sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
5a5602f79010cdd38a465d85425ae7166f28634252fc684e7fd2ec6a136a916b | Python | 2,135 | 57 | # 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... |
8d0be5931f02fe561020a36c31712b319b277b10b8bf1400d572fb86808e0f09 | Python | 2,135 | 48 | import torch
import math
### this was used to generate the ensemble for the two-state model during training.
def generate_two_state_ensemble(positions, dG, num_bins, min_bin, max_bin,):
# positions: shape [B, N_res, 3]
# dG: shape [B, 1]
# return: shape [B, N_res, N_res, num_bins]
lower_breaks = torch.... |
f05a192a023c82e667a480baea6295253945b92b3f0e4fbcd22aab2434a6e223 | Python | 2,136 | 67 | import tensorflow as tf
import numpy as np
from tensorflow.keras.models import load_model
from sklearn.metrics import r2_score
# GPU configuration
gpus = tf.config.experimental.list_physical_devices('GPU')
if gpus:
try:
for gpu in gpus:
tf.config.experimental.set_memory_growth(gpu, Tr... |
347cd5f630c06f4510dafe8ab16ee89158345e55d9c22e59e807aa182e4765d1 | Python | 2,138 | 51 |
import os
import logging
from glob import glob
from PIL import ImageFile
ImageFile.LOAD_TRUNCATED_IMAGES = True
def read_images_paths(dataset_folder, get_abs_path=False):
"""Find images within 'dataset_folder' and return their relative paths as a list.
If there is a file 'dataset_folder'_images_paths.txt, r... |
1334e1f0fee8b80306358ae6aa3157b925766e1ff26ab74e1e2def8a4b0483a6 | Python | 2,139 | 56 | import glob
import os
import numpy as np
import pandas as pd
list_all_neukin_df = []
skipdates = ["220818", "220819"]
input_folder = "/sc-projects/sc-proj-cc15-ag-wenger-retune/data_kinematic_states_neural/"
VICON_FS = 200
window = 300
overlap = 250
days = [i for i in next(os.walk(input_folder))[1] if i not in skip... |
20f0029c13610f5b902148b674ac088d6fe240c7cf4d0f29a41e79759f1a7e5f | Python | 2,140 | 69 | import sys
import time
import getopt
import json
from scipy.sparse import csr_matrix
import anndata
import pandas as pd
import numpy as np
from anndata import AnnData
# usage
def affine_h5ad_usage():
print("""
Usage : affine_h5ad.py -i <input.h5ad>
-o <output.h5ad>
-x [column of ... |
2389c488b2c974a770678d65834458fe81411f672fa70fa422cad740a4c4dff7 | Python | 2,140 | 60 | #!/usr/bin/env python
"""
HAL module for controlling a LUDL stage.
Hazen 05/17
"""
import math
from PyQt5 import QtCore
import storm_control.hal4000.halLib.halMessage as halMessage
import storm_control.sc_hardware.baseClasses.stageModule as stageModule
import storm_control.sc_hardware.ludl.ludl as ludl
class LudlS... |
bab06d10849b6208760d65fcd4158ce3c4a15ee411bdcd9e0686384ca9e6cfaa | Python | 2,140 | 55 | # -*- coding: utf-8 -*-
import numpy as np
import nibabel as nib
from dipy.io.stateful_tractogram import StatefulTractogram, Origin, Space
from scilpy.tractanalysis.voxel_boundary_intersection import \
subdivide_streamlines_at_voxel_faces
def test_subdivide():
# Creating a few very short streamlines (2 point... |
d98d0077f46fc4541649a494eebde469f6fd97ae34b43fb1a3f92bf9283fc901 | Python | 2,140 | 51 | import numpy as np
def get_im2col_indices(x_shape, field_height, field_width, padding=1, stride=1):
# First figure out what the size of the output should be
N, C, H, W = x_shape
assert (H + 2 * padding - field_height) % stride == 0
assert (W + 2 * padding - field_height) % stride == 0
out_height =... |
dc70ed3a0153c83a0e5b86e455577835944661834ac78f37c25f2256acca7e12 | Python | 2,140 | 51 | from dtiplayground.dmri.common.tools.base import ExternalToolWrapper
from dtiplayground.dmri.common import measure_time
import dtiplayground.dmri.common
from pathlib import Path
import subprocess as sp
import os
class NIRALUtilities(ExternalToolWrapper):
def __init__(self,binary_path= None, **kwargs): ## binary... |
15161f632e7790dc17ea6f8a99864e4b77587e01488f8e598b777f03178fe7dc | Python | 2,142 | 60 | #############################################################################
# Copyright (C) 2020-2026 MEmilio
#
# Authors: Daniel Abele
#
# 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 Licen... |
797eb7eab7fb9fc55ebed80a619a070ce881103ac1428c75abc126ac9f0b3a98 | Python | 2,142 | 69 | """MEA-Stim: electrical stimulation detection & analysis (MATLAB port).
See ``python/MEASTIM_PORT_PLAN.md`` for the port plan and parity strategy.
