sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
0336a13fb48ace41287ef0a7ad4a981cdba9815820228b22b21535a2559c56e8 | Python | 4,445 | 78 | import matplotlib.pyplot as plt
from src.ionisation import *
if __name__ == "__main__":
"""
Equation for systematic error removal
E_actual (in eV) = 0.397 + 0.731 * E_vert (in eV) for wB97X-D4
Hydroxyorcein | Calculated energies | Energies after systematic error removal
S1111 | ... |
115e6bddeb379a821a4d88eeab13b5e458d717ef56d6b67d63e82a910f65d469 | Python | 4,445 | 105 | # -*- coding: utf-8 -*-
"""
Created on Wed Jan 18 14:12:39 2023
@author: gligorov
"""
import xgboost as xgb
import numpy as np
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score
from Data_processing import keep_features, generate_all_permutations, flatten_3d_array... |
6cd62cce160feb67d27837bcc3f223e328447fe76fe8d88d19c09d0b6d8e92e6 | Python | 4,445 | 137 | """ Shared functions to load/generate data """
import itertools
import math
import random
import string
import numpy as np
from impyute.dataset.corrupt import Corruptor
from impyute.ops import error
def randu(bound=(0, 10), shape=(5, 5), missingness="mcar", thr=0.2, dtype="int"):
""" Return randomly generated data... |
ecee7715d99ee0b5566260cda764ce27ae30f2da34923e6d877d00189629b911 | Python | 4,445 | 74 | #!/usr/bin/env python
###--------------------------------------------LOAD LIBRARIES
import scanpy as sc
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
import copy
import os, glob
import random
###--------------------------------------------4 layers
print('Reading anndata'... |
b1bf528d41d682acd4205aa05c8663fdd2f24372c0bea0219b533dd893557a41 | Python | 4,446 | 80 | import pytest
import numpy as np
from brainscore_vision import load_dataset, load_stimulus_set
from brainscore_vision.benchmark_helpers.neural_common import filter_reliable_neuroids
TOTAL_NEUROIDS = 2048
RELIABILITY_THRESHOLD = 0.3
EXPECTED_RELIAB_NEUROIDS = {
'monkeyF': {'V1': 332, 'V4': 117, 'IT': 157},
'monk... |
f72772ac9d6ca51164102a1a54991f534ae707e68a8d40429c947564cf77506c | Python | 4,446 | 138 | import jax
import jax.numpy as jnp
import matplotlib.pyplot as plt
import glob
import sys
import os
import re
import json
plt.rcParams["font.sans-serif"] = ["DejaVu Sans"] # Best available
plt.rcParams["font.family"] = "sans-serif"
plt.rcParams.update({
"font.size": 10,
"axes.titlesize": 10,
"axes.l... |
9c088ab37c89183706d01c85c3df6cf457147a1efa857f8fa4e235c62dcfd1b2 | Python | 4,449 | 118 | """
For code used in distributed training.
"""
from typing import Tuple
import torch
import torch.distributed as dist
import os
from torch import Tensor
import torch.multiprocessing as mp
def set_sharing_strategy(new_strategy=None):
"""
https://pytorch.org/docs/stable/multiprocessing.html
https://discu... |
02f2ca13fc653865247ccf08cbba00c734e9f161ea6b9205eebbb15ed86fa089 | Python | 4,450 | 100 | # -*- coding: utf-8 -*-
import argparse
import sys
import numpy as np
import pandas as pd
from loguru import logger
import time
from scipy.special import softmax
sys.path.append('..')
from nerpy.ner_model import NERModel
from nerpy.dataset import load_data
def main():
parser = argparse.ArgumentParser('NER task'... |
0cb72624bbf1d18bd376c2ebe7baf2a17238455b62f38e24e81e488ed7da7ac2 | Python | 4,450 | 149 | """Contains utility functions for the SRC package."""
import os
import logging
from dataclasses import dataclass, field
import pandas as pd
import pysam
@dataclass
class PRSConfig:
"""Common configuration class for PRS scoring."""
