sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
f7f83b328368e013e81e6e44fc099808044e1a96a4c42e656ddfd5510501aa44 | Python | 12,872 | 297 | # patched from https://github.com/shap/shap/blob/master/shap/plots/_beeswarm.py
# to support multiple colormaps and specifying feature columns.
# Summary plots of SHAP values across a whole dataset.
from __future__ import division
import warnings
import numpy as np
import scipy as sp
from scipy.stats import ga... |
013839745b4c36fbc3216a97e9161851a33233de95a1b63ef80309c54bf93c8c | Python | 12,876 | 326 | from typing import Optional, Tuple
import torch
import torch.nn.functional as F
from torch.nn import Linear,LayerNorm
from torch_geometric.loader import DataLoader
from torch_geometric.nn import GraphConv
from torch_geometric.data import InMemoryDataset
# from torch.optim.lr_scheduler import StepLR
import torch_geometr... |
dfa033ccb2769c11e3f0b36590d6882f8a9448da6991625efa9eae902acac688 | Python | 12,879 | 238 | from typing import Tuple
import numpy as np
import brainscore_vision
from brainscore_core.supported_data_standards.brainio.assemblies import PropertyAssembly
from brainscore_vision.benchmarks import BenchmarkBase
from brainscore_vision.benchmark_helpers.screen import place_on_screen
from brainscore_vision import load_... |
fc958ebeec89018ffa20b690a4125bb31ab6608f11947196457d67e5fff28016 | Python | 12,879 | 277 | #!/usr/bin/env python
# author: Jannes Spangenberg
# github: https://github.com/JannesSP
# website: https://jannessp.github.io
import numpy as np
import multiprocessing as mp
import pysam
import sys
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, Namespace
from os.path import exists, join, dirname,... |
7020ae498f95557fe8f196631b7bdc1433c41520067f4b56826a51605564b8fd | Python | 12,882 | 331 | import os
os.environ["CUDA_VISIBLE_DEVICES"] = "1"
import argparse
import torch
import numpy as np
import torchvision
from backbones.synpoc_gen import SynPoC
from dataset import CreateDatasetSynthesis
from skimage.metrics import structural_similarity as ssim
from skimage.metrics import peak_signal_noise_ratio as psnr
... |
8e5f35905d38af6be51b13f90af94d8d35193ef6396194a6fd225ba22cd4a563 | Python | 12,883 | 432 | from collections.abc import Generator, Iterable, Sequence
from dataclasses import dataclass
from functools import lru_cache, partial
from typing import (
TYPE_CHECKING,
Any,
Protocol,
)
import numpy as np
import torch
from timm.data.mixup import rand_bbox
from eir.data_load.data_utils import Batch, get_ou... |
00451da9fd9b75771a0fb9ef2db4775c2443a70e621af1724b4675de30216ead | Python | 12,886 | 200 | import os, collections
import numpy as np
from dataclasses import dataclass
from typing import Any, Union, Callable, Dict
# enum definitions
SEX_MALE: str = 'm'
SEX_FEMALE: str = 'f'
SEX_NONBINARY: str = 'nb'
SEX_UNDISCLOSED: int = '-'
# enum definitions
TYPE_PILOT: int = 0
TYPE_REGULAR: int = 1
# enum definitions
... |
f2602544d375954f3f8b7d63ec93a0f6d11dcb60026c6a2b929ef434c75b628b | Python | 12,886 | 380 | #!/usr/bin/env python3
"""
Robustness analysis for laminar gradients:
- Vary number of gradients (n_components) from 5 to 25
- Recompute D_inter, D_Deep, D_Mid, D_Sup for each
- Compute correlation matrices across gradient counts
- Correlate D_inter/D_Deep/D_Mid/D_Sup with Margulies G1 and G2
to check how stable the ... |
0caa8a4ea3acbb6a6b74953aa5a2aff7eb2eadc5b579762b290e9cedc4169345 | Python | 12,891 | 321 | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved
from __future__ import annotations
from collections import OrderedDict
from typing import Callable
import torch
from torch import nn
from torch.utils.checkpoint import checkpo... |
b12cbf15675d257641707a9a33cb72dba7878b1c2e9aed26ff609edce1006e1d | Python | 12,901 | 338 | # -*- coding: utf-8 -*-
# modified from: https://github.com/jc2852/QQ-NET,
# https://wcm.box.com/s/v1thrs0ezuuhb13cdho1xaoiu3bd9h5j,
# the 'QQ_NET_test_simul.ipynb' file
# Youjie Wang, 2025-08-24
import torch
import os
import torch.nn as nn
from torch.autograd import Variable
import matplotlib.pylab as plt
import ma... |
db9c55d65004808ce5e4f8065234123ec2c438546e9519ceb345b908fea51f77 | Python | 12,904 | 303 | from pathlib import Path
import json
from typing import List, Union
import pandas as pd
from natsort import natsorted
from napari_dmc_brainmap.utils.path_utils import get_info
from napari_dmc_brainmap.utils.atlas_utils import (
analysis_ml_from_atlas_coordinate,
coord_mm_transform,
get_bregma,
hemispher... |
ceccad276a0a09b43fdaf84c45fbf42ff3e61795cc0fe02e8496c03f960ebb8e | Python | 12,905 | 364 | # Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import contextlib
import math
import warnings
from functools import partial
from typing import Tuple, Type
import torch
i... |
c4f85c5d3ffbc5321e600d27a03a615a5e24643ebc7bb08b7c60de0f33c68d61 | Python | 12,908 | 242 | # @thread_worker(progress={'total': 100})