"""
from .detection import (
StimChannelInfo,
detect_stim_times,
get_stim_patterns,
check_stim_pattern,
)
from .cleaning import clean_spikes_from_stim
from... |
8d4dabadc0675b64f6d80380eb0b6dc3680e6d03a1601308ff2449022a10e863 | Python | 2,142 | 58 | import torch
from UBSIM.blind_SIM_functions import calc_residual
def cost_function_norm(M, predicted, psf, num_frames):
"""
The cost function for blind-SIM with normalization by average intensity added
Parameters:
M: the set of raw input sub-frames
predicted: t... |
e6fb5086d9fd42e00caa90bb81578b5f36cfe3f3ef40bc715fb90a70fc56941c | Python | 2,142 | 48 | # # a nipype interface to pad dwi
import os
import nibabel as nib
from nipype.interfaces.base import (
TraitedSpec, CommandLineInputSpec, CommandLine,
File, traits, Str
)
class PadDWIInputSpec(CommandLineInputSpec):
in_dwi = File(exists=True, mandatory=True, desc='Input DWI file', argstr='%s', position=0)... |
5abb84ccae46d3217a939543934994f316d63778778e29aa4b1449828aea2563 | Python | 2,143 | 47 | from brainscore_core.supported_data_standards.brainio.assemblies import BehavioralAssembly
from brainscore_vision import data_registry, stimulus_set_registry, load_stimulus_set
from brainscore_core.supported_data_standards.brainio.s3 import load_assembly_from_s3, load_stimulus_set_from_s3
data_registry['Lonnqvist202... |
c96ce8e2271dd3a972835634ccc8a087840d621886311c7267987e9ce0a1b220 | Python | 2,143 | 68 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Script to remove specific labels from an atlas volume.
>>> scil_labels_remove DKT_labels.nii out_labels.nii.gz -i 5001 5002
----------------------------------------------------------------------------
Reference:
[1] Al-Sharif N.B., St-Onge E., Vogel J.W., Theaud ... |
df468829c115270c866a394c820002f727933ba18fcb239a511237f5cf6383c7 | Python | 2,143 | 71 | import unittest
import numpy as np
import torch
import torch.testing as ptt
from deepdwi import fourier
if __name__ == "__main__":
unittest.main()
class TestFourier(unittest.TestCase):
def test_fft(self):
input = torch.tensor([0, 1, 0], dtype=torch.cfloat)
ptt.assert_close(
fou... |
43c07499c21511b4f195c7e8e21e157e8dcc793d7068d696ba220dd6c82ae302 | Python | 2,144 | 59 | import os
from copy import deepcopy
from typing import Optional
from deepreg.constant import KNOWN_DATA_SPLITS
from deepreg.dataset.loader.interface import DataLoader
from deepreg.registry import FILE_LOADER_CLASS, REGISTRY
def get_data_loader(data_config: dict, split: str) -> Optional[DataLoader]:
"""
Retur... |
83a24e4a9cdee3e7f1a1f61bb8d1df7ff75c272fa4a47349d532cabd786b54e5 | Python | 2,144 | 60 | import pandas as pd
import seaborn as sns
from matplotlib.axes import Axes
from rscvp.util.cli.cli_celltype import CellTypeSelectionOptions
from rscvp.util.cli.cli_output import DataOutput
from argclz import AbstractParser, argument
from neuralib.plot import plot_figure
__all__ = ['ParaCorrMatOptions']
class ParaCo... |
ae8d8a1c2ca4da3d9f99c7f1d6a1863dd03e9fd435789dbb85469f89bf6b2933 | Python | 2,144 | 71 | #!/usr/bin/env python
# author: Jannes Spangenberg
# e-mail: jannes.spangenberg@uni-jena.de
# github: https://github.com/JannesSP
# website: https://jannessp.github.io
"""
Using 9mer Gaussian models might lead to overfitting.
Using this script, we reduce the 9mer models to 5mer models by only using the middle 5 bases.... |
b520aa613185c3b140d62ab456d70197b390574760606601cac3f60048e7fcd9 | Python | 2,144 | 51 | import numpy as np
from brainscore_core.supported_data_standards.brainio.assemblies import BehavioralAssembly
from brainscore_vision import load_dataset, load_metric
from brainscore_vision.benchmark_helpers.screen import place_on_screen
from brainscore_vision.benchmarks import BenchmarkBase
from brainscore_vision.metr... |
fd45d1d317ae39bc102e3936ac5a13625c0b7769c27803646cf7d6b4018f8b1c | Python | 2,144 | 59 | import numpy as np
from argclz import AbstractParser
from neuralib.plot.plot import scatter_histplot
from rscvp.model.bayes_decoding.main_cache_bayes import ApplyBayesDecodeCache
from rscvp.model.bayes_decoding.util import calc_wrap_distance
from rscvp.util.cli import CameraOptions
from rscvp.util.util_lick import cal... |
976831f9bd5038562c9ad9125c640be7cd4054ef82d3c2cfdb905f8261a4e954 | Python | 2,145 | 49 | import pytest
import os
import re
def test_DropConfigKeys(dropConfig):
for key in dropConfig.CONFIG_KEYS:
assert dropConfig.get(key) == dropConfig.config_dict[key]
def test_DropConfigPaths(demo_dir, dropConfig):
assert dropConfig.getRoot() == f"{demo_dir}/Output"
assert dropConfig.getProcessedDat... |
071ffc89e6a70f635d37ac6b89df0fd27c5d7b9eb1e3b3cc1e28eca00ac24de5 | Python | 2,146 | 66 | # -*- coding: utf-8 -*-
import matplotlib.pyplot as plt
import numpy as np
import sys
import os
# In[]
# Generate_initial_population
def write_txt_sx_width_initial_points_540(L0, Lb, b_min, b_max):
R_bonding = Lb
element_size_ds = L0/500
bonding_ds = Lb/20
sx_width_initial_poi... |
de0d3f8ab6b5f16661098db48f84189f61e71d0441758a33720aa5e75c11745f | Python | 2,146 | 52 | from brainscore_core.supported_data_standards.brainio.assemblies import NeuronRecordingAssembly
from brainscore_vision import data_registry, stimulus_set_registry, load_stimulus_set
from brainscore_core.supported_data_standards.brainio.s3 import load_assembly_from_s3, load_stimulus_set_from_s3
BIBTEX = """@article{bas... |
797ed515f431f3077c865d684a1d704740b2aef32e3063d0185596f35ed25554 | Python | 2,148 | 56 | # by Shaoxuan Yuan at 2024/04/22
import torch
import torch.nn as nn
import torch.optim as optim
from torch.utils.data import DataLoader, TensorDataset
import numpy as np
from unet import U_Net # 从您的 UNet 文件导入模型类
# from old_unet_model import UNet # 从您的 UNet 文件导入模型类
# 加载数据集
train_images = np.load('D:/桌面/proje... |
98e4142afb1f624c6aed466daffe352ebe6770271ae65e81963ecb61960d8562 | Python | 2,148 | 79 | import csv
import pandas as pd
import torch
from tqdm import tqdm
label_list = pd.read_csv("/data2/whr/czl/TwiBot22-baselines/datasets/Twibot-20/label.csv")
label = []
for i in label_list["label"]:
if i == "bot":
label.append(1)
if i == "human":
label.append(0)
label_tensor = torch.tensor(lab... |
ee29a5ea159e7c06e73d06c1b67845529854d1cb3ed2885844a6d027d0859699 | Python | 2,148 | 55 | """Config API for specifying and running pipelines.
The config API allows you to define a full analysis pipeline (data loading,
preparation, and model training) as a YAML config and run it in a single
call. For example, to train a TDE-HMM::
config = '''
load_data:
inputs: training_data
... |
b971f5d2252fbb9e13a7e4d3185dd074e09467b9ab4c02b52a6f3c3389a5d399 | Python | 2,149 | 69 | import datajoint as dj
from .experiment import BrainArea, Layer
from .preprocess import ExtractRaw, Prepare, Slice, MaskCoordinates
import numpy as np
schema = dj.schema('pipeline_map', locals())
schema.spawn_missing_classes()
@schema
class LayerMembership(dj.Computed):
definition = """
-> ExtractRaw.GalvoRO... |
13224ef9930156a11607005fd5be8f567b8171ddac9e949282d7ea994b0ba179 | Python | 2,150 | 78 | #!/usr/bin/env python3
"""
sa.py
Parse and possibly sanity-check a .sa file output by bowtie2-build in --sa
mode. These files have a very simple format: first is a uint32_t containing
the length of the suffix array, the rest is an array of that many uint32_ts
containing the suffix array.
"""
import sys
import struc... |
8d702c6213af4c4d38314df726da0dcc160e66e97b1a6918845899d8f1a8dbf2 | Python | 2,150 | 64 | import torch
from torch import Tensor
import torch.nn as nn
from typing import List, Union, Tuple
class SpatialEmbedding(nn.Module):
def __init__(self, backbone: nn.Module):
"""
A model architecture for skoots-based spatial embeddings.
:param backbone:
:type backbone:
"""
... |
2a196341bae514aeb1e7af9c58cf9824e670eec17e2e04b44046baa7836f1431 | Python | 2,151 | 58 | # Copyright (c) OpenMMLab. All rights reserved.
import mmcv
import torch.nn as nn
from mmcv.cnn import ConvModule
from .make_divisible import make_divisible
class SELayer(nn.Module):
"""Squeeze-and-Excitation Module.
Args:
channels (int): The input (and output) channels of the SE layer.
rati... |
9bdb76e9908b5f4734759a64854b93d6d63dce11c626c3f756ef5b30e3d8279f | Python | 2,151 | 94 | class Animal:
"""
Animal metadata container for experimental subjects.
Parameters
----------
animal_id : str or int
Unique identifier for the animal.
name : str, optional
Name of the animal.
dob : str or datetime, optional
Date of birth.
sex : str, optional
... |
9e9ee0858302f1973cb4eb7e841957fd7f9d99264c6e2dbf5f2be8989bd3330d | Python | 2,151 | 71 | from typing import Tuple
import torch
from batchgeneratorsv2.transforms.base.basic_transform import BasicTransform
class MirrorTransform(BasicTransform):
def __init__(self, allowed_axes: Tuple[int, ...]):
super().__init__()
self.allowed_axes = allowed_axes
def get_parameters(self, **data_di... |
b04d36e77d34367adb39c19d24abd6472c87404a1d647fb65aa943eb46388a76 | Python | 2,151 | 67 | #!/usr/bin/env python
# This file is part of connectome-manipulator.
#
# SPDX-License-Identifier: Apache-2.0
# Copyright (c) 2024 Blue Brain Project/EPFL
import importlib.util
from setuptools import setup, find_packages
# read the contents of the README file
with open("README.rst", encoding="utf-8") as f:
README... |
ccfa2dcda6c211b03c838f552d01f216f67a8972c986f138848252056317ff33 | Python | 2,151 | 48 | import strawC, numpy as np, random, argparse, gzip, pandas as pd
def readStrawCResult(result, bin_offset=0):
i, j, v = [], [], []
for r in result:
i.append(r.binX)
j.append(r.binY)
v.append(r.counts)
return np.array(i, dtype=int), np.array(j, dtype=int), np.array(v, dtype=float)
... |
a8d4e9a4de96a5e1a01f7de171311caa6261dad4912976081f8aa7eb343b6e4d | Python | 2,152 | 68 | """Tests for locomotion.tasks.two_tap."""
import cluster.multi_gpu as multi_gpu
import functools
from absl.testing import absltest
import numpy as np
import os
DEMO_PATH = "../demo/markerless_mouse1"
CONFIG_PATH = "../tests/configs/dannce_mouse_config.yaml"
DANNCE_PATH = "../tests/configs/label3d_dannce.mat"
class... |
e7edf0498c60b6ba0b56338ab135e61343151dd0d40f5e907dd6196bd0062d34 | Python | 2,152 | 63 | # -*- coding: utf-8 -*-
"""
Created on Sun Mar 27 14:08:48 2022
@author: Artur Klepaczko
"""
import csv
from itertools import product
from pathlib import Path
from typing import Final
import numpy as np
from glcm_extractor import get_glcm_feature_vector
from shape_extractor import get_shape_feature_vector
ROOT: F... |
f493f7f5046cffb5b015fe1852a83a931663813e6ac99637d7dacc93d7834697 | Python | 2,152 | 85 | import numpy as np
import torch
import pickle
import os, sys
import glob
import pandas as pd
input_folder = sys.argv[1]
subset = sys.argv[2]
split = torch.load("./split_dict.pt")
valid_index = split[subset]
def flatten(d, index):
res = []
for x in d:
res.extend(x[index])
return np.array(res)
... |
d31a83f012339ed52f0d05397f387338cacf5be3cf114beb1c21cb08f846c5b8 | Python | 2,153 | 61 | from __future__ import annotations
from pathlib import Path
import numpy as np
import pytest
from pytestqt.qtbot import QtBot
from ..conftest import close_or_pause
from .conftest import MainWinFactory
from .conftest import draw_and_commit_polygon
from .conftest import select_shape
from .conftest import show_window_a... |
79b96a83365dc54fe8fdb41d1336344fb5512119eb7ef44ad02b8d99155dfbee | Python | 2,154 | 58 | import functools
from brainscore_vision.model_helpers.activations.pytorch import PytorchWrapper
from brainscore_vision.model_helpers.check_submission import check_models
from brainscore_vision.model_helpers.activations.pytorch import load_preprocess_images
import torch
from .evnet.evnet import EVNet
def get_model(name... |
19ddb434489b6533d870eaa1480ee4b211efb016ae51fbc6f4a1be54ae1b29f2 | Python | 2,155 | 74 | # -*- coding: utf-8 -*-
"""
Show low resolution of colour system
With this script, the low resolution of colour perception can be shown. An rgb
image is read and converted to greyscale. Then, a grid is defined on the image
and only the grid points are coloured by a smoothed version of the initial
colour image.
"""
#... |
adaeb82ce361922cafba83259b1be4f8a96aac799fae227c118f2d916cdae872 | Python | 2,155 | 60 | # Configuration file for the Sphinx documentation builder.
#
# For the full list of built-in configuration values, see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Project information -----------------------------------------------------
# https://www.sphinx-doc.org/en/master... |
47979406358347d8b6ace735f09d82c05437dcdd1b9f258732c28bb3c20c0a18 | Python | 2,156 | 39 | from string import ascii_lowercase as alphabet
import numpy as np
from pytest import approx
from brainscore_core.supported_data_standards.brainio.assemblies import NeuroidAssembly, DataAssembly
from brainscore_vision import load_ceiling
from .ceiling import PearsonCorrelation
class TestInternalConsistency:
def ... |
ebd631ede08a1f9925132e09d165f852be6b679182c7303c4af41ff2f192401c | Python | 2,157 | 67 | """
Example of how to use the prediction pipeline inside osl-dynamics
to perform a grid search and nested cross-validation.
This script is based on simulated data.
"""
import numpy as np
from osl_dynamics.analysis import prediction
from osl_dynamics.utils.misc import set_random_seed
set_random_seed(42)
# Create a ... |
a31102a703ef1e0e446f040be8384862db10f2302e74e0723c74bbc32d69359b | Python | 2,158 | 62 | import nilearn
import nilearn.plotting
import scipy
import nilearn.image
import numpy as np
import pickle
import fire
import matplotlib.colors as colors
import matplotlib.pyplot as plt
from matplotlib.colors import LinearSegmentedColormap
from matplotlib.colors import ListedColormap, BoundaryNorm
task = "category"
ba... |
fd572ec9081b73d4479f3af176122d50be65a268369f3c9ea8e06d6bebafc191 | Python | 2,158 | 74 | """
.. _surface_picking_example:
Picking a Point on the Surface of a Mesh
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
This example demonstrates how to pick meshes using
:func:`surface_mesh_picking() <pyvista.Plotter.enable_surface_picking>`.
This allows you to pick points on the surface of a mesh.
"""
############ IMPO... |
1891f0b0a91ac442076b7b628ddb6ecaff024c4097dd5d8f873ae8ec8d16edd1 | Python | 2,159 | 68 | from xml.dom.minidom import parse
import xml.dom.minidom
import numpy as np
import sys
import getopt
import json
#Usage
def get_xml_matrix_usage():
print("""
Usage : SEAM.py get_xml_matrix -i <file.xml>
-o <output>
""",flush=True)
def get_trackEM_forward(param :str) -> np.matrix:
... |
44a12d89629f0bd394e5c9fce58b54459e5597cef4c3cd69c7b5742f85a8e2eb | Python | 2,160 | 57 | """Test the functions in the yasa/heart.py file."""
import unittest
import numpy as np
from yasa.fetchers import fetch_sample
from yasa.heart import hrv_stage
# Load data
ecg_filepath = fetch_sample("ECG_8hrs_200Hz.npz")
ecg_file = np.load(ecg_filepath)
data = ecg_file["data"]
sf = int(ecg_file["sf"])
hypno = ecg_f... |
6fc490053428384f807d1e36ff5312d9a69558aaecb7a3a52e6882e184813d43 | Python | 2,160 | 71 | import pytest
import os
import numpy as np
import pandas as pd
from collections import OrderedDict
from impedancefitter import get_equivalent_circuit_model, PostProcess, Fitter
from openturns import Distribution, TestResult
@pytest.fixture
def postprocessRC():
f = np.logspace(1, 8)
omega = 2. * np.pi * f
... |
ab715e1fe85fb191c39fb39343971a1cd184eedc86b975fb0d001a762ef8f44f | Python | 2,160 | 71 | # The ImpedanceFitter is a package to fit impedance spectra to
# equivalent-circuit models using open-source software.
#
# Copyright (C) 2021, 2022 Julius Zimmermann,
# julius.zimmermann[AT]uni-rostock.de
#
# This program is free software: you can redistribute it and/or mod... |
af9d5d0a2d1b50cb03bae0663420002316fc95ea2dfd9c2d80d30bca9179506f | Python | 2,160 | 76 | """
Wrappers for VTK lookup tables.
"""
# Author: Oualid Benkarim <oualid.benkarim@mcgill.ca>
# License: BSD 3 clause
from vtk.util.vtkConstants import VTK_STRING, VTK_UNSIGNED_CHAR
from .base import BSVTKObjectWrapper
from ..decorators import unwrap_input
class BSScalarsToColors(BSVTKObjectWrapper):
"""Wrapp... |
e42488547c8b2762e624ddec33190c6455e79d78fdaea34da4ef3645d20ad111 | Python | 2,160 | 65 | """Deprecated compatibility shim for OpenAI / Argo model loading.
The construction logic now lives in ``chemgraph.models.endpoints.openai_direct``
and ``chemgraph.models.endpoints.argo`` behind shared protocol builders. Prefer
``chemgraph.models.loader.load_chat_model``, which routes Argo Claude models
through the Ant... |
153d30e7537178065ac8b3ff19bb947448c3d3f0e66a48780a7b1049413e43db | Python | 2,161 | 57 | import torch
from torch_geometric.data import Data
from torch_geometric.data.datapipes import functional_transform
from torch_geometric.transforms import BaseTransform
from torch_geometric.utils import to_scipy_sparse_matrix
@functional_transform('largest_connected_components')
class LargestConnectedComponents(BaseT... |
439ea8ea607ed87c238044996ae57c404254f49b072b6bd513b8edff386fc014 | Python | 2,161 | 60 | #!/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=['tractometry.zip'])
tmp_dir = tempfile.... |
bef3c0c2f83cb5fa61d68ccbdde1b0dfe025ed15155edfb1a587c4243973883f | Python | 2,161 | 89 | #!/usr/bin/env python3
import argparse
import numpy as np
from ase import io
from ase.io.trajectory import Trajectory
from ase.io import read, write
from HessKerNNCalculator.KerNNCalculator import *
from os.path import splitext
import ase.units as units
'''
Usage: python3 NN_NM.py -i structure.xyz
'''
#parse comman... |
3d427d116d1048ec82a5b01263e561e420d7b3a30d73d3c34f62e74633fcae1b | Python | 2,162 | 70 | """Mask files.
- MNI152_T1_1mm_brain.nii.gz
- MNI152_T1_2mm_brain.nii.gz
- MNI152_T1_8mm_brain.nii.gz
- ft_8mm_brain_mask.nii.gz
Mask files can be resampled in FSL, e.g. to resample the 1x1x1 mm grid MNI mask file to a 5x5x5 mm grid:
.. code::
flirt -in $FSLDIR/data/standard/MNI152_T1_1mm_brain.nii.gz -ref $FSL... |
1192315334a7aef58f3a1ba668a4a661f0b6f93428dd28e3879922e61b6fed58 | Python | 2,163 | 89 | import arbor as A
from arbor import units as U
import matplotlib.pyplot as plt
from pathlib import Path
import numpy as np
here = Path(__file__).parent
ctr = "(location 0 0.5)"
mrf = A.load_swc_neuron(here / "Acker2008.swc")
dec = (
A.decor()
.set_property(Vm=-55 * U.mV)
.paint('"soma"', A.density("hh"... |
5dba8adc62b7352464a843ae3962b6ad19c1c50c2e66190d5ce143777fd3082d | Python | 2,163 | 63 | import torch
from utils import common_functions as c_f
from reducers.base_reducer import BaseReducer
from reducers.mean_reducer import MeanReducer
def aggregation_func(x, num_per_row):
zero_denom = num_per_row == 0
x = torch.sum(x, dim=1) / num_per_row
x[zero_denom] = 0
return x
class PerAnchorRedu... |
c6019046943c1ac2f65846e636320ebc43a4f7ff8a9efeafc7651bfe30ed3e98 | Python | 2,163 | 96 | """
utilites to read the linemod dataset to numpy types
@author Pavel Rojtberg <https://github.com/paroj>
"""
import numpy as np
def _parse_ply_header(f):
assert f.readline().strip() == "ply"
vtx_count = 0
idx_count = 0
for l in f:
if l.strip() == "end_header":
break
elif... |
c07f5c274b106c581d7393c33fecdd1ca78a2eb8209f1811d03da9d8ca8ed53c | Python | 2,164 | 45 | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'selectstack.ui'
#
# Created by: PyQt5 UI code generator 5.7.1
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore, QtGui, QtWidgets
class Ui_selectStack(object):
def setupUi(self, selectStack):
sel... |
52a0e60f0bece2c7d364ccd24f0a873384562b07accceeb69ed48c6c4c120c89 | Python | 2,165 | 66 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import os
import tempfile
import numpy as np
import nibabel as nib
from scilpy.io.streamlines import save_tractogram
from dipy.io.stateful_tractogram import StatefulTractogram, Space, Origin
tmp_dir = tempfile.TemporaryDirectory()
def init_data():
streamlines = [[... |
c57ec0483a034e6fd3c9c6f1e858f2395da8d4354885b33da6ee44666d128a40 | Python | 2,165 | 43 | from tests.common import *
class Test_RVC_Pipeline:
# change the third instance of "run: true" to "run: false" to turn off the RVC module
# run the RVC module using this config_RVC_norun (which should do nothing)
def test_pipeline_no_run(self,demo_dir):
LOGGER.info("run RNA variant calling pipeline with ... |
90ff47346c0ae0ec1a873584c793abb9ec620196e0c11e86dff3bdc7e83b54aa | Python | 2,166 | 56 | import matplotlib
import numpy as np
from matplotlib.colors import LinearSegmentedColormap
font = {'family': 'serif',
# 'serif': ['Computer Modern'],
'serif': ['Helvetica', 'DejaVu Sans'],
# 'weight': 'bold',
'size': 8}
savefig = {'bbox': 'tight',
'pad_inches': 0.01,
... |
f7670b245760fb618549f98c742bfe6ae03f27e77d7bfe82901aee990554a4cc | Python | 2,167 | 70 | # -*- coding: utf-8 -*-
# python standard library inputs
import os
import datetime
# external inputs
from nipype.interfaces.freesurfer import VolumeMask
def get_ribbon_fsurf(path, sub):
"""Get ribbon fsurf.
This function calculates the grey matter ribbon mask using a wrapped
freesurfer function. Old f... |
3f9bd70aebbfd294daddadab37aae01f4833299d1f765366b47fccd28e4a0d5e | Python | 2,168 | 62 | """Run the ALCF IRI Facility API workflow through the ChemGraph agent.
Uses the ``single_agent_iri`` workflow, which can be bound to either of
two shipped tool sets (both cover ALCF's IRI REST API at
https://api.alcf.anl.gov):
* ALCF_IRI_FLAT_TOOLS -- 43 direct tool wrappers (default;
... |
4884b77015f8b405a583cbffdcf5277847523df5cfac8340de20a8d5cc07ac36 | Python | 2,168 | 71 | import seaborn as sns
import matplotlib.pyplot as plt
import pandas as pd
import glob
import os
wk_dir = snakemake.params.wk_dir
opdf = snakemake.output.opdf
opng = snakemake.output.opng
dfs = []
for statf in glob.glob(os.path.join(wk_dir, '*/logs/stats_summary.txt')):
dfs.append(pd.read_table(statf))
a = pd.conc... |
b20142784a989e587f3fac4173d6f6834a87ed5d9c1998d0d5c9f215684e6bbd | Python | 2,168 | 67 | from tomocupy_stream import GPURecRAM
from tomocupy_stream import find_center
import h5py
import numpy as np
import tifffile
# init data, dark, flat, theta
with h5py.File('data/test_data.h5', 'r') as fid:
data = fid['/exchange/data'][:, :, :]
dark = fid['/exchange/data_dark'][:]
flat = fid['/exchange/data... |
c9ba3e600c502edbd6b1349631da6ec59baec85d76483b97ad19f3d7e0069e47 | Python | 2,168 | 52 | import imageio
from tqdm import tqdm
import warnings
from .util import generate_frames, filter_frames_index_function, apply_filters, discretize
from math import ceil
def zebra_noise(output_file, xsize, ysize, tdur, levels=10, xyscale=.2, tscale=50, fps=30, xscale=1.0, yscale=1.0, seed=0, filters=[("comb", 0.08)]):
... |
3f1b6a7d046546014f41f75bbc7765c2d909297aa8feff4e747445bded1cad76 | Python | 2,169 | 24 | from brainscore_vision import benchmark_registry
from .benchmark import Allen2022fmriSurface, Allen2022fmriSurfaceRSA
# Default: 8 subjects, 515 images
benchmark_registry['Allen2022_fmri_surface.V1-ridge'] = lambda: Allen2022fmriSurface('V1', 'ridge')
benchmark_registry['Allen2022_fmri_surface.V2-ridge'] = lambda: All... |
0be15b505d1f98e2b00a22db6d2f29074566e956e699a2dfdc1c3c09daa30064 | Python | 2,170 | 79 | import unittest
import warnings
from unittest.mock import patch
from rscvp.model.glm.main_eval import BehavioralGLMOptions
from .util import check_attr
class TestGLMModule(unittest.TestCase):
"""Test in ``model.glm`` module and relevant statistic locally"""
@classmethod
def setUpClass(cls):
warn... |
2acd0dadf733301fbfc46ccc65d3adab1af40fde985a5c67311f96166acba4ac | Python | 2,170 | 47 | import os
from nipype.interfaces.base import (CommandLineInputSpec, CommandLine, traits, TraitedSpec, BaseInterface, BaseInterfaceInputSpec, File)
from traits.api import Directory, Str, List, Bool, Enum, Int, Float, TraitError, Either
# binarize an image under a threshold
class FSLMathsUnderThrInputSpec(CommandLineInp... |
dde6e983d05b195eefb1d832669c58cad709941c1b778eb8f852a52da5b580be | Python | 2,170 | 68 | import nibabel as nb
import numpy as np
import subprocess
import os
import glob
subs = ['sub-05']
digits = ['D2', 'D3', 'D4']
for sub in subs:
volumes = sorted(glob.glob(f'/home/sebastian/Desktop/patchFlatten/{sub}_done/upsampled/registeredFunc/regTmp/vol_*_reg.nii.gz'))
nrVols = len(volumes)
layerFil... |
0d334ad389e9951a2985f31d49d3fbda688db53e4b3a0cacc1fe120512982234 | Python | 2,172 | 68 | import click
from matplotlib import pyplot as plt
import numpy as np
import pandas as pd
from cycler import cycler
purple = [.5, 0, .5, 0.9]
purple_light = [.5,0,.5, 0.3]
green = [0, 1, 0, 0.9]
green_light = [0,1,0,.3]
blue = [1,.3,0, .9]
blue_light = [1,.3,0,.3]
colors = [purple,green, blue]
colors_light = [purple_l... |
a3d18e072b6445b6845fa157eccfc8b1da1ce62335a39141522a945807e981fe | Python | 2,172 | 71 | # The ImpedanceFitter is a package to fit impedance spectra to
# equivalent-circuit models using open-source software.
#
# Copyright (C) 2018, 2019 Leonard Thiele, leonard.thiele[AT]uni-rostock.de
# Copyright (C) 2018, 2019, 2020 Julius Zimmermann,
# julius.zimmermann[AT]un... |
6d19ffdf1b5edc435893952c5deec1ff4f8a3457e86262d9102bdf7c9a93df47 | Python | 2,174 | 64 | # -*- coding: utf-8 -*-
"""
Method to extend interpolation objects to constantly / linearly extrapolate.
"""
#:copyright: Copyright 2015 by Christoph Kirst, The Rockefeller University, New York City
#:license: GNU, see LICENSE.txt for details.
import scipy.interpolate
from numpy import array
def extrap1d(x, y, int... |
850d9fdb11c84a7264d73246b959bcb6de6ae5b27b567800cca7c014d0c956db | Python | 2,174 | 60 | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
# If ex... |
b71f055e2b04627c6d552c3c2b46d505936da0bf80b1f2e51ba3639d7ab0a7d0 | Python | 2,175 | 45 | import os,sys
import torch
import argparse
from chinn.models import PartialDeepSeaModel, NNClassifier
from chinn import train
def get_args():
parser = argparse.ArgumentParser(description="Train distance matched models")
parser.add_argument('data_name', help='The name of the data')
parser.add_argument('mod... |
18b4afe964263e0e6fa2a3a85d0ade0385d435b863b465d44850c6e6fc1133bc | Python | 2,176 | 67 | import ants
import antspynet
import sys
import os.path
from os import path
import tensorflow as tf
t1_file = sys.argv[1]
output_prefix = sys.argv[2]
threads = int(sys.argv[3])
tf.keras.backend.clear_session()
config = tf.compat.v1.ConfigProto(intra_op_parallelism_threads=threads,
i... |
b8b97a572a0ae966d1bdc36b860f9791ee039065fafca4503beb697ae1481884 | Python | 2,176 | 56 | import serial
from psychopy import core
def identify_targets():
# make list with one dict per port. Dict contains port and boolean that controls if it will be used
sers = [{'ser': serial.Serial(
f"/dev/ttyUSB{ser_num}", timeout=0), 'use': False} for ser_num in [0, 1]]
for target in ['Buttons', 'Se... |
cdacc18966b23c72eacb33fba690ab847b6aaa1cd0284f1c4ddd9d6f12e6ad54 | Python | 2,176 | 67 | """Example for running TINDA on MEG data from the Nottingham MEGUK dataset.
"""
import os
import pickle
import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import ttest_rel
from osl_dynamics.inference import modes
from osl_dynamics.analysis.tinda import tinda, plot_cycle, optimise_sequence
def get_d... |
f378cf0b464f2ac5e1daf3609ba25fd51c7e34f294846281707ffe006c3e9ef1 | Python | 2,176 | 84 | import pandas as pd
import numpy as np
##########
# analysis
def load_exps(l_pqt):
'''Load simulation results from disk
Parameters
----------
l_pkl : list
List of parquet files with simulation results
Returns
-------
exps : df
data for all experiments 'path_res'
'''
... |
4fe462bdf4e91076bb4a46683f271dfe7855a35f628c80d69ddd39a3ebf61626 | Python | 2,177 | 75 | import functools
import hashlib
import importlib
import io
import tarfile
from pathlib import Path
from django.conf import settings
from django.contrib.sessions.backends.base import SessionBase
_OPA_RULES_PATHS = {
Path(__file__).parent / "rules",
}
@functools.lru_cache(maxsize=None)
def get_opa_bundle() -> tup... |
97d83b34ff6e03d1978aec441bce3463d16b90f1c1d00200e497ecb6b0a84b81 | Python | 2,178 | 60 | from nipype import IdentityInterface, Function
from PUMI.engine import NestedWorkflow as Workflow
from PUMI.engine import NestedNode as Node
from nipype.interfaces import BIDSDataGrabber, fsl
from nipype.utils.filemanip import list_to_filename
from PUMI.pipelines.anat.segmentation import bet_fsl, bet_hd
import os
# ex... |
df57374c143ca41b115d737e71f753fab93980c774a8a32d93bc0275dd8b5d72 | Python | 2,178 | 76 | import pandas as pd
import scipy.stats as stats
import pyfocus
__all__ = ["GWAS", "GWASSeries"]
class GWASSeries(pd.Series):
@property
def _constructor(self):
return pyfocus.GWASSeries
@property
def _constructor_expanddim(self):
return pyfocus.GWAS
class GWAS(pd.DataFrame):
""... |
e2f7ad800dab230cc58eeea76062ab2f4ea17cc89d125985d651b38035ce43a2 | Python | 2,180 | 66 | import sys,os
from setuptools import setup, find_packages
from os.path import join as pjoin, dirname, exists
from glob import glob
from dtiplayground.config import INFO as info
using_setuptools = 'setuptools' in sys.modules
extra_setuptools_args = {}
if using_setuptools:
# Set setuptools extra arguments
extra... |
db611a4bc8c2aa84e1c5f58302a1598c436921c384d11613b369d5015492fce3 | Python | 2,182 | 101 | import numpy as np
from scipy.constants import epsilon_0 as e0
from impedancefitter.cole_cole import cole_cole_R_model
from impedancefitter.RC import RC_model, drc_model, rc_model, rc_tau_model
omega = 2.0 * np.pi * np.logspace(1, 8, num=20)
# parameters are chosen that multiple models yield same result
# for RCfull... |
e55db7365223cf6c41c67ff410929119436369c9255d8a662e70003af1a27387 | Python | 2,182 | 55 | from eir.models.model_setup_modules.output_model_setup_modules import al_output_modules
from eir.models.output.tabular.linear import (
LinearOutputModule,
LinearOutputModuleConfig,
)
from eir.models.output.tabular.mlp_residual import (
ResidualMLPOutputModule,
ResidualMLPOutputModuleConfig,
)
from eir.m... |
a9b5667ac0330eeaccbee694eb722f2af435afd3db644ad5e4a79f37c129d621 | Python | 2,185 | 60 | import argparse
import torch
from torch_geometric.nn import Node2Vec
from torch_geometric.utils import to_undirected
from ogb.nodeproppred import PygNodePropPredDataset
def save_embedding(model):
torch.save(model.embedding.weight.data.cpu(), 'embedding.pt')
def main():
parser = argparse.ArgumentParser(des... |
f4ed7c43b25ea935971eaa8f4841a637d78be287129bb6885ecb25689b38fdf9 | Python | 2,185 | 64 | #!/usr/bin/env python3
import configparser
import re
import sys
from pathlib import Path
REPO_ROOT = Path(__file__).resolve().parents[1]
RE_PLACEHOLDER_PR_URL = re.compile(r"//github\.com/[\w.-]+/[\w.-]+/pull/X")
def main():
scriv_config = configparser.ConfigParser()
scriv_config.read(REPO_ROOT / "changelo... |
1041c0c1a51dd4a2406c74d53d88c12338914573010e4ee54cd786e8428b708d | Python | 2,186 | 67 | # Generated by Django 3.2.14 on 2022-07-18 06:37
import os
import shutil
from django.conf import settings
from django.db import migrations
from cvat.apps.engine.log import get_logger
MIGRATION_NAME = os.path.splitext(os.path.basename(__file__))[0]
MIGRATION_LOG = os.path.join(settings.MIGRATIONS_LOGS_ROOT, f"{MIGRA... |
1082625354bf298035fbdeb3738ae783aa10ae4acff5bdb5afbc634323ff1e07 | Python | 2,186 | 48 | #!/usr/bin/python
#########################################
# Author: Yunjiang Qiu <serein927@gmail.com>
# File: restriction_cut.py
# Create Date: 2015-02-27 16:46:15
#########################################
import sys
import argparse
from Bio import SeqIO
from Bio.SeqUtils import GC
import re
def find_site(fasta,s... |
7b8fc4efbf42f8d47ab0144df57b9c0d14c7be3ca3a7aac58dd697e1338e73bd | Python | 2,186 | 68 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
from io import BytesIO
import boto3
from botocore.exceptions import ClientError
from shared.utils.config import MOTO_ENDPOINT_URL, MOTO_KEY, MOTO_SECRET_KEY
class S3Client:
def __init__(
self, endpoint_url: str, *, access_key: str, se... |
aefec70e0e34eef39835cd05dc5f643731d4285261253a91508ce041468942af | Python | 2,186 | 58 | import functools
from brainscore_vision.model_helpers.activations.pytorch import PytorchWrapper
from brainscore_vision.model_helpers.check_submission import check_models
from brainscore_vision.model_helpers.activations.pytorch import load_preprocess_images
import torch
from .evnet.evnet import EVNet
def get_model(name... |
ce40626ddccebdad3f589e57eea8d67976c4ee2501b749021c1554216e493a1e | Python | 2,186 | 45 | import os
import sys
import json
from mako.template import Template
sys.path.append(os.path.abspath(os.path.dirname(os.path.realpath(__file__))))
from macularCellFactoryGenerator import load_jsons as load_cell_jsons
from macularSynapseFactoryGenerator import load_jsons as load_synapse_jsons
def generate_header(json_... |
3ba1b748786ea26f370d7957b68b11c3847cd40754963eb670cf9a11557a3c08 | Python | 2,187 | 61 | import json
from tqdm import tqdm
from MyBotometer import Botometer, NoTimelineError
from tweepy.error import TweepError
import tweepy
from argparse import ArgumentParser
import os
if __name__ == '__main__':
parser = ArgumentParser()
parser.add_argument('--dataset_name', type=str)
parser.add_argument('--p... |
9b2e9c851900d713e2ed94332b2f25d55331ab93521f400b7d2f406ca7bbc50f | Python | 2,187 | 52 | from PySide6.QtWidgets import QApplication, QMainWindow, QFileDialog, QFormLayout, QPushButton, QVBoxLayout, QDialog, QLabel, QComboBox, QDialogButtonBox
microscopy_options = ['Brightfield/Phase Contrast', 'Nucleus', 'Budneck', 'Others']
class FileTypeDialog(QDialog):
def __init__(self, parent=None):
super... |
d1ff0af10cd7388feb78b711027eef9b84b4872d33f434ced285dde5b1ac2619 | Python | 2,188 | 61 | from collections.abc import Sequence
from dataclasses import dataclass, field
from typing import Literal
al_cat_loss_names = Literal["CrossEntropyLoss", "BCEWithLogitsLoss"]
al_con_loss_names = Literal[
"MSELoss",
"L1Loss",
"SmoothL1Loss",
"PoissonNLLLoss",
"HuberLoss",
]
@dataclass
class Tabular... |
17666158601ba957ec6bd1b7f05e6fcabf934de6a09fc40f0d90cecef4622d88 | Python | 2,189 | 56 | #!/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=['commit_amico.zip'])
# ToDo: For more ... |
9ebda4b914cd3ff54e5267ff240e6f245d33ed54fdf3ad28e27dc4d0bbb2582e | Python | 2,189 | 64 | from sklearn.metrics import accuracy_score, f1_score, precision_score, recall_score, matthews_corrcoef, \
roc_auc_score, precision_recall_curve, auc
import torch
import torch.nn.functional as func
def null_metrics():
return {
'acc': 0.0,
'f1-score': 0.0,
'precision': 0.0,
... |
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