bcf: str
col: str = field(default="GT")
build: str = "hg38"
imput... |
b53e02d3ccdc508014d4d3d2bd19923b5b9ff107fbdae3d136f00a0e178ea669 | Python | 4,450 | 127 | """Train surrogate model with Pytorch Lightning"""
import os
import hydra
import lightning as pl
import omegaconf
from dotenv import load_dotenv
from hydra.utils import instantiate
from lightning.pytorch.callbacks import EarlyStopping, ModelCheckpoint, TQDMProgressBar
from omegaconf import DictConfig, OmegaConf, open... |
c4c3ab25342d18a7819278775e054bc243a29935d4ea6c3a8936ed3c8f0b95fe | Python | 4,450 | 141 | from lasagna.tree.node import Node
_ROOT, _DEPTH, _WIDTH = list(range(3)) # Used by classes to navigate the tree
class Tree(object):
""" A simple tree class
"""
def __init__(self):
self.__nodes = {}
@property
def nodes(self):
return self.__nodes
def add_node(self, id... |
cd6d303b5a4bdef39d0c20fcd0d154c048bb308d6383f2812e17f2db4e2b65f3 | Python | 4,451 | 107 | from zigzag.classes.stages import *
import re
def get_hardware_performance_zigzag(
workload,
accelerator,
mapping,
opt="latency",
dump_filename_pattern="outputs/{datetime}.json",
pickle_filename="outputs/list_of_cmes.pickle",
):
# Initialize the logger
import logging as _logging
_... |
de7e8a9a8fdc90aab8d15a359955f68c8c90030d16868f834bced2d3ba1336e6 | Python | 4,451 | 119 | #############################################################################
# Copyright (C) 2020-2026 MEmilio
#
# Authors: Maximilian Betz
#
# 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... |
1a2628d875b8eb2dda6ecb98873423bcb6ec28e798c905950a58e40219274194 | Python | 4,452 | 121 | import numpy as np
from matplotlib import pyplot as plt
from matplotlib.axes import Axes
from neuralib.plot.colormap import insert_colorbar
__all__ = [
'plot_decoding_err_position',
'plot_confusion_scatter',
'plot_confusion_heatmap'
]
def plot_decoding_err_position(mean_err: np.ndarray,
... |
4c31d06e91b81a78e3ff69356d6f2c1a1ac1cea2c4841fed7510c8a6f840c03e | Python | 4,452 | 128 | """Create rasters and firing rate plots."""
import os
import sys
import os
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
import matplotlib as mpl
import pandas as pd
import json
from ast import literal_eval
from spikes.spike_utils import get_condition_spike_times
from spikes.spike_u... |
6057f527e7bac914b3c7ebfc65a3b1c405a4b7f91de3bf15cfc3103c313e9cdf | Python | 4,454 | 109 | """Can the window actually be resized vertically?
On a Mac the window could be made wider and narrower but its height would not
budge. Nothing pinned it: the Results tab's network-viewer control column is
five stacked group boxes, and an unscrolled panel hands its full height to the
window as a *minimum*. That minimum... |
6ca6cc663979cbf8666fffa27a4c6ceef1fe2e92d9affd0e9c5aabf779db068f | Python | 4,454 | 108 | import warnings
import numpy as np
from dipy.core.gradients import gradient_table
from src.wrappers.OsipiBase import OsipiBase
from src.original.fitting.IAR_LundUniversity.ivim_fit_method_modified_topopro import IvimModelTopoPro
class IAR_LU_modified_topopro(OsipiBase):
"""
Bi-exponential fitting algorithm by... |
91cc73975f5e3e81ee4471765100b15104bf00a9051cfbf148354206378164f5 | Python | 4,454 | 112 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Script for fitting a Bingham distribution to each fODF lobe, as described
in [1].
The Bingham fit is saved, with each Bingham distribution described by 7
coefficients (for example, for a maximum number of lobes of 5, the number
of coefficients is 7 x 5 = 35 -- less th... |
17bbc8d1cb5c20ad4c40ff71ebe512439b027483a8eb685faa6f921876c1c61c | Python | 4,456 | 138 | #!/usr/bin/env python3
# This script is included in documentation. Adapt line numbers if touched.
import arbor as A
from arbor import units as U
import pandas as pd
import seaborn as sns
import sys
from pathlib import Path
# (1) Read the morphology from an SWC file.
if len(sys.argv) == 1:
print("No SWC file passe... |
2a6887f61a05bbb035cb99391d7d8a501d1b268398f16e6450140b86fcfe39bf | Python | 4,458 | 143 | import json
import os
import os.path as op
def write_json(fname, data):
"""
Write data to JSON file.
Parameters
----------
fname : str
Full path to the file to write.
data : dict
A dict containing the data to write.
Returns
-------
None
"""
with open(fnam... |
120c029c64cafe4a2882fa0dd2f765856ac7f2eed5769759d73950c4c9be18d6 | Python | 4,459 | 102 |
import json
import numpy as np
from PIL import Image
def update_cellclass(classjson: str, maskmap: str, maskmapdownfactor: int) -> None:
"""
In the loaded json, replace all the cells predicted as tumor cells outside tumor region
into epithelial cells (class 6) and rewritte previous json with new changes... |
8fd20ea8f22cf416ac84652f2933aaa803181d7c962134c9c5dd52d7279beab2 | Python | 4,459 | 130 | from pydantic import BaseModel, Field, model_validator
from typing import Any, Optional, Dict
import torch
import logging
try:
from fairchem.core import FAIRChemCalculator, pretrained_mlip
except ImportError:
logging.warning("fairchem is not installed. .")
FAIRChemCalculator = None
pretrained_mlip = N... |
ffc1fff29950f353f6e942ae834006bfcad6fb6f9b004a59bd528428000051cc | Python | 4,459 | 122 |
import pandas as pd
import numpy as np
import numpy as np
from numpy.linalg import norm
import MDAnalysis as mda
from MDAnalysis.analysis import distances
import sys
def point_in_triangle(x, y, a1, b1, a2, b2, a3, b3):
def area(x1, y1, x2, y2, x3, y3):
return abs(x1*(y2 - y3) + x2*(y3 - y1) + x3*(y1 - y... |
98ae39a06b5e8421946fbf6b0e17a257e1e4e1d21933d13781fbe8307d31b792 | Python | 4,460 | 120 |
import numpy as np
import scipy
import matplotlib
# matplotlib.use('Qt5Agg')
import matplotlib.pyplot as plt
import pathlib
from postprocessing_modules.axonal_delay_kernel import AxonalDelayKernel
from helper_functions.load_cell_distributions import compute_distribution
from helper_functions.cell_type_lib import get_c... |
05b363f6deaa0c532060e6f09ff6e8cf8f13a70068f7dafda39857c1eee8a3b3 | Python | 4,462 | 131 | #!/usr/bin/env python3
"""
Rule-Based Detector Evaluation
Evaluates heuristic artifact detectors on binary test data.
Authors: Evans Nyanney, Parthasarathy D Thirumala, Shyam Visweswaran, Zhaohui Geng
Year: 2025
License: MIT
"""
import os
import json
import logging
from typing import Tuple, Dict, Any
import numpy a... |
e463cc140c0341a849d59b5c61c290c83022f3018238f364e28651553a42b28a | Python | 4,462 | 125 | """Make discrete distance bins for figure"""
import nibabel as nb
import numpy as np
import subprocess
root = '/Users/sebastiandresbach/data/s1Anfunco/Nifti/derivatives'
digits = ['D2', 'D3', 'D4']
for digit in digits:
distFile = f'{root}/sub-07/func/rois/sub-07_{digit}_maxpoint_BOLD_geodistance.nii.gz'
nii ... |
66e5ae8b6f1b95ba5f3a805406eb57fabba39fc75ea9b44bbb788a97c4a59477 | Python | 4,463 | 134 | import h5py
import os
import matplotlib.pyplot as plt
import numpy as np
DIR = os.path.dirname(os.path.realpath(__file__))
HOME_DIR = DIR.rsplit('/', 1)[0]
HOME_DIR = HOME_DIR.rsplit('/', 1)[0]
print('> HOME: ', HOME_DIR)
DATA_DIR = HOME_DIR + '/data/'
print('> DATA: ', DATA_DIR)
# %%
for met in ['jets', 'ss']:
... |
731b56a568313c4ed4ef262e9cd32dd4f2292682749e4be4541261ef6aac59bf | Python | 4,463 | 146 | """
this module provides a PyTorch implementation
for the least square althorithm, such as
the conjugate gradient method.
Author:
Zhengguo Tan <zhengguo.tan@gmail.com>
References:
* https://sigpy.readthedocs.io/en/latest/generated/sigpy.alg.ConjugateGradient.html
* https://docs.scipy.org/doc/scipy/referen... |
c65c57186012dcee1bfbbc8e7e4b123594a9bc42bfc42243f3b1b7be2b7c56f7 | Python | 4,463 | 136 | from tqdm import tqdm
import numpy as np
import pandas as pd
from nest.hotspot.hotspot import _compute_cutoff, compute_hotspots
from nest.utility.utility import get_activity_dataframe
from nest.cci.cci import compute_activity
def interaction_hotspots(
adata,
verbose=False,
interactions=None,
save_act... |
9cbeb256dc563fe860601acb44a8c4bdeae4ee99c4a324db5b388cdd7e275d87 | Python | 4,464 | 115 | import os
import shutil
import csv
import hashlib
import logging
from util.config_vars import config
from util.io import make_dir_if_not_exists
class IdentifyAndMoveDuplicates:
"""
The downloaded data may contain duplicates.
Those duplicates are identified and moved into a dedicated duplicate folder
t... |
553e6bda69dee65f3b684b1db742f72ef1bdb4892751dd0f99bb804231526bc3 | Python | 4,465 | 98 | #!/usr/bin/env python
"""
Material configurations for Rwp Uncertainty Quantification
"""
import os
SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__))
CNN_DIR = os.path.dirname(SCRIPT_DIR)
MATERIALS = {
'CeO2': {
'model_folder': 'model_CeO2_100epochs_digit_zero0p0075_lp0p005_May13_2025',
'mod... |
b72d6e12ecb5618ddee208811b11b229d8a534aa66c8a5b6892a40e4cf42872a | Python | 4,465 | 148 | """bpdb.py - Tools for working with protein structure files
"""
from collections import Counter
from Bio.PDB import MMCIFParser, PDBParser, Selection, NeighborSearch
def pdb_model(structure_file, water=False, ions=False):
"""Return a biopython [1] model entity from a structure file.
Parameters
--------... |
d8e0136cf84296661f54bf1e12a844a270dbc4511e3f82eebff7878fc8262c86 | Python | 4,466 | 113 | import pandas as pd
import os
import sys
import numpy as np
import subprocess
def stiching_denoised_patches(input_path, output_fn = None):
cts_files = sorted([x for x in os.listdir(input_path) if 'Counts.txt' in x])
denoised_fns = sorted([x for x in os.listdir(input_path) if 'denoised' in x])
assert(len(c... |
4680b55826da1552f29a9c26c139d6e4a4aa18dcb7543b80124bc19652dc1595 | Python | 4,467 | 114 | import torch
from torch import Tensor
from typing import List, Tuple, Optional, Union
import torch.nn as nn
from .layer_norm import LayerNorm
from .drop_path import DropPath
import warnings
"""
self.double_conv = nn.Sequential(
nn.Conv2d(in_channels, mid_channels, kernel_size=3, padding=1, bias=Fals... |
6e07c8a913241c9013bb5626d3d9f5f2403cefa6a43053fe6404dacead2e43dd | Python | 4,467 | 122 | # 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... |
1d91e8a75777aeccb9cb30febaf4dff0578ce27fec873b393c879ef2df58a2f0 | Python | 4,468 | 58 | from brainvoice.waveform_utils import write_waveform
import pathlib
import os
import glob
import shutil
import pandas as pd
from tqdm import tqdm
import soundfile as sf
if __name__ == "__main__":
source_root_path = '05-09-23_decoding_single_trial_vs_sil'
destination_root_path = '05-09-23_decoding_single_tria... |
20a6f2c41bc33503fab1916a81eedf80cb3ab3b38d0f63905539883e62728310 | Python | 4,468 | 110 | # # This script is an example of how to use the ModalityCentricPreprocessor class to preprocess a set of MR images. It is only here for quick development and testing purposes. It is not intended to be used in a production environment.
from pathlib import Path
from brainles_preprocessing.modality import CenterModalit... |
7b021354acbfeeb479eb6d9456bdb1ddfaf6d44f65fa3115cefebf9cf7b7823d | Python | 4,468 | 145 | #!/usr/bin/env python
#
# compare.py
#
# copyright F. Nedelec, December 14th 2007, 14.03.2018; 4.8.2020
"""
compare.py
Compare files from two root directories
Usage:
compare.py root1 root2 [opendiff]
"""
from __future__ import print_function
import sys, os, shutil, time, subprocess, tempfile
exe = "diff"
dif... |
7db86cd04d0dd78f3f2e285dd9c9cfa882161629a9f2c8f08364e937091e98df | Python | 4,468 | 98 | from pathlib import Path
import pytest
from pytest import approx
from brainscore_vision import benchmark_registry, load_benchmark
from brainscore_vision.benchmark_helpers import PrecomputedFeatures
from brainscore_vision.benchmark_helpers.test_helper import StandardizedTests, PrecomputedTests, NumberOfTrialsTests, \
... |
e7c4d40d677edc7c61ab4789efa0830bf372bf3619dd0968a3a23bc29263be86 | Python | 4,468 | 122 | import warnings
warnings.filterwarnings("ignore", message="It is not recommended to directly access")
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch_geometric.nn.models import MLP
from dataset import BatchMolGraph
from module.ExplainableCrossAttentionEncoder import ExplainableCrossAttenti... |
ed8c03c5e94aa60a108f00e5ed9073b7fe04e7c4d1f3baa1cec8f4cc37693a49 | Python | 4,472 | 121 | import sys, os, copy
import torch
from monai.config import print_config
from monai.transforms import (
AddChannel, Compose, LoadImage, EnsureChannelFirst,
ScaleIntensity, ToTensor, HistogramNormalize, ResizeWithPadOrCrop
)
from monai.data import NibabelWriter
from utils.netdef import ShuffleUNet
import numpy as... |
03554df4f63b666a31bf83285c686989a87ad1ba98c066e62e83b0715f6b1e89 | Python | 4,473 | 114 | import argparse
import subprocess
import shutil
import os
import time
import multiprocessing
from gen_rosetta_args import gen_rosetta_args
def copyComplete(source, target):
# copy content, stat-info (mode too), timestamps...
shutil.copy2(source, target)
# copy owner and group
st = os.stat(source)
... |
121cf7e57028c9487f150cb7d2f71b78afac83608931d0de54ce92756aa2a5b9 | Python | 4,473 | 97 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Sep 8 13:58:12 2023
@author: rl05
"""
# import sys
import os.path as op
import numpy as np
import pandas as pd
# sys.path.append('/imaging/hauk/rl05/fake_diamond/scripts/preprocessing')
import config
def count_letters(text):
return sum(c.isalph... |
4aac5cedf88b9681042557e49fb40cfa16c56ff02285e1e37304ad3f59a9dcda | Python | 4,474 | 107 | """ AFMmeasurements_changingsettings_oneposition-manysettings.py
This script iterates over a list of measurement settings at every position, so
"go to position 1" --> "take a measurement with each of the settings in order_force-settings.txt" -->
"go to position 2" --> "take a measurement with each of the settings in o... |
b0800e50d8ae3b26d4db8eac3593c9350ed07bad1c67a10fefc51b4f51d4778e | Python | 4,474 | 134 | #!/usr/bin/env python
"""
Filming tests.
"""
import os
import pytestqt
import sys
from PyQt5 import QtCore, QtGui, QtWidgets
import storm_analysis.sa_library.datareader as datareader
import storm_control.hal4000.hal4000 as hal4000
import storm_control.sc_library.hdebug as hdebug
import storm_control.sc_library.param... |
618a6152680dbdde75a72e4f5813a19d70d79a45399f82358ff43e71cae332b1 | Python | 4,475 | 82 | from brainvoice.data.commonvoice_spectrogram_dataset import CommonVoiceSpectrogramDataset
from brainvoice.data.stratified_batch_sampler import StratifiedBatchSampler
import torch
import pandas as pd
import os
class CommonVoiceSpectrogramStream(object):
def __init__(self, bv_dataset_path, cv_dataset_path, catego... |
81cf5fd2d649caff1a99fb95a53f53cbf865b714edb74e3947c1021b7ed77959 | Python | 4,476 | 156 | import os
import pytest
import numpy as np
import pandas as pd
from collections import OrderedDict
from impedancefitter import Fitter, get_equivalent_circuit_model
R = 1000.
C = 1e-6
model = "parallel(R, C)"
Rc = 5.3e-6
dm = 7e-9
ecp = 60
kcp = 0.5
p = 0.2
km = 5e-11
em = 7.9
p = 0.1
kmed = 0.1
emed = 80
c0 = 1
k =... |
869a7bd00d26030ce473ea1b1889869e1c464fbd632ad2842ac2a7a1db99f16b | Python | 4,477 | 136 | """
Collect statistical maps of all participants in a folder
"""
import glob
import shutil
ROOT = '/Users/sebastiandresbach/data/s1Anfunco/Nifti'
subs = ['sub-05', 'sub-06', 'sub-07', 'sub-09', 'sub-10', 'sub-14', 'sub-15', 'sub-16', 'sub-17', 'sub-18']
contrasts = {1: 'D2vsAll',
2: 'D3vsAll',
... |
2ad170a5000cc1e6a028e6c67773133e252c9f59986588cf22075d98c84a4649 | Python | 4,478 | 106 | import os
from importlib import import_module
from pathlib import Path
cell_graph_config = {
"cell_f_list": [
'area',
'r_equiv',
'r_maj',
'r_min',
'angel',
'ecc',
'maj_x',
'maj_y',
'min_x',
'min_y',
'x',
'y',
],
... |
431380d203000590ec740815c77f08507f19596524e25db7e732b503ba4436fd | Python | 4,478 | 154 | """Resolve endpoint configuration without constructing model clients."""
from __future__ import annotations
from collections.abc import Mapping
from typing import Any
from chemgraph.models.endpoints import EndpointSpec, ModelRequest
from chemgraph.models.endpoints import vllm as vllm_ep
from chemgraph.models.endpoin... |
289ed998f497c3efe97e412402cb059d7a5319f08ebb16733296403109ec0cbf | Python | 4,479 | 115 | import pandas as pd
import matplotlib.pylab as plt
import numpy as np
def load_bhv(path='rtnet/behavioral data.csv', reject=True):
bhv_path = 'rtnet/behavioral data.csv'
bhv = pd.read_csv(bhv_path)
if reject:
# Participant rejection
part_idxs = bhv.subject.unique()
n_parts = len(pa... |
4b4c6f1faebd64ee2f1d22f2113e64c5e27c2b7bba856fbb161a53e1df95e81a | Python | 4,479 | 145 | from __future__ import absolute_import
from torch import nn
from torch.nn import functional as F
from torch.nn import init
import torchvision
import torch
from .pooling import build_pooling_layer
'''
this is the original code, I just didn't modify RWM
'''
__all__ = ['ResNet', 'resnet18', 'resnet34', 'resnet50', 're... |
0a6547b58a9c9061297a24b0c5034543ddde45db3e1ccbd18fd96f1804a33b3c | Python | 4,480 | 117 | #Lucas Sancéré -
import os
import yaml
from attrdictionary import AttrDict as attributedict
from tqdm import tqdm
from histo_miner import hovernet_utils, segmenter_utils
from histo_miner.utils import cellclass_process
script_dir = os.path.dirname(os.path.abspath(__file__))
########################################... |
20c8fa2b6ea1450a12ca4f754c8344214b551e60d0efd72ff9d33520462b8bda | Python | 4,480 | 118 | import os
import numpy as np
import nibabel as nib
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
import imageio
# ========= User settings =========
flair_path = r"F:\BIDS\demo_BIDS\derivatives\xfm\sub-AFib0241\ses-baseline\sub-AFib0241_ses-baseline_acq-highres_space-T1w_desc-brain_FLAIR.nii... |
5b370ad44c95673ba10907f66318dd21e152b95ccf715264b82297d63a6bc4f2 | Python | 4,480 | 113 | import torch
import torch.nn as nn
import models.snn_type as snn_type
from conf import global_settings as conf_set
from models import snn_soma
#import torch.cuda.nvtx as nvtx
class basic_block(nn.Module):
expansion = 1
def __init__(self, in_channels, out_channels, stride=1, has_bn=False):
super(basic_... |
770bf84512aeb9c779a6434069cfc13d9b44de33d801001495ae2a6d083202b2 | Python | 4,480 | 121 | # 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... |
8c1c8449a4498aee6a4f2ac445efad48730a67ac9447dd07d716da61ae14c760 | Python | 4,480 | 115 | import argparse
import joblib
from collections import defaultdict
import numpy as np
import pandas as pd
from sklearn.ensemble import RandomForestClassifier
from xgboost_ensemble_classifier import XGBoostEnsembleClassifier
from xgboost import XGBClassifier
from sklearn.neural_network import MLPClassifier
from sklearn... |
5e2d12fb81d8c8e9759550e2a4dfc2c9817ddeebaff64634d075847629d1703f | Python | 4,481 | 124 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
# NOTE: importing in the utils.py header leads to circular importing
import textwrap
from datetime import datetime
from django.db.models import QuerySet
from django.http import HttpResponseGone
from django.http.response import HttpResponse
from drf... |
66d39beacb3ccc41293e36275397d964a449fee9ab9e4de58967476e9bc90c19 | Python | 4,481 | 146 | from pathlib import Path
from typing import TYPE_CHECKING
import numpy as np
from tests.setup_tests.setup_modelling_test_data.setup_targets_test_data import (
get_current_test_label_values,
get_test_label_file_fieldnames,
set_up_label_file_writing,
set_up_label_line_dict,
)
from tests.setup_tests.setu... |
db9a3edf542005836ba7619cb104af4c6fabb58664367e879ae3bffa343494a7 | Python | 4,481 | 168 | # NeuN,S100,Olig2,Iba1,RECA1,Cleaved Caspase-3,Tyrosine Hydroxylase,Blood Brain Barrier,GFP,
# PDGFR beta,Parvalbumin,Choline Acetyltransferase,GFAP,Smooth Muscle Actin,Glutaminase,Doublecortin,
# Sox2,PCNA,Vimentin,GAD67,Tbr1,Eomes,Calretinin,Nestin,Aquaporin-4,Calbindin,
cell_type_panel = {
'NeuN': 'S1_R2C4.tif',... |
aa835619acfa3af297b14d7955f310f4f82de9efbe02a9fe6c14e898d1620c53 | Python | 4,482 | 130 | #!/usr/bin/env python
import numpy as np
import pandas as pd
import click as ck
from sklearn.metrics import classification_report
from sklearn.metrics.pairwise import cosine_similarity
import sys
from collections import deque
import time
import logging
from sklearn.metrics import roc_curve, auc, matthews_corrcoef
from... |
61f5970d46db090d209418323994fdd7ed5bf1e894a70844799e7f8c8541c8a1 | Python | 4,483 | 117 | """Causal, leakage-free preprocessing.
Two normalisation stages, in this order:
1. **Per-session causal baseline** -- each session's features are expressed
relative to the median/IQR of that session's own first `baseline_min`
minutes. Absolute EDA level and eyelid geometry are strongly
subject-specific, so w... |
cac95e9f0c2dbb0a4ebfce1e566cef41f6c02ec4c03af2310291ecbf3b876ac3 | Python | 4,483 | 120 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
from __future__ import annotations
from django.conf import settings
from django.contrib import admin
from django.db import models
from django.db.models import functions as db_functions
from django.utils import timezone
from rest_framework_api_key.mo... |
4a3fd178459b390db6a4b38aea93fa44c4df1bc3f77dd5b92d0a7f3696e80bf2 | Python | 4,484 | 128 | import os
import sys
import logging
from datetime import datetime
from errno import EEXIST
LOGDIR = 'logs'
PREDDIR = 'predictions'
class FileExistsError(Exception):
pass
def main_name():
"""Return the name of the main file without the extension."""
import __main__ as main
return os.path.splitext(mai... |
ad3d34b17d2e80f99081a080cbe924ef7198850f050cb99f76621299c8ed1958 | Python | 4,486 | 107 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
"""Create a ground truth job in an existing task from an exact frame list you choose.
Steps:
1. Retrieve the task and resolve the requested frames: indexes (--frame) or
file names (--frame-name, matched against the task's frame list).
2. Re... |
f3c90110a1967f42cc3505e3b83178c55cda680405080de19af367ed055a21eb | Python | 4,486 | 105 | # modules.py
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Function
def initialize_weights(module):
for m in module.modules():
if not hasattr(m, 'weight') or not m.weight.requires_grad:
continue
if isinstance(m, nn.Linear):
nn.... |
55ce3fcc365fbb437a8c182b45bb41fbda158920527a12c9197ac643eb76ea3b | Python | 4,489 | 229 | # -*- coding: utf-8 -*-
"""
Created on Fri Mar 31 19:56:02 2023
@author: axthi
"""
import os
my_path = os.path.dirname(os.path.realpath(__file__))
class project_template:
def __init__(self):
self.proj_nr = 0
self.exp_cond = '' # 'target' or 'control'
self.roi = ''
self.... |
6c054e17c4517ed6cb1e5a09a34d5837acd561a19f34bc75197d8de67edc69c6 | Python | 4,489 | 118 | #! /usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Compute a density map of seeds saved in .trk file.
* They are saved as a data_per_streamline 'seeds' when using our tractography
scripts with option --save_seeds.
- scil_tracking_local
- scil_tracking_local_dev
- scil_tracking_pft
If you use your own tractograms, yo... |
dfc590d05846aef0a49e5b13cdad9d8f1662d191ff63bcd5020d6cc1e0c44d9f | Python | 4,489 | 114 | """
Loads data from imagej/fiji ROIs or ROIs sets (zip files)
Requires ijroi from: https://github.com/tdsmith/ijroi/blob/master/ijroi/ijroi.py
`pip install ijroi` to get it.
"""
import os
try:
import ijroi
except ImportError:
print('fiji_roi_reader_plugin requires the ijroi module from:\n'
' htt... |
968c9814fd4c242eefaa486e7738a4669f970c68bd189a046277e279040ca4ee | Python | 4,491 | 174 | """LangChain ``@tool`` wrappers over :mod:`chemgraph.tools.ase_core`.
Every public function here is a thin decorator that delegates to the
corresponding plain-Python implementation in ``ase_core.py``.
"""
from __future__ import annotations
import os
from typing import Any, Dict
from langchain_core.tools import tool... |
ab72e49c770b8fafa23738bb5bb64506bdfe2d3b88274c1319647dcbd492c79c | Python | 4,491 | 119 | from keras.models import Model
import numpy as np
import innvestigate.utils as iutils
import os
from keras.preprocessing.image import img_to_array, load_img
import tensorflow as tf
import PIL.Image
import matplotlib