# def do_presegmentation(input_path, params_dict, channels, single_channel, regi_bool, regi_chan, preseg_params,
# start_end_im, mask_folder, output_folder, seg_type='cells'):
# """
# Perform pre-segmentation on the provided image data.
#
# Pa... |
81fc88122a0d4046382ef3c7752b40223a4eaf79b525dc508aecf3e4478293c6 | Python | 12,912 | 359 | import json
from copy import copy
from dataclasses import asdict
from pathlib import Path
from typing import TYPE_CHECKING, Any
import numpy as np
from aislib.misc_utils import ensure_path_exists
from eir.experiment_io.input_object_io_modules.array_input_io import (
load_array_input_object,
)
from eir.experiment_... |
35650f1b71f81710e074dd7957d902a5841b68d2ea7e0f6c3f450003fd678139 | Python | 12,915 | 283 | # %%
import numpy as np
import pandas as pd
import argparse
from sklearn.linear_model import LinearRegression,Ridge,Lasso
from sklearn.ensemble import RandomForestRegressor
from sklearn.tree import DecisionTreeRegressor
import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import spearmanr,mannwhitneyu,pe... |
bd02333201b73802e73eb117802ebcbcf12911cf5cbf37e323392e7c1bd0dce0 | Python | 12,915 | 344 | #!/usr/bin/env python
"""
Postprocessing of MRI segmentation masks.
Source:
Harmening, N., & Miklody, D. (2022): MRIsegmentation, doi:10.5281/zenodo.7357674
(https://github.com/harmening/MRIsegmentation)
and Andy's tools:
Yu Huang, Jacek Dmochowski, Yuzhuo Su, Abhishek Datta, Chris Rorden, Lucas
Parra: "Automated MRI... |
d4833b4b39c3cba87041a9e8297761b017e0c2093df9c3ffafec8a02cadd1ec1 | Python | 12,920 | 362 | import os
import sys
import time
import json
import numpy as np
import pandas as pd
from typing import Dict, List, Tuple, Any
from dataclasses import dataclass, field
sys.path.append(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
from src.llm_orchestrator.base_llm import BaseLLM
from src.physics_validat... |
7131bf6fa7b2314fd51908f5c8a6942bee9ced512ac5c93559658d11f5ecce54 | Python | 12,922 | 426 | import os
import random
import sys
from datetime import datetime
import numpy as np
import pandas as pd
# camera recording
import win32gui
from psychopy import core, event, visual
from psychopy.constants import FINISHED
from psychopy.hardware.emulator import launchScan
from pywinauto.application import Application
... |
dde1a2a347819a57d8c28ef13609cc4b9ab39be8a75580b329583c856618a0b2 | Python | 12,926 | 332 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
from subprocess import check_output,Popen,PIPE,STDOUT
from .utils import *
from tqdm import tqdm
def get_archived_list(pref = labdata_preferences):
preffolder = os.path.dirname(LABDATA_FILE)
archived_files = []
if 'archives' in pref.keys():
if not pref... |
87bc6eac330fc7f88d20c5b0049fddf5f3d1b60c1c50196e364fe91fc1d407b6 | Python | 12,930 | 275 | import nighres
import os
import nibabel
import numpy
import glob
import scipy.ndimage
import ants
indir = '/home/pilou/Projects/Cerebellum/Cerebellar-segmentation-ABC/ahead2/coreg/'
outdir = '/home/pilou/Projects/Cerebellum/Cerebellar-segmentation-ABC/ahead2/tissues/'
#bfimg = indir+'Ahead_brain_122017_blockface-imag... |
9faabe01a860cb21edcd02b00aca9b5bdd43ad07db1195340f52b9ed5f588385 | Python | 12,938 | 306 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Register bundle to a template for screenshots using a reference.
The template can be any MNI152 (any resolution, cropped or not)
If your in_anat has a skull, select a MNI152 template with a skull and
vice-versa.
If the bundle is already in MNI152 space, do not use --t... |
9ce37e473f829c6915c0b1d5c6cee8dcd4018c1092bbb114f2ba2ab21b172a2d | Python | 12,940 | 319 | """
MSI H&E Overlay & Tissue Annotation Tool
─────────────────────────────────────────
Interactive tool for overlaying MSI heatmaps onto H&E images,
drawing polygon ROIs, and saving tissue masks into AnnData objects.
Workflow:
1. Load processed h5ad and generate an m/z heatmap
2. Load the matching H&E image
3. I... |
154b1c787365d52927a83cf6869fc26ca04a833117f46f5baaaf9d08839fd895 | Python | 12,941 | 332 | import reprlib
from collections.abc import Sequence
from pathlib import Path
from typing import TYPE_CHECKING
import polars as pl
from eir.setup import schemas
from eir.setup.schema_modules.output_schemas_array import (
ArrayOutputSamplingConfig,
ArrayOutputTypeConfig,
)
from eir.setup.schema_modules.output_s... |
f63308487f0ce1237a81cf5e5a0d4803f4e8b4039c9082650d32ab29a930022f | Python | 12,942 | 366 | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
from functools import partial
import torch
from ult... |
d2962b928cc9d375d9118ea97962ec76389114b55b6908f9e766e98fb0fd7d54 | Python | 12,950 | 253 | """
DMC-BrainMap widget for stitching .tif and .czi files
2024 - FJ, XC
"""
# import modules
from qtpy.QtWidgets import QPushButton, QWidget, QVBoxLayout, QMessageBox
from napari import Viewer
from napari.qt.threading import thread_worker
from magicgui import magicgui
from magicgui.widgets import FunctionGui
from nat... |
528a4ff30f1ac2c3183fc93882dbf3b4d944ee258e2e4551b54b495e0a59510d | Python | 12,951 | 275 | """The styling controls a viewer exposes, and how a request maps onto them.
One declaration, used three ways: the page builds its form from it, the server
coerces and validates query parameters against it, and the tests check that
every knob is reachable. Keeping those in one place is what stops a control
from existin... |
adb3149bc17c16eefce0ac6a678aed6544b12970161c8bc5b47d690e4a30f37c | Python | 12,955 | 405 | """LLM-as-judge evaluator for ChemGraph answer and tool-call correctness.
Compares the agent's tool-call sequence and final answer against the
ground-truth tool calls and final result using a binary scoring scheme
(1 = correct, 0 = wrong). The judge receives the original query,
expected and actual tool calls, and exp... |
97db53e723861b943b2503bdcf8715adbc8b54936c6e561f11a1ddd3c83eebd4 | Python | 12,957 | 351 | import torch
import os
import json
import datetime
import matplotlib.pyplot as plt
import numpy as np
from infopath.config import load_training_opt, save_opt
def get_log_path(opt, model_path=""):
if hasattr(opt, "log_path"):
return opt.log_path
root_path = "log_dir"
curr_commit = get_commit_path(... |
be6c2fe4ebe972d90f9e5e50c6f76ad1d5540a42b1197a09964c42f53f52fd14 | Python | 12,961 | 343 | import torch
import os
import sys
import re
import glob
from pathlib import Path
import argparse
from collections import defaultdict
# Add the parent directory to sys.path
script_dir = Path(__file__).parent
project_root = script_dir
while not (project_root / 'Deps').exists() and project_root.parent != project_root:
... |
af7af32a31b0ca1928e22ebf769058232cfc09b694145eff368b3027b6b7379a | Python | 12,962 | 367 | # Copyright (C) 2022 Intel Corporation
# Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
import csv
import json
import uuid
from collections import Counter
from datetime import datetime, timedelta, timezone
from http import HTTPStatus
from io import StringIO
from time import sleep
import pytest
fro... |
04f5546a91698db19856b37f2e5022275d7fe1ba289d8cbdb154198678456863 | Python | 12,964 | 366 | # -*- coding: utf-8 -*-
import numpy as np
from nibabel.streamlines.array_sequence import ArraySequence
from scilpy.viz.color import clip_and_normalize_data_for_cmap
def add_data_as_color_dpp(sft, cmap, data, clip_outliers=False, min_range=None,
max_range=None, min_cmap=None, max_cmap=None,... |
8b76e932f41bfbadbce79f947dfc4b78cf4ca307fa3ed0b1a1b32e7f7ab69f74 | Python | 12,966 | 267 | from typing import Dict, Any
import numpy as np
import pandas as pd
import optuna
import torch
import torch.nn as nn
import torch.optim as optim
import torch.utils.data as data_utils
from sklearn.model_selection import KFold
from src.model import Net
from src.trainer import ModelTrainer, DatasetLoader
from src.preproce... |
e7eaa03071fbbf74676852373e511a8bbafa51bc27c1fede3dd0fc546dac47a0 | Python | 12,967 | 330 | import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
import jax.numpy as jnp
import jax
import os
import json
import sys
import glob
import matplotlib.colors as mcolors
from matplotlib.colors import to_rgba
from scipy.stats import spearmanr, kendalltau
import numpy as np
jax.config.update("jax_default_m... |
b52d4c7544e793182c4c364e714a4b9c198b966165730df7e6350b452bfb90d8 | Python | 12,976 | 337 | import sys
sys.path.insert(0, '../')
sys.path.insert(0, '../../')
sys.path.insert(0, '../../../')
sys.path.insert(0, '../../../ogb')
import os
import argparse
import time
from shutil import copy
import torch
import torch.nn.functional as F
from torch.utils.data import DataLoader
from ogb.linkproppred import PygLinkPr... |
b559d305ecc3bb856e5f90ac3ccefdcd65c0c61986f9f9cbe23e4c416426eadd | Python | 12,976 | 291 | import os, json, sys, shutil
sys.path.insert( 0, os.path.join( os.sep, 'usr', 'share', 'gkg', 'python' ) )
import numpy as np
import matplotlib.mlab as mlab
import matplotlib.pyplot as plt
from CopyFileDirectoryRm import *
from MWF_Preprocessing import *
from VBM_Preprocessing import *
from NODDI_Preprocessing import... |
a6880a0ed7d04b1bd6883b37602b8948e4a50bdf9a14c2ad0164d3bffdf88a92 | Python | 12,977 | 408 | import logging
import os
import pickle
from pathlib import Path
from typing import Literal
from unittest.mock import MagicMock, patch
import numpy as np
import obspy
import pandas as pd
import pytest
import requests
import scipy.signal
import torch
from obspy.clients.fdsn.header import FDSNException
import seisbench
... |
33992897a1b4128511bb5f25499379182a29de1626a5017784d71b95de8e83d2 | Python | 12,980 | 320 | # This file is part of connectome-manipulator.
#
# SPDX-License-Identifier: Apache-2.0
# Copyright (c) 2024 Blue Brain Project/EPFL
"""Collection of function for flexible nodes/edges access, to be used by model building and manipulation operations"""
import numpy as np
import pandas as pd
import libsonata
from bluep... |
5c0dc3455a105c591d84fb4d3d608dcb0f57fa6380855c7b046bc248b6984905 | Python | 12,981 | 341 | # script for the second part of figure 1. Single contrast vs multi-task localization in real data using the language dataset.
import numpy as np
import matplotlib.pyplot as plt
import OptimalBattery.evaluate as ev
import Functional_Fusion.atlas_map as am
import OptimalBattery.estimate as es
import OptimalBattery.util ... |
6c7c527523d4cb057fd596fda852a9ec61ed38a0217906a593ab9209c3145e5a | Python | 12,985 | 339 | # Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved
import logging
import os
import random
import sys
import traceback
from argparse import ArgumentParser
from copy import deepcopy
import submitit
import torch
from hydra import compose, initialize_config_module
from hydra.utils import instantiat... |
9a08e61b0225e333c9ad2317cfcb41bce90e1d045c2c941f02ed2b6db0941abb | Python | 12,985 | 223 | from PyQt5.QtWidgets import QSlider,QWidget,QGridLayout,QHBoxLayout,QVBoxLayout,QLabel,QCheckBox,QRadioButton,QSizePolicy
from PyQt5.QtCore import Qt
from PyQt5.QtGui import QPixmap,QImage
from napari_dmc_brainmap.probe_visualizer.probe_vis.probe_vis.view.QLabelMT import QLabelMT
import cv2
import numpy as np
imp... |
9f9df389884f87cc92fabd9c9c4c6d9c54c0a8c968f6c8ab55ec8b4f7ff1e721 | Python | 12,997 | 309 | import re
from scipy.io import savemat
from sklearn.model_selection import StratifiedKFold
from tqdm import tqdm
from LocationRegressionHelper import *
import time
from numpy.random import default_rng
import argparse
import platform
import numpy as np
from pathlib import Path
import requests
print("Code is running o... |
499c19570ba257c9b8f4af9b9a3d9825145abb5732d36b833315415125227c37 | Python | 12,998 | 380 | # -*- coding: utf-8 -*-
import nibabel as nib
import numpy as np
import scipy.io
import scipy.ndimage
from scilpy.io.image import get_data_as_mask
def py_fspecial_gauss(shape, sigma):
"""
Function to mimic the 'fspecial gaussian' MATLAB function
Returns a rotationally symmetric Gaussian lowpass filter o... |
a28bf8f6acfe535e553b096a5117f5f85432a89d94206355c65826c6161cd97e | Python | 13,014 | 353 | # -*- coding: utf-8 -*-
"""
Created on Thu Apr 6 20:23:41 2023
@author: axthi
"""
import numpy as np
import os
from copy import deepcopy
from scipy.spatial.transform import Rotation as R
from simnibs import mesh_io, sim_struct
from simnibs.utils.file_finder import SubjectFiles
from simnibs.utils.simnibs_logger impo... |
be350fd10623a1e715ffb34f40032738b7281d16385ab77355954d056d70645a | Python | 13,014 | 293 | '''
Script to run a relatively bare preprocessing procedure for a
given subject. Essentially, this will read the raw data, set the
relevant info, apply a notch filter for line noise (and harmonics),
apply demeaning to channels, remove excessively noisy single trials
that might poorly condition the ICA, apply a bandpass... |
9154c30470970deb7572ef96ed0f1eb0b9257e83cc090d55e6159a596e1b0d5f | Python | 13,015 | 367 | #!/usr/bin/env python3
# -*- coding: UTF-8 -*-
# Python standard library
from __future__ import print_function
from shutil import copytree
import os, sys, hashlib
import subprocess, json
def md5sum(filename, first_block_only = False, blocksize = 65536):
"""Gets md5checksum of a file in memory-safe manner.
Th... |
5a4990fe0126870db0f7c714ef2386c1e4a2e5b37e8a03df4c40ae527f93dd36 | Python | 13,016 | 319 | import torch
import os
import argparse
import datetime
import numpy as np
from torchsummary import summary
from monai.networks.nets import AttentionUnet, BasicUNetPlusPlus # , UNet
from brainCT.networks.unets import UNet, UNet3d_AG, UNet_PlusPlus4
#from torchProject.unet.unet_model import UNetModel
#from pytorch_bcnn... |
fa8e97f646e22c9ac88ca870ca98c594cd1b75fd33338efc2b5a0957b1cd416b | Python | 13,020 | 257 | #!/usr/bin/python
#-----------------------------------------------------------------------
# File : patspec.py
# Contents: pattern spectrum functions
# Author : Christian Borgelt
# History : 2013.12.03 file created
# 2013.12.06 function psp2bdr added, pspfilter adapted
# 2013.12.14 fixed a probl... |
4c44f397e9a287c9d738c807a9b1d11e1eefc7f4163ddd2482b30af9d2f3a4d7 | Python | 13,026 | 353 | """``Isocortex2dProjector``: construction, aggregation, and hemispheres.
Built from mini-CCF files through the public constructor, so this exercises
the loading code as well as the projection -- and the loading code is where a
substantial share of the known defects live.
"""
import numpy as np
import pytest
from ccf... |
4eb510bd161b87a42a6399bf4e32453a735e5fef64788658a0581c819d26e40a | Python | 13,030 | 405 | # -*- coding: utf-8 -*-
import os
import gc
import numpy as np
from time import time
import matplotlib.pyplot as plt
from collections import defaultdict
from scipy import stats
from . import latent
import torch
def reshape_for_metric(y, per_fragment, distance):
n, h, w = y.shape
if distance ... |
24414e7f1293b6a784f55d24d20bec8ea8b6c40d9eb2178de18f403adb5c03b1 | Python | 13,037 | 226 | import cv2
import numpy as np
import functools
import distinctipy as dc
from PyQt5.QtWidgets import QSlider,QWidget,QGridLayout,QHBoxLayout,QVBoxLayout,QLabel,QCheckBox,QRadioButton,QSizePolicy
from PyQt5.QtCore import Qt
from PyQt5.QtGui import QPixmap,QImage
from napari.utils.notifications import show_info
... |
964e641bf6e8552f9101d8be0133f40ddb592b0ab7df1c387add22b57b976c88 | Python | 13,039 | 342 | #!/usr/bin/env python3
# general imports
import numpy as np
import sys
import matplotlib.pyplot as plt
from tqdm import tqdm
import time
# torch imports
import torch
import torch.nn as nn
# PyTorch TensorBoard support
from torch.utils.tensorboard import SummaryWriter
from datetime import datetime
# utils imports
fr... |
c069363125252b5217bbb8baf7aeabbff8cf3b7e87be70a91d7a3e89425a68bc | Python | 13,040 | 352 | # -*- coding: utf-8 -*-
# cifar100_resnet50_td_vs_baseline.py
import copy, random, os
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.utils.data import DataLoader, random_split
from torchvision import datasets, transforms
import matplotlib.pyplot as plt
# ===... |
397338086955553ed60e6133fa1002648fb65a5af14b4825f0c6162ba82da64b | Python | 13,043 | 386 | # -*- coding: utf-8 -*-
"""Rigid registration."""
import os
import shutil as sh
from pathlib import Path
import nibabel as nb
import numpy as np
from .. import execute_command
from ..io.affine import apply_affine_chunked, read_vox2vox
from ..io.vol import copy_header, mri_convert
from ..segmentation.vol import remov... |
db9ead8976ba1d59787bac42850cd8fe986591c5ee84e05e590b16c65485e240 | Python | 13,044 | 373 | #!/usr/bin/env python
"""
The core functionality for a HAL module. All modules should be
a sub-class of this module.
Hazen 01/17
"""
import faulthandler
import traceback
from collections import deque
from PyQt5 import QtCore, QtWidgets
import storm_control.sc_library.halExceptions as halExceptions
import storm_co... |
80794e4db0a11d8eb308011aadf0b9ea58904e6a0499afaea07ef06eec8a3351 | Python | 13,051 | 259 | from pathlib import Path
from snakemake.logging import logger
import numpy as np
import pandas as pd
import os
import shutil
pd.set_option("future.no_silent_downcasting", True)
class ParamHelper:
def __init__(self,include,sampleAnnotationColumns,group,path):
"""
include: boolean. True-include th... |
559a61d864a2ca05ab8f9a2a646ba2ea90acd6ee74e79c063e3d013dee358764 | Python | 13,055 | 266 | # Copyright (c) 2026 Rohit Jena. All rights reserved.
#
# This file is part of FireANTs, distributed under the terms of
# the FireANTs License version 1.0. A copy of the license can be found
# in the LICENSE file at the root of this repository.
#
# IMPORTANT: This code is part of FireANTs and its use, reproduction, or... |
a7d00dab1dfe0bb0201ee84178d7d8cb410fe9dc418cb11b9be9aecbe7dbd66e | Python | 13,058 | 227 | from PyQt5.QtWidgets import QSlider,QWidget,QGridLayout,QHBoxLayout,QVBoxLayout,QLabel,QCheckBox,QRadioButton,QSizePolicy
from PyQt5.QtCore import Qt
from PyQt5.QtGui import QPixmap,QImage
from napari_dmc_brainmap.probe_visualizer.probe_vis.probe_vis.view.QLabelMT import QLabelMT
import cv2
import numpy as np
imp... |
ddfe13326fbec668c43a378e6e5eb952e41ba6d1fcd87cf0c493262779119b9e | Python | 13,063 | 337 | # -*- coding: utf-8 -*-
# svhn_td_vs_baseline.py
import copy, random, os, sys
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.utils.data import DataLoader, ConcatDataset
from torchvision import datasets, transforms
import matplotlib.pyplot as plt
# ==========... |
00c68d1f7447a50a069604e79f610fcc307e2bd340de1f3e090cbb807419e365 | Python | 13,066 | 406 | # coding=utf-8
"""
Tests for deepreg/model/loss/label.py in
pytest style
"""
from test.unit.util import is_equal_tf
from typing import Tuple
import numpy as np
import pytest
import tensorflow as tf
import deepreg.loss.label as label
from deepreg.constant import EPS
class TestSumSquaredDistance:
@pytest.mark.p... |
492d8196e95d4bb148bca44a940530b2a03bd6a03dbfd557eccefcdc4bbfe3a4 | Python | 13,067 | 353 | from pathlib import Path
from typing import Any
import cv2
import numpy as np
VALIDATED_IMAGE_SHAPE = (800, 1140)
CORNER_ORDER = np.float32(
[
[0.0, 0.0],
[1.0, 0.0],
[1.0, 1.0],
[0.0, 1.0],
]
)
def offsets_to_homography(offsets: Any, image_shape: tuple[int, ...]) -> np.nd... |
3d068d9850190c2553baa653ac8496d81a164c51731bd7a50921ef05307ea153 | Python | 13,070 | 416 | # from functools import wraps
# import numpy as np
# # return real part of a vector
# def real_vector(vector):
# return map(lambda x: x.real, vector)
# # return imaginary part of a vector
# def imag_vector(vector):
# return map(lambda x: x.imag, vector)
# class EpochSignalSlicer(object):
# def __init__... |
e259aad74268fd4f83a58e7e7f8923fb6aa99ef9e18cace8b9fe7c97dd0bc2f3 | Python | 13,071 | 439 | '''
Auxiliary functions for common math operations
for RSAs. Typically, these are reimplementations
of things found in scipy or numpy, but for higher
dimensional arrays.
'''
import numpy as np
from scipy.stats import rankdata
from typing import Any, Union, Callable
from . import math_torch as torch
def euclidean_1d(... |
65d46bd58692f4d012f8249064c835cf242a178c9cdca4c29a910cb7eb350a81 | Python | 13,080 | 338 | import numpy as np
import pandas as pd
import os
from sklearn.model_selection import KFold
from sklearn.metrics import accuracy_score, recall_score, f1_score, roc_auc_score, matthews_corrcoef, roc_curve
from sklearn.utils.class_weight import compute_class_weight
import tensorflow as tf
from tensorflow.keras.mode... |
1f9098dce48b13faec54654666da4696fd0b9761f3ad95d4ccdd353e3420aec5 | Python | 13,087 | 333 | import numpy as np
import pandas as pd
import Functional_Fusion.dataset as ds
import OptimalBattery.util as ut
import nibabel as nb
import Functional_Fusion.atlas_map as am
from OptimalBattery.global_config import repo_dir, data_dir
import os
from collections import OrderedDict
def make_task_library(base_dir, sessions... |
ae2e5b6ab0d0227face474196206ec93ccb308683c4fde2394834682e2014f44 | Python | 13,090 | 264 | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
from itertools import cycle
from typing import Any
import cv2
import numpy as np
from ultralytics.solutions.solutions import BaseSolution, SolutionResults # Import a parent class
from ultralytics.utils import plt... |
d20ca9a1902549344dfb68bfbfb6210b996841e620e8e51a51c7d836045909b5 | Python | 13,091 | 261 | import numpy as np
import random
import time
from scipy.stats import spearmanr
from scipy.spatial.distance import squareform
import pandas as pd
import pathlib
import argparse
import matplotlib.pyplot as plt
def corr_spearman(a, b):
return spearmanr(a, b)[0]
def corr(A, B, method='spearman'):
all_correlation... |
1624748d79b111e6245eecc738265851464e8d5cb460069977c36f275ac46594 | Python | 13,092 | 351 | from torch import nn, autograd
import torch
import torch.nn.functional as F
class MLP(nn.Module):
""" a simple 4-layer MLP """
def __init__(self, nin, nout, nh):
super().__init__()
self.net = nn.Sequential(
nn.Linear(nin, nh),
nn.LeakyReLU(0.2),
nn.Linear(n... |
1f596270b27a1d982d7b2275681e4b1eeb8fb7340f5331f331ae9ec6f2cffb9b | Python | 13,095 | 412 | """Script to correct resting state matrices with null-matrix"""
import nibabel as nb
import numpy as np
import glob
from nilearn.connectome import ConnectivityMeasure
from nilearn import plotting
import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
plt.style.use('dark_background')
ROOT = '/User... |
e158c8113874774ae38490e14d5da34fb4808eec6d7e1b2397377859c2c51fd8 | Python | 13,097 | 394 | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved
from __future__ import annotations
from torch import nn
from ultralytics.nn.modules.transformer import MLP
from ultralytics.utils.patches import torch_load
from .modules.bloc... |
61a39eae97eabaf33f39e6716b0fff551c75f2e9c9d30a773bc86f5314a581a1 | Python | 13,101 | 230 | import cv2
import numpy as np
import functools
import distinctipy as dc
from qtpy.QtWidgets import QSlider,QWidget,QGridLayout,QHBoxLayout,QVBoxLayout,QLabel,QCheckBox,QRadioButton,QSizePolicy
from qtpy.QtCore import Qt
from qtpy.QtGui import QPixmap,QImage
from napari.utils.notifications import show_info
from... |
59b7fb7dd6af2f22c55c037ed26c1329158845d03e9b5c02a7d28fc73c50b52a | Python | 13,104 | 368 | """Tests for provider readiness detection and ALCF token handling."""
import json
import pytest
from ui import alcf_auth, codex_auth, providers
@pytest.fixture()
def clean_env(monkeypatch, tmp_path):
"""Remove provider credentials and isolate token caches."""
for var in (
"OPENAI_API_KEY",
... |
e1ccf67c41dd8cf25747455c336de2f89d19152c1056e51c83b8489010f24be8 | Python | 13,104 | 315 | """
EEG Signal Processing Script
Read BDF, extract events at original sampling rate
Optionally downsample and check event timing alignment
Bandpass filter, standard montage, average reference
ICA (Picard extended) + ICLabel automatic artifact rejection
Interpolate bad channels, narrow-band filter
Epoch, ... |
a0c3ca7df060ecf925d9aa3e55ce77bf331ea8d5bf299aeceeb92a78ba4456da | Python | 13,106 | 228 | # Tests of the BIDS discovery and the batch planning of dmriprep (no processing):
# python -m unittest discover -s tests
import json
import tempfile
import unittest
from pathlib import Path
import nibabel as nib
import numpy as np
import yaml
from dtiplayground.dmri.common import bids
from dtiplayground.dmri... |
3b6bed9f1a2c290ea762bdb571ab9c87d202695ec420cf2de6408ff2102ec893 | Python | 13,123 | 349 | # Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import os
import warnings
from threading import Thread
import numpy as np
import torch
from PIL import Image
from tqdm im... |
2ff2b5f1acf6b7b2a72795ba36cae7ceb11b2f418fc91cdd30383056c0b388db | Python | 13,127 | 365 | # -*- coding: utf-8 -*-
"""
Collection of routines to detect maxima
Used for finding cells or intensity peaks.
"""
#:copyright: Copyright 2015 by Christoph Kirst, The Rockefeller University, New York City
#:license: GNU, see LICENSE.txt for details.
import sys
import numpy
#from scipy.ndimage import maximum_filter
... |
bf97a70fbc616394f4ee545bfbbd3b617b2358fce1e79f0fa87e981d3d89e52e | Python | 13,129 | 278 | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
from copy import copy, deepcopy
from pathlib import Path
import torch
from ultralytics.data import YOLOConcatDataset, build_yolo_dataset
from ultralytics.data.augment import LoadVisualPrompt
from ultralytics.model... |
13cc07d600e71e569ec7dabc696bf8202c309c1d95b50c3516a390c33cdd028e | Python | 13,130 | 340 | #############################################################################
# Copyright (C) 2020-2026 MEmilio
#
# Authors: Rene Schmieding
#
# 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 Li... |
536ab72c5462992a6856526218200a1868968c2ed8d8903f1b9acc987db84dec | Python | 13,131 | 363 | import numpy as np
import pandas as pd
import random
import torch
import esm
import torch.nn.functional as F
import torch.nn as nn
from sklearn.metrics import mean_squared_error
from scipy.stats import pearsonr, spearmanr
import random
from sklearn.metrics import root_mean_squared_error,mean_absolute_error, accuracy_sc... |
bf4a687aea0bdf2896dc8cca6035743b9351c199cba61869cf237886416c2c07 | Python | 13,133 | 259 | from sklearn.metrics import accuracy_score, f1_score, precision_score, recall_score, roc_auc_score
from layer import SimpleHGN
import pytorch_lightning as pl
from torch import nn
import torch
import argparse
from torch.optim.lr_scheduler import CosineAnnealingLR
from pytorch_lightning.callbacks import ModelCheckpoint
f... |
ebca1051106630a5ecf383a23814e2f60f5713a9c3b393bf01185fe01fd4d759 | Python | 13,133 | 334 | import numpy as np
import torch
import re
try:
from rdkit import Chem
print("Found rdkit, all good")
except ModuleNotFoundError as e:
use_rdkit = False
from warnings import warn
warn("Didn't find rdkit, this will fail")
assert use_rdkit, "Didn't find rdkit"
allowed_bonds = {'H': 1, 'C': 4, 'N'... |
d37d7ab62390737412685bfbff1b673fce746f09796028b5214feba72d5d52fa | Python | 13,135 | 386 | from collections import Counter
from math import isclose
from statistics import mean
import numpy as np
import polars as pl
import pytest
import torch
from hypothesis import given, settings
from hypothesis.strategies import integers, lists
from eir.data_load import data_loading_funcs
from eir.data_load.datasets impor... |
ef87394ba95c2bc35c5265a0f6aba83e22b6a6f95f113ae76bc1ebdddcd4e1da | Python | 13,136 | 391 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Mar 23 10:29:55 2023
@author: mgruenig
"""
BATCH_SIZE = 8192
RUN_VERSION = 'v17_2' # name of the run in tensorboard
GPU = '1' ## cuda_visible_device -> which gpu to train on
CACHE = '/home/mgruenig/tmp/tf_cache/' # prefix of the cache fi... |
97b531b6005acd8f8ad7b26e126fa8418db4a28d2f32ef981e4706191560e3cf | Python | 13,137 | 274 | #!/usr/bin/env python3
# -*- coding: utf-8
"""
Script that evaluates model on simulated data.
Created on 2020/02/03
@author romain_lopez
"""
import os
import click
import numpy as np
from utils import get_mean_normal, find_location_index_cell_type, metrics_vector, discrete_histogram
import scanpy as sc
import matpl... |
323a32d643b68ffcabc59015d05784ed63db0208a79ec98991e2732734a5802a | Python | 13,139 | 382 | # cec2017.hybrid
# Author: Duncan Tilley
# Hybrid function definitions, f11 to f20
from . import basic
from . import transforms
import numpy as np
def _shuffle_and_partition(x, shuffle, partitions):
"""
First applies the given permutation, then splits x into partitions given
the percentages.
Args:
... |
cc8b6adfa963a243bc554b08e3bf9115bd05367caac49cd0ed2716487a0a3248 | Python | 13,143 | 299 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sun Feb 4 12:05:56 2024
@author: rl05
"""
import sys
import os.path as op
import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import t
from mne.stats import permutation_cluster_1samp_test, spatio_temporal_cluster_1samp_test
sys.path.appe... |
5bcde2c99afb272520db132f19176fc2c1cffdaad00c23c77e1666ceb054fc44 | Python | 13,146 | 328 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
import json
from collections.abc import Generator
from contextlib import contextmanager
from http import HTTPStatus
from unittest import mock
import pytest
from cvat_sdk.api_client import ApiClient, Configuration, models
from shared.utils.config im... |
5bae6bc3f104b81336922374eecd93b67e6b77fedd481917fcd13f21d242d7d0 | Python | 13,147 | 342 | # ==============================================================================
# Binaries and/or source for the following packages or projects are presented under one or more of the following open
# source licenses:
# adapter.py The OpenLane Dataset Authors Apache License, Version 2.0
#
# See:
# https:/... |
c63c3a47ab60887bd6da1279b2fd8e61b4fe25b047e4709dc8f881eda5799b7d | Python | 13,149 | 375 | # -*- coding: utf-8 -*-
"""
train the image encoder and mask decoder
freeze prompt image encoder
"""
# %% setup environment
import numpy as np
import matplotlib.pyplot as plt
import os
join = os.path.join
from tqdm import tqdm
from skimage import transform
import torch
import torch.nn as nn
from torch.utils.data impo... |
c8e67260a495ddac609ce3d384f820da8b6242a3a4094d9fd8e1a82b6d649f1e | Python | 13,158 | 433 | import numpy as np
import pandas as pd
from typing import Dict, List, Tuple, Optional
import sys
import os
sys.path.append(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
from config.physics_constants import (
F, R, T_STD,
VRFBParams,
NoiseParams,
celsius_to_kelvin,
nernst_potential_... |
a9dc842796ca36e7029cdd3de6c6daa02878c84346984a6987b27825eb41f841 | Python | 13,162 | 274 | #!/usr/bin/env python3 -u
# 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 torch
from torch.utils import cpp_extension
from torch.utils.cpp_extension impo... |
95050c2b9be03a76361a515f9e547475e27556fb1b3b4c8f367ee8f43477f507 | Python | 13,164 | 188 | ### COPIED FROM https://github.com/cpilab/group-bayesian-model-comparison/blob/master/groupBMC.py ON 06/04/2024 to allow debugging
## This script was originally published under teh MIT License
'''
MIT License
Copyright (c) 2020 cpilab
Permission is hereby granted, free of charge, to any person obtaining a copy
of th... |
21ade0dfdb5fc57907c951ab584d89bedaff8b7d822ca06d3720fb66ac42059f | Python | 13,165 | 321 | from sklearn.metrics import roc_auc_score, average_precision_score
import pandas as pd
import os
import numpy as np
try:
import torch
except ImportError:
torch = None
### Evaluator for graph classification
class Evaluator:
def __init__(self, name):
self.name = name
meta_info = pd.read_csv... |
de7c29bfac2c27b94ae99a95b4fae53d18d74bdaec325affe38f8187d86d3baa | Python | 13,169 | 373 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Aug 29 15:54:00 2017
@author: ajaver
"""
import numpy as np
import cv2
import pandas as pd
from scipy.interpolate import interp1d
from .curvatures import curvature_grad
from .postures import get_length
from .helper import DataPartition, get_n_worms_est... |
e360efedd4391e238ea94d08404a7b26c8946f38512a909406cba8ac32f35634 | Python | 13,169 | 191 | # -*- coding: utf-8 -*-
"""
Created on Fri Nov 19 01:23:18 2021
@author: Yoshi
"""
import warnings
warnings.simplefilter(action="ignore",category=FutureWarning)
import os
program_path = os.getcwd()
os.chdir(f"{program_path}/motion_corrector")
from motion_corrector import *
os.chdir(f"{program_path}/data_extracto... |
09709d347141f475b99560cad8dc6cf9d971ddf22a14c21f31e6147b0db17d5c | Python | 13,170 | 323 | # Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import copy
from typing import Tuple
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as... |
31968ad2c5848cf4418cef84ff76b007fad5b036800d9cf81422dec346b48ae0 | Python | 13,173 | 283 | #
# fiberprofile/analysis/impute.py (from FiberProfileAnalysis/impute_profiles.py)
#
# Impute missing values in along-tract profile tables (the output of gather) with a per-dataset SIREN implicit neural
# representation (INR).
#
# For each dataset (one column identifier, e.g. <subject>_<session>_<prefix>) all ... |
a20dc210174597e6b818e723e3392b7c5249e19fcf78fb56beeeef7ef7b97842 | Python | 13,173 | 339 | from torch_geometric.nn import GCNConv
from sklearn.neighbors import kneighbors_graph
import torch
import numpy as np
#from ..utils.helpers import calc_gex
# define the number of neighbors (six for visium)
n_neighbors = 6
# define the simcomen class
class simcomen(torch.nn.Module):
"""
A k-hop Graph Neural Net... |
ea32ed4ec02a8a5880938f9e6f0ec6e04ca426206288e3643b04e4f1435ebc12 | Python | 13,175 | 450 | """usage: {} --cell <cell_mask> --tissue <tissue_mask> --blur <blur_mask> --image <orig_img.tif>
"""
import os
import sys
import getopt
import copy
from collections import Counter
import numpy as np
import pandas as pd
import cv2
def getfootprint(struc, a, b=None):
from skimage.morphology import (
s... |
76ea8379543aee81891e84a52afa731717146ad4052ed8e4b98c5e7b0aacda79 | Python | 13,181 | 310 | """Independent reproduction of LAION-fMRI's published 12-rep noise ceiling.
We use the per-session single-trial betas (`SingletrialBetas_statmap.nii.gz`)
and the trial→image TSVs from `derivatives/glmsingle-tedana/<sub>/<ses>/func/`,
then implement the NSD variance-based estimator (Allen et al., 2022) that the
LAION-f... |
104f5a12ad80b92e7cb30a3b1a798f8f94295b835005d5ac896db40961b3a2c0 | Python | 13,182 | 392 | import os
from os.path import join
import pyvista as pv
import numpy as np
import re
import matplotlib.pyplot as plt
import pickle
import nibabel as nib
from simnibs.utils.file_finder import SubjectFiles
def _pvmesh_from_skin_geo(infile):
# make pyvista mesh out of a skin geo file
with open(infile, "rt") as... |
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