _ensure_output_dir(path):
os.makedirs(path, exist_ok=Tr... |
c6023dbcc4e199ccc1cd6bbc21df1072d2d7dab50ecfafda27ba208a3cec8a80 | Python | 4,521 | 140 | """Abstract base class for pyment datasets."""
from __future__ import annotations
import logging
from abc import abstractmethod
from typing import Any, Callable
import numpy as np
import pandas as pd
import tensorflow as tf
from numpy.typing import ArrayLike
from sklearn.utils.class_weight import compute_class_weigh... |
05007c19bbfc124d3caf9212c7407ec43fb42c71986cadfe08a57c370a577b9f | Python | 4,524 | 154 | # -*- coding: utf-8 -*-
"""
usage example:
python MedSAM_Inference.py -i assets/img_demo.png -o ./ --box "[95,255,190,350]"
"""
# %% load environment
import numpy as np
import matplotlib.pyplot as plt
import os
join = os.path.join
import torch
from segment_anything import sam_model_registry
from skimage import io, ... |
ec96b8ae6e47922715ef51a7ede3ec42fa0e90f99032614ae92cc2f62a0774c5 | Python | 4,524 | 95 | #encoding=utf-8
from __future__ import print_function
import sys
sys.path.append("../../")
import jieba
jieba.enable_parallel(4)
def cuttest(test_sent):
result = jieba.cut(test_sent, HMM=False)
for word in result:
print(word, "/", end=' ')
print("")
if __name__ == "__main__":
cuttest("这是一个伸手不... |
15217e96b3a478765529a847fa51ce22b0442f7b8fe90184c9d57931eb15ed48 | Python | 4,525 | 117 | import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle, ConnectionPatch
import figure_properties as fp
import numpy as np
seed = 11
c2_poi_fn = str(seed) + '_longer_100_poi_2Hz_7_Control.npz'
l2_poi_fn = str(seed) + '_longer_100_poi_2Hz_20_Letm1.npz'
#p2_poi_fn = str(seed) + '_PDP_slower_100_poi_2Hz_... |
3ae7597747b52a1d92a60f7e5046cc632999c56f468d62d99f4b7cf456e41bd8 | Python | 4,525 | 95 | #encoding=utf-8
from __future__ import print_function
import sys
sys.path.append("../../")
import jieba
jieba.enable_parallel(4)
def cuttest(test_sent):
result = jieba.cut_for_search(test_sent)
for word in result:
print(word, "/", end=' ')
print("")
if __name__ == "__main__":
cuttest("这是一个伸手... |
311eb8a730f31cc53d5598b3ca2d10e2f2a1cbd8f7bf8b509ddb375835837fe0 | Python | 4,526 | 168 | # -*- coding: utf-8 -*-
"""ANA <-> ORIG registration
The purpose of the following script is to compute the deformation field for the
registration between antomy in conformed freesurfer space and native anatomical
space. The transformation can be computed from the headers of source and target
images. The script needs a... |
374a202ab01bf9973f070608da2f77a9bcd32498ff9df7ef8a5067e7c83a70dc | Python | 4,527 | 85 | """A module that contains core CoRelAy classes, such as :py:class:`~corelay.base.Param`."""
import typing
from corelay.plugboard import Slot
from corelay.utils import get_fully_qualified_name
class Param(Slot):
"""A single parameter slot, which can be used to parameterize implementations of :py:class:`~corelay.... |
446891459e0c871fb3887f5cf36603e5aae2fd20243907da5c43127f83482041 | Python | 4,527 | 124 | """
EventClassifier_numUnit
@ 2022 Knowblesse
Modified Version of EventClassifier. This script output accuracy when only a subset of units are used in the
classification.
- Description
- .mat dataset must have two variable, X and y. (mind the case of the variable name)
- using the sklearn SVC class, build and t... |
4472e50154c988430cc41559c465ef113e2beeffbd3c8b5953d0bca6745c7408 | Python | 4,527 | 95 | #encoding=utf-8
from __future__ import print_function
import sys
sys.path.append("../../")
import jieba
jieba.enable_parallel(4)
def cuttest(test_sent):
result = jieba.cut(test_sent,cut_all=True)
for word in result:
print(word, "/", end=' ')
print("")
if __name__ == "__main__":
cuttest("这是一个... |
7c47ab46ad9218644bc3e8e65bb3dbbf63485d621641d6551fea41841a47d639 | Python | 4,527 | 144 | import os
import json
import numpy as np
import nibabel as nib
from scipy import ndimage
def count_shells(dwi_json_path):
'''
Count the number of shells in the DWI data
'''
f = open(dwi_json_path)
dw_head = json.load(f)
shell_list = []
for enc in dw_head["keyval"]["dw_scheme"]:
sh... |
8ae1a7b8c7825b5aefdd8dd737e28ab625c48b90b2221c596a0ed812d7272221 | Python | 4,527 | 136 | # coding=utf-8
# Copyright 2018 The Google AI Language Team 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 ... |
c580cbcf4965318596b2db5ddbc56ccef9b7b3784650d2a408121b053e56b15d | Python | 4,527 | 164 | """Example script for running inference on simulated MDyn_HMM_MVN data.
- Multi-dynamic version for dynemo_hmm-mvn.py
- Should achieve a dice of ~0.99 for alpha and ~0.99 for beta.
"""
print("Setting up")
import os
import numpy as np
from osl_dynamics import data, simulation
from osl_dynamics.inference import metrics... |
f152be057229d63a4917bb98de0e16d204c845f2dcd18c053b547aa3e9b5a512 | Python | 4,527 | 149 | import src.contour as con
import nibabel as nib
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import matplotlib.animation as animation
import cv2
import gc
from pylab import *
import src.finElFit as fe
def ani_frame(dataset,filename):
#creates mp4 file of dataset formated like the e... |
ddf70b9f2595f38801753fc40305db4d32b491f3fadc6ceccc5fff6ce00f37b9 | Python | 4,528 | 134 | import numpy as np
import itertools
def get_phase(rdm, phase):
assert phase in ["pre", "gray", "post", "pre-post", "pre-gray", "post-gray", "all"]
if phase == "pre":
res = rdm[:33, :33]
elif phase == "post":
res = rdm[33:66, 33:66]
elif phase == "gray":
res = rdm[66:, 66:]
e... |
ab40af7ec6eed17629c8b1d11abfda12fc29d0008ca1b9430ce024e9035626fd | Python | 4,530 | 123 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Computes the endpoints maps of a bundle (head and tail). The endpoints maps are
a count of the number of streamlines that start or end in each voxel.
Note: If the streamlines are not ordered, the head/tail are random and not
really two coherent groups.
- To get a ... |
37dfe542eccab07889ba42861f54f6f23d80c0ad86965c085395d960eed7fa14 | Python | 4,531 | 74 | #!/usr/bin/env python3
# scripts/export_fold_stats.py
import sys
from pathlib import Path
import numpy as np
import pandas as pd
# ──────────────────────────────────────────────────────────────────────────────
# 1. 将项目根目录加入模块搜索路径（假设本文件在 PROJECT_ROOT/scripts/ 下）
# ─────────────────────────────────────────────────────... |
d03bba1447919908b0feaa730b33ba3b1755f446db441f2bd8ef190ef96a16ee | Python | 4,533 | 156 | # -*- coding: utf-8 -*-
"""
Plots for autocorrelation analysis (simulation)
The purpose of the following script is to generate exemplary plots for the
autocorrelation analysis of ODC data (averaged over 1000 iterations). The
following plots are produced:
1. phi vs. fwhm
2. phi vs. k_fft
3. phi vs. P_fft
... |
402b9510c50784657f1e2d727c9dfffb3da08f97f60e321570dd48f66d522198 | Python | 4,534 | 127 | import os
import logging
import numpy as np
import mne
import xml.etree.ElementTree as ET
def load_eeg_data(base_path):
"""
Load EEG data (EDF files), sleep stage labels, and artifact indicators from a structured directory.
The function reads EEG recordings in EDF format along with their corresponding sl... |
5f533ea78726b202f8c7eb1298e5071d3128ef21ae1b1e7097f24c09badd9819 | Python | 4,534 | 147 | # Copyright (C) 2020-2022 Intel Corporation
# Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
from datumaro.components.errors import AnnotationExportError
from datumaro.components.project import Environment
from cvat.apps.dataset_manager.bindings import CvatExportError
from cvat.apps.engine.models i... |
78fe5fa307dda35f15b3a413550236887af1447a61beefd9990e565be545e819 | Python | 4,535 | 143 | # -*- coding: utf-8 -*-
# external inputs
import numpy as np
from scipy.signal import find_peaks
# local inputs
from ..utils import get_fft
def analyze_fft(arr, fovx, fovy, xv, yv, f_cut=0.05, p_min=None, p_max=None,
nsample=1000):
"""Analyze FFT.
This function computes the peak frequen... |
bff8f891723cfcdbd6c3dfc51363f9ebc703bf7f7d5802f567df49b63f9fdc8c | Python | 4,535 | 156 | from __future__ import annotations
import base64
import io
import json
import subprocess
import sys
from pathlib import Path
from typing import Final
import numpy as np
import PIL.Image
import pytest
_REPO_ROOT: Final = Path(__file__).resolve().parents[3]
def _write_annotation(directory: Path, /) -> None:
img ... |
b2aee6db789bca9268fb6c8ef164d8d32c266aaa49b75540397c0188f441285e | Python | 4,538 | 146 | #!/usr/bin/python
#
# Active X based Coherent CUBE 405 laser control.
#
# Hazen 8/09
#
from PyQt5 import QtCore, QtGui, QAxContainer
import sys
import time
class Cube405(QAxContainer.QAxWidget):
def __init__(self, parent = None):
QAxContainer.QAxWidget.__init__(self, parent)
se... |
4777ca21fc154f4fdeab61acbdfc7a8718aba2f48fdba66bfe467f9b1f99f143 | Python | 4,539 | 112 | import pandas as pd
import torch as th
import numpy as np
import dgl
import os
def get_data(df, features_dict, terms_dict, features_length, features_column):
"""
Converts dataframe file with protein information and returns
PyTorch tensors
"""
data = th.zeros((len(df), features_length), dtype=th.fl... |
c021947d8c28d46248214dce104d5dcc10d410a2ba571f76c7484b86ee2c05cf | Python | 4,539 | 123 | from __future__ import annotations
import argparse
import json
import subprocess
from pathlib import Path
import pytest
# Skip when the optional 'academy' extra is absent.
pytest.importorskip("academy")
from chemgraph.academy.runtime import dashboard_launcher
from chemgraph.academy.runtime.profiles.system import Sy... |
8b5627f6e130694d56644f2e66345253dcbe198d77c0fbe71c6dce1dacb43dfd | Python | 4,540 | 109 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import os
import tempfile
from scilpy import SCILPY_HOME
from scilpy.io.fetcher import fetch_data, get_testing_files_dict
# If they already exist, this only takes 5 seconds (check md5sum)
fetch_data(get_testing_files_dict(), keys=['plot.zip'])
tmp_dir = tempfile.Tempora... |
8ccf04d9ca2019105e295e7fbb11855ca64413905152a70f73c9cf79603eac8c | Python | 4,541 | 94 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import os
import tempfile
from scilpy import SCILPY_HOME
from scilpy.io.fetcher import fetch_data, get_testing_files_dict
fetch_data(get_testing_files_dict(), keys=['btensor_testdata.zip'])
tmp_dir = tempfile.TemporaryDirectory()
def test_help_option(script_runner):
... |
ace99532de25cfbbe30f201796dad76a8ff6547f34919f1b1f792b76e05bd36c | Python | 4,541 | 93 | #@String(value="<HTML>This script runs Convex Hull Analysis on an entire directory of reconstruction files.<br>Processing log is shown in Console.", visibility="MESSAGE") msg
#@File(label="Input directory:", style="directory", description="Input folder containing reconstruction files (.traces, .swc, json) to be analyze... |
c29f02a563a55213ce4248e66286bd206fdcd68305a35bf70f7520fc32c68714 | Python | 4,542 | 128 | from pathlib import Path
from unittest.mock import patch, Mock
import pytest
from stack_corr.definitions import StackCorrConfig, InferParams, STACK_CORR_CONFIG
from stack_corr.stack_corr import load_model
class TestStackCorrConfig:
"""Test the StackCorrConfig dataclass."""
def test_default_config(self):
... |
dda09b23a6d9ccd0ebedd67643b5a62473d6a2e362a927a2383c76126286ed06 | Python | 4,543 | 111 | from typing import Optional
from torch import Tensor
from torch_geometric.nn.conv import MessagePassing
from torch_geometric.nn.conv.gcn_conv import gcn_norm
from torch_geometric.nn.dense.linear import Linear
from torch_geometric.typing import Adj, OptTensor, SparseTensor
from torch_geometric.utils import spmm
clas... |
8915a0ad4568027e360e954f1348d97252c1e8eb54380aca979767e775a609ce | Python | 4,545 | 114 | import logging
from typing import List, Optional, Union
import torch
from torch import Tensor
from torch_geometric.explain import Explanation
from torch_geometric.explain.algorithm import ExplainerAlgorithm
from torch_geometric.explain.config import ExplanationType, ModelTaskLevel
from torch_geometric.nn.conv.message... |
4f9f9330dc9ff33452e5692f0d2d678cf2ed2655a71009ca008f13f6305c18d6 | Python | 4,546 | 125 | import pandas as pd
from scipy.stats import mannwhitneyu, chi2_contingency
def excel_column_letter_to_index(letter):
letter = letter.upper()
index = 0
for char in letter:
index = index * 26 + (ord(char) - ord('A')) + 1
return index - 1
def load_data_from_excel(file_path, ages_col1, ages_col2,... |
bca21fed2905850565057d4d55fbd2bc9cea6e3a47074812235bf8028ba658f9 | Python | 4,546 | 181 | # -*- coding: utf-8 -*-
# external inputs
import numpy as np
from gbb.neighbor import nn_2d
# internal inputs
from ..io.affine import vox2ras_tkr
from ..utils.apply_affine_chunked import apply_affine_chunked
__all__ = ['label_border', 'label_dilation', 'label_erosion', 'roi_fov', 'roi_sphere']
def label_border(arr... |
a694137f828af1ba5eca57a28f8d8c59c5932b5361bd86b33a241c3cd0013c32 | Python | 4,548 | 155 | '''RegNet in PyTorch.
Paper: "Designing Network Design Spaces".
Reference: https://github.com/keras-team/keras-applications/blob/master/keras_applications/efficientnet.py
'''
import torch
import torch.nn as nn
import torch.nn.functional as F
class SE(nn.Module):
'''Squeeze-and-Excitation block.'''
def __in... |
cf409dfec24561451e3c3b616164303ed3057d797f8b2b4228112a3239f7c937 | Python | 4,548 | 130 | # Copyright (c) OpenMMLab. All rights reserved.
"""Modified from https://github.com/open-
mmlab/mmdetection/blob/master/tools/analysis_tools/analyze_logs.py."""
import argparse
import json
from collections import defaultdict
import matplotlib.pyplot as plt
import seaborn as sns
def plot_curve(log_dicts, args):
i... |
f908b3fd18c3e41067cf937d5b5a66b4534a5090deda549ea0de553788b56a23 | Python | 4,548 | 119 | from collections.abc import Mapping
from functools import reduce
from bx.misc.binary_file import (
BinaryFileReader,
BinaryFileWriter,
)
def cdbhash(s):
return reduce(lambda h, c: (((h << 5) + h) ^ ord(c)) & 0xFFFFFFFF, s, 5381)
class FileCDBDict(Mapping):
"""
For accessing a CDB structure on d... |
3e55da077e45a39e1b0df88ec09b4da1151c8203709b50e4ad8b2cd614cb979b | Python | 4,549 | 144 | # -*- coding: utf-8 -*-
# @Author : LG
import os
from xml.etree import ElementTree as ET
import tqdm
from ISAT.formats.isat import ISAT
class VOCDetect(ISAT):
"""
VOC format for object detection
Attributes:
keep_crowd (bool): keep the crowded objects
"""
def __init__(self):
s... |
423ba3e6abcca23198d8168e106056cbe06d33d270668d316394d9bd3c9baedf | Python | 4,549 | 122 | #!/usr/bin/env python3
import os
import math
import tensorflow as tf
import pandas as pd
import keras
from keras import layers
from tensorflow import data as tf_data
import random
import numpy as np
import autoAnalysis
from sklearn.preprocessing import StandardScaler
from sklearn.metrics import classification_report, ... |
4861d85d79fd2d2948dee622692e80c70267ed2407dbf7ed302f5d9d95010474 | Python | 4,549 | 140 | #!/usr/bin/python3
#
import os
import sys
import argparse
from sklearn.neighbors import NearestNeighbors
from uac import utils
# Create the parser
my_parser = argparse.ArgumentParser(description="Calculation of old atrial coordinates")
# Add the arguments
my_parser.add_argument("target_path", metavar="path", type=st... |
edd7c7e9a939c3d2d4dbae36e79894be5c2d77fbbdb1ab7726754c2c31fd0449 | Python | 4,550 | 146 | #!/usr/bin/env python
#
# collect.py renames files from subdirectories
#
# Copyright F. Nedelec, 2007--2021
"""
Synopsis:
Rename files or folders following a pattern containing an integer index,
as in 'image0001.png'. The file will be moved in the current directory
The number in the file name is... |
1db6c3d8b02d8459628f9557a478ad461213fa63281678e60c483c14ebe8d6fa | Python | 4,551 | 123 | #!/usr/bin/env python
"""
Voltage controlled Z stage functionality.
Hazen 05/17
George 02/18 - Abstracted from mclVoltageZModule.py
"""
from PyQt5 import QtCore
import storm_control.hal4000.halLib.halMessage as halMessage
import storm_control.sc_hardware.baseClasses.daqModule as daqModule
import storm_control.sc_h... |
763cee033533594baa7506b8d8cce33ef8be17aa4bf3ea6c4f33ab152b650dff | Python | 4,552 | 132 | import ttach as tta
import multiprocessing.pool as mpp
import multiprocessing as mp
import time
from train_supervision import *
import argparse
from pathlib import Path
import cv2
import numpy as np
import torch
from torch import nn
from torch.utils.data import DataLoader
from tqdm import tqdm
def seed_everything(se... |
542f1a9459b768dc2a64ca02c272046a1454704f35055116899f748b9350aea6 | Python | 4,553 | 124 | from k_means_constrained import KMeansConstrained
import numpy as np
import matplotlib.pyplot as plt
import matplotlib as mpl
import h5py
import shapely
def get_clusters(X,NperPatch=100,frac_range=[0.8,1.2]):
n_clusters = int(len(X) / NperPatch)
minsize = NperPatch*frac_range[0]
maxsize = NperPatch*frac_r... |
02d6d82843157aa1689ea5caabe6b783fa74e708a6ac139871e04127cd66ddb8 | Python | 4,555 | 141 | from pathlib import Path
import pytest
from magicgui.widgets import Image
_mpl_image = pytest.importorskip("magicgui._mpl_image")
np = pytest.importorskip("numpy")
pilImage = pytest.importorskip("PIL.Image")
def test_image_widget():
# png works
image = Image(value=Path(__file__).parent / "_test.png")
a... |
5a0f670fe1d28047195c30aaab8f2ba156684222cd113906c791498213e38e94 | Python | 4,555 | 107 | #!/usr/bin/env python
"""Warp HArtMuT artefact sources into an individual head.
Python port of the HArtMuT individualwarp routine (project_points.jl,
https://github.com/harmening/HArtMuT/tree/main/individualwarp). The original
uses Julia + VTK ray casting. This version uses trimesh, which PCAwarp already
depends on, s... |
67cb6fedfd638b79c92add80d55deeb357478022e0557386d07da3e5146ddd98 | Python | 4,555 | 158 | #!/usr/bin/python
#
## @file
#
# Communicates with the Newport SMC100 motor controller.
#
# Hazen 2/11
#
import time
import storm_control.sc_hardware.serial.RS232 as RS232
## SMC100
#
# Encapsulates control of Newport SMC100 motor controller using RS-232.
#
class SMC100(RS232.RS232):
## __ini... |
b548bfce459a39865532ed389ec588a18909e31a542f8cec134c1079b330afd1 | Python | 4,555 | 119 | # This file is part of Mooney computational modeling project.
#
# Mooney computational modeling project is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) an... |
f74cbf2873887e6b2b1064bd22c7a0475b329bf006f8bc31f1a4138edee3b8ef | Python | 4,555 | 126 | ######################################################################
# Copyright (C) 2020-2026 MEmilio
#
# Authors:
#
# Contact: Martin J. Kuehn <Martin.Kuehn@DLR.de>
#
# 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... |
b29026e3b59d59451f0686d037d75d21a8ac5dad4d944724ca491bbe0adbf585 | Python | 4,556 | 156 | # -*- coding: utf-8 -*-
import logging
import numpy as np
def create_acqparams(readout, encoding_direction, synb0=False,
nb_b0s=1, nb_rev_b0s=1):
"""
Create acqparams for Topup and Eddy
Parameters
----------
readout: float
Readout time
encoding_direction: string... |
ab9438c2d672f9967f0cf5626da56507f4139f578253e44b014952b14b2dab6a | Python | 4,558 | 154 | """
Train and compare DLIM (Deep Latent Interaction Model) models
on *simulated data* for different data types (cascade, bio, tgaus).
This script:
1. Generates simulated data using the specified model type.
2. Trains multiple DLIM models (with and without spectral regularization).
3. Collects learned embeddings from ... |
b86a4258985f9f51563e734ca2f27d0f0cf9316aa4b1b8b672ed4a7d3247c409 | Python | 4,558 | 133 | import json
from pathlib import Path
from argparse import ArgumentParser
import numpy as np
import xarray as xr
from brainscore_core.supported_data_standards.brainio.assemblies import NeuroidAssembly
import brainscore_core.supported_data_standards.brainio.packaging as _brainio_pkg
from brainscore_core.supported_data_... |
70a03042a79f72e00477d6be4d2a324710812e93828f93961a03097edd95bd95 | Python | 4,559 | 125 | from __future__ import annotations
from collections.abc import Callable
from typing import TYPE_CHECKING
from magicgui.types import Undefined, _Undefined
from ._mixins import _OrientationMixin
from ._ranged_widget import MultiValueRangedWidget, RangedWidget, T
if TYPE_CHECKING:
from typing_extensions import Unp... |
87472fa1341c697e1f4445daa735cd628b9552c9fdc8962450001346c2ace256 | Python | 4,559 | 116 | import os
import h5py
import numpy as np
import pandas as pd
import scipy.misc
import scipy.misc
import scipy.misc
import xarray as xr
from result_caching import store
from tqdm import tqdm
from brainscore_core.supported_data_standards.brainio.assemblies import DataAssembly
from brainscore_core.supported_data_standar... |
bc399401230a7c9ddffcc9cea360c551e96b01b5a940cfe9bfbab9c4ecdbbfd5 | Python | 4,560 | 143 | import math
from dataclasses import dataclass
from typing import TYPE_CHECKING, Literal
from torch import Tensor, nn
from eir.models.input.array.models_locally_connected import FlattenFunc
from eir.models.input.sequence.transformer_models import (
get_positional_representation_class,
parse_dim_feedforward,
)
... |
2c42983fa406f7beaf53e10a0a5adba6e82d28d87f7bda175704641ca589d859 | Python | 4,561 | 134 | import ttach as tta
import multiprocessing.pool as mpp
import multiprocessing as mp
import time
from train_supervision import *
import argparse
from pathlib import Path
import cv2
import numpy as np
import torch
from torch import nn
from torch.utils.data import DataLoader
from tqdm import tqdm
def seed_everything(se... |
7cd8edc3b144ca5fe84e42f522574ee474eeb38030bdbbfd123729a2bfcee714 | Python | 4,561 | 140 | import torch
from torch import nn
import torch_geometric.nn as gnn
from sklearn.metrics import average_precision_score, roc_auc_score
class GNNEncoder(nn.Module):
def __init__(self, n_input, n_hidden, n_heads, n_batch=0):
super().__init__()
self.n_batch = n_batch # n_batch= -1: no batch norm, 0: ... |
2fad2d217f7be2013228d3586c170be06b70fa9b382642e9f781480536ed9bec | Python | 4,562 | 162 | from __future__ import annotations
from pathlib import Path
import pytest
from PySide6.QtCore import QMimeData
from PySide6.QtCore import QPoint
from PySide6.QtCore import QPointF
from PySide6.QtCore import Qt
from PySide6.QtCore import QUrl
from PySide6.QtGui import QDragEnterEvent
from PySide6.QtGui import QDropEve... |
0c9795336fc83f5f67e774790808c06e63541b13719125e18803c54ffd538613 | Python | 4,563 | 91 | import numpy as np
from brainscore_core import Score
from brainscore_vision import load_metric, load_ceiling, load_dataset
from brainscore_vision.benchmarks import BenchmarkBase
from brainscore_vision.benchmark_helpers.neural_common import NeuralBenchmark, average_repetition
VISUAL_DEGREES = 11.2
NUMBER_OF_TRIALS = 1... |
8f867a5d16560d93f5a6788d284504b4649b35c1a143e295e05cc595d8a18d75 | Python | 4,565 | 113 | from src.wrappers.OsipiBase import OsipiBase
import warnings
import numpy as np
import matlab.engine
class OJ_GU_bayesMATLAB(OsipiBase):
"""
Bi-exponential fitting algorithm by Oscar Jalnefjord, University of Gothenburg
"""
# I'm thinking that we define default attributes for each submission like thi... |
b05cf134f3ac878d77e3e0c6f228b5a9111cdd2c1f13b31f0fce6fefdc02dd33 | Python | 4,565 | 134 | """interp_wrapper
"""
import numpy as np
from scipy.ndimage import map_coordinates
from nsdcode.utils import isnotfinite
__all__ = ["interp_wrapper"]
def interp_wrapper(vol, coords, interptype='cubic'):
"""
interp_wrapper(vol, coords, interptype)
<vol> is a 3D matrix (can be complex-valued)
<coor... |
d258720c9779c40f08cc84c943d807de978932969234ee4a0384a2ecc210d839 | Python | 4,565 | 155 | """
A DeepReg Demo for classical nonrigid iterative pairwise registration algorithms
"""
import argparse
import os
import shutil
import h5py
import tensorflow as tf
import deepreg.model.layer as layer
import deepreg.util as util
from deepreg.registry import REGISTRY
# parser is used to simplify testing
# please run ... |
e709907aeacfcc4c62935ad5982d8013dcc094802afc33266d1e2fcbeab8818d | Python | 4,566 | 137 | import pathlib
import re
from typing import Union, List, Dict, Optional, Tuple
from napari_dmc_brainmap.utils.params_utils import load_params
def split_strings_layers(s: str, atlas_name: str, return_str: bool = False) -> Tuple[str, Union[str, int]]:
"""
Split a string into its head and tail components based ... |
f6a53c6c64dd3bcdf1ffe78abed6af9a666dc03575bf1d92aae07b81cb9c0fa0 | Python | 4,566 | 162 | import numpy as np
from scipy.constants import epsilon_0 as e0
import impedancefitter as ifit
from impedancefitter.single_shell import eps_cell_single_shell
from impedancefitter.suspensionmodels import bh_eps_model, bhcubic_eps_model, eps_sus_MW
em = 6.5
Rc = 3.8e-6 / 2.0
dm = 5e-9
km = 0.0
kcp = 0.25
ecp = 50
kmed =... |
870961c930e889ae3e24078c905eea1b45a680a164dc974a1bd3d50e11814347 | Python | 4,568 | 90 | from brainvoice.visualization import plot_spectrogram_on_axis, save_borderless, gen_spectrogram_cmap
from brainvoice.spectrogram_utils import inv_linear_spectrogram, get_better_synth_hparams
from brainvoice.waveform_utils import apply_raised_cosine_window, rms_normalize_audio
from brainvoice.models.utils import load_mo... |
d4668b610ec191a51579aaf56d7cf78eaf5091647dc4cc34eb7b7dfb9b6afd03 | Python | 4,568 | 129 | # Keywords and parameters obtained from https://wiki.fysik.dtu.dk/ase/_modules/ase/calculators/orca.html#ORCA
# Orca parameters for CompChemAgent
from typing import Optional
from pydantic import BaseModel, Field
from ase.calculators.orca import ORCA, OrcaProfile
import warnings
import os
import shutil
class OrcaCalc... |
7cf7663c6f82a5afeb81afc1b2cd4f0842e6a37091da1df808817d09757d3f6b | Python | 4,570 | 135 | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch import Tensor
from typing import Optional, List, Union
def soft_erode(img: Tensor) -> Tensor:
""" approximates morphological operations through max_pooling for 2D and 3D """
if len(img.shape) == 4:
p1 = -F.max_pool2d(-img, (3... |
f9e14c608c9c3c0d46255b32837cb9aa22a2408380acd82642839af7e4962319 | Python | 4,571 | 148 | """Unit tests for the segmentation metrics in histo_miner.evaluations.
Values here are hand-computed. get_fast_pq requires contiguous instance ids
(1..N), which every fixture below respects.
"""
import numpy as np
import pytest
from histo_miner.evaluations import get_fast_pq, remap_label
# --------------------------... |
c9c20c80751a20f6ee29135c28484d74bc6b886c32647ff6766ea85ba6517710 | Python | 4,573 | 141 | # 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... |
3b67623e1e09d44a159825e776331a348d58aa383638f633be02f7fe4c99f29d | Python | 4,574 | 121 | from numpy.typing import NDArray
from tqdm import tqdm
import h5py
import numpy as np
import os
class CentroidLabel:
""" A class to generate centroid labels for datasets.
Args:
dataset_path (str): Path to the dataset directory. """
def __init__(self, dataset_path: str):
self.dataset_path... |
3c27d24d618473cd4dafa70703941419ef1ee2155ad819bc2c8e83e942003223 | Python | 4,574 | 148 | # Copyright (c) DP Technology.
# 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.
import logging
import numpy as np
logger = logging.getLogger(__name__) # pylint: disable=invalid-name
class ... |
434244cb141934128b5e417d59cd0a2e4c6ada7e325f8e7db31b0511898bb5b0 | Python | 4,574 | 143 | from pathlib import Path
from typing import Callable, Optional
import dolfin as df
import nibabel
import numpy as np
import pyvista as pv
import scipy
import simple_mri as sm
from dolfin import inner
from panta_rhei import FenicsStorage
from gmri2fem.utils import apply_affine, nan_filter_gaussian
from i2m.vtk2mri imp... |
17d007ef3a6fc31619c6a59b031a627b4efb344fe44d50a28f781d7d0f695631 | Python | 4,575 | 125 | from ..qt import *
from .. import thalamus_pb2
import json
import asyncio
import logging
LOGGER = logging.getLogger(__name__)
class OculomaticWidget(QWidget):
def __init__(self, config, stub):
super().__init__()
self.config = config
self.stub = stub
if 'Computing' not in config:
config['Comp... |
709804b3d483b94b6e4e28d53d68b5bb7a87c2526d0e5bc863cbeb94ebe5b2a3 | Python | 4,575 | 140 | import os
import sys
sys.path.append('.')
import click as ck
import numpy as np
import pandas as pd
from collections import Counter, deque
from deepgo.utils import (
Ontology, FUNC_DICT, NAMESPACES, MOLECULAR_FUNCTION, BIOLOGICAL_PROCESS,
CELLULAR_COMPONENT, HAS_FUNCTION)
@ck.command()
@ck.option(
'--go-... |
ddc8f22c50b1afa085735efc8754b8d65fa12bb216a2ac0ca16c65d346b9c077 | Python | 4,577 | 142 | # The ImpedanceFitter is a package to fit impedance spectra to
# equivalent-circuit models using open-source software.
#
# Copyright (C) 2023 Julius Zimmermann,
# julius.zimmermann[AT]uni-rostock.de
#
# This program is free software: you can redistribute it and/or modify
# ... |
584869ff6542954a82c53484199d10488e51cf1d2f9962c910a23bba639a16f1 | Python | 4,579 | 146 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Jun 17 14:30:31 2022
@author: moritz
"""
import os
import sys
import h5py
import pytz
import numpy as np
from datetime import datetime
import matplotlib.pyplot as plt
from scipy.constants import speed_of_light
# Get time zone object for time calculatio... |
0679d1d24cee7ef632f6e57d3370713257293584750435bd3daaf914feab5561 | Python | 4,580 | 121 | from argparse import ArgumentParser
import numpy as np
import time
import torch
import torch.nn as nn
from torch.utils.data import DataLoader, Dataset
from model import SATAR
from tqdm import tqdm
import json
class MyDataset(Dataset):
def __init__(self, data, padding_value,
max_tweet_count=128, m... |
36ebc36fc554e6a6eccb4dbd36c188e5c2bc0655fdecc2dc437e2ee1dbfa13c2 | Python | 4,580 | 128 | import unittest
import logging
import numpy as np
import pandas as pd
import scipy.stats as stats
import diffxpy.api as de
class _TestSingleSfNull:
def _test_null_distribution_wald(
self,
n_cells: int,
n_genes: int,
noise_model: str
):
"""
Test... |
3e0e6142dd9e6df0a197005391802b875cfbc17d954e37eb02664e4d7b5586d2 | Python | 4,580 | 90 | import os
import subprocess
import nibabel as nib
import numpy as np
from nipype.interfaces.base import BaseInterface, BaseInterfaceInputSpec, TraitedSpec, File, Directory
from traits.api import Bool, Int, Str
class MirrorMaskInputSpec(BaseInterfaceInputSpec):
in_file = File(mandatory=True, desc='Input mask file t... |
72ce8793f1f19d27fba8be54837df20c8b0ff8d13b3f0d9180dea1568f59d2f6 | Python | 4,580 | 135 | import logging
from typing import List, Tuple
import pandas as pd
import scikit_posthocs as sp
import statsmodels.api as sm
from statsmodels.formula.api import ols
from statsmodels.sandbox.stats.multicomp import multipletests
def calculate_contrast(
results_df: pd.DataFrame,
condition_col: str,
values_co... |
9c9cb45b6c4db94913ce707498e0c53301a53c4a91a3e457043782911e87df90 | Python | 4,580 | 144 | import torch.nn
from utils.dataset import ijgiDataset as Dataset
from models.sequenceencoder import LSTMSequentialEncoder
from utils.logger import Logger, Printer, VisdomLogger
import argparse
from utils.snapshot import save, resume
import os
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argu... |
498fd032f6b237266fb130ece182aae61864f3f3e508763d74ecef51aa5e7c91 | Python | 4,581 | 111 | from src.wrappers.OsipiBase import OsipiBase
import warnings
import numpy as np
import matlab.engine
class ASD_MemorialSloanKettering_QAMPER_IVIM(OsipiBase):
"""
Bi-exponential fitting algorithm by Eve LoCastro and Amita Shukla-Dave, Memorial Sloan Kettering
"""
# I'm thinking that we define default ... |
ecac1bd0e8b40aa742d34c90384f82f1ecadc58cd398505ec36d5181dbfee061 | Python | 4,582 | 110 | """
Copyright 1999 Illinois Institute of Technology
Permission is hereby granted, free of charge, to any person obtaining
a copy of this software and associated documentation files (the
"Software"), to deal in the Software without restriction, including
without limitation the rights to use, copy, modify, merge, publis... |
f8ae4d8e37ef8ca60a250de45e03480d1ee5c0c27f186212238e5be7420632f6 | Python | 4,582 | 136 | from typing import Optional, Tuple
import torch
from torch import Tensor
from torch_geometric.experimental import (
disable_dynamic_shapes,
is_experimental_mode_enabled,
)
from torch_geometric.utils import cumsum, scatter
@disable_dynamic_shapes(required_args=['batch_size', 'max_num_nodes'])
def to_dense_ba... |
00396f719421783148c959244582a56499964943b6a44fc94bb5c80c9e404269 | Python | 4,583 | 101 | import functools
import dill
from brainscore_vision.model_helpers.activations.pytorch import PytorchWrapper
from brainscore_vision.model_helpers.activations.pytorch import load_preprocess_images
from robustness.model_utils import DummyModel
from robustness.attacker import AttackerModel
from robustness.datasets import D... |
ae9a7fa26f7c41ddce0d1b90519a87b37a6d9ef99585d39e7ed3f37eb1e2957d | Python | 4,583 | 134 | from yacs.config import CfgNode as CN
# -----------------------------------------------------------------------------
# Training config definition
# -----------------------------------------------------------------------------
_C = CN()
# -----------------------------------------------------------------------------
#... |
bdd2dc302d07afe4dd8e0a6b93b81369e4410bf16f0dde637c198636021a130b | Python | 4,583 | 111 | import os
from importlib import import_module
from pathlib import Path
cell_graph_config = {
"cell_f_list": [
'fourier',
15,
True,
[
'area',
'r_equiv',
'r_maj',
'r_min',
'angel',
'ecc',
'maj_x',
'maj_y',
'min_x'... |
cb29181e2f4d0d533c7030cd29346dde2417a556d447316c8291533d4df25ab8 | Python | 4,583 | 154 | #!/usr/bin/python
#
## @file
#
# Gooch and Housego AOTF control.
#
# Hazen 02/14
#
import storm_control.sc_hardware.serial.RS232 as RS232
import time
## AOTF
#
# Class for controlling a Gooch and Housego AOTF using RS-232 communication.
#
class AOTF(RS232.RS232):
## __init__
#
# Create the control objec... |
0a6ec7480329361a89d5a1b97525860405e3ff147446399612b7e339852329e0 | Python | 4,584 | 100 | import numpy as np
from rsatoolbox.util.searchlight import get_volume_searchlight
from rsatoolbox.data.dataset import Dataset
from nilearn.image import load_img
from nilearn.masking import compute_brain_mask
from rsatoolbox.rdm.calc import calc_rdm
from rsatoolbox.rdm import RDMs
import pickle
from rich.progress import... |
d6b944768cbcc5565d7a7a79e3f95fec2e432fc51be53d4556fbe440a0954ab5 | Python | 4,585 | 119 | from brainscore_core.supported_data_standards.brainio.assemblies import NeuronRecordingAssembly
from brainscore_vision import data_registry, stimulus_set_registry, load_stimulus_set, load_ceiling
from brainscore_core.supported_data_standards.brainio.s3 import load_stimulus_set_from_s3, load_assembly_from_s3
from brains... |
2ce2334489f3b3ab7e1ae071c44ba3eadb365d8b33ab94d5374576ebee6544a9 | Python | 4,586 | 75 | from torch.utils.data import SubsetRandomSampler
from slide.slide_helper import *
from slide.data_loader import *
from utils.detection_helper import create_anchors
from object_detection_fastai.loss.RetinaNetFocalLoss import RetinaNetFocalLoss
from object_detection_fastai.models.RetinaNet import RetinaNet
from utils.cal... |
5d0dbdab84e6f21a4e762f0d9e031e540ab3753160fc101a4e2310f33951cc1b | Python | 4,586 | 157 | import torch
import torch.nn as nn
from eir.models.tensor_broker.tensor_broker import (
CachedTensor,
attach_tensor_broker_module_injection,
)
class SimpleFusionModule(nn.Module):
def forward(self, x: torch.Tensor, cached: torch.Tensor) -> torch.Tensor:
return x + cached
def test_cache_dropout_... |
c428f9899db7bc472881056c29ce380f1b521431cbf3ef3ef30c33244f60f569 | Python | 4,588 | 121 | import pytest
import numpy as np
import SimpleITK as sitk
import torch
from fireants.io.image import BatchedImages, Image
from fireants.io.imagemask import apply_mask_to_image, generate_image_mask_allones
from fireants.registration.greedy import GreedyRegistration
import logging
logger = logging.getLogger(__name__)
l... |
2966dcc63a7106645058ea397e167ff907294b841204f8fcbd2d91ed09b8ec80 | Python | 4,590 | 123 |
import re
import os
import pandas as pd
import numpy as np
class TaxaLevel:
def __init__(self, taxa_dir:str):
self.names = None
self.nodes = None
self.taxa_dir = taxa_dir
def parse_files(self):
"""
Parses the files in the given directory and places the names
a... |
72fac15b4ef227d93debb606aad664515b0ef79a33369e3eb824b9ee2e4b0dcf | Python | 4,590 | 158 | """
Reading and writing delimited data files (with headers and comments).
"""
from itertools import count
FIRST_LINE_IS_HEADER = object()
class ParseError(Exception):
def __init__(self, *args, **kwargs):
Exception.__init__(self, *args)
self.linenum = kwargs.get("linenum", None)
def __str__(... |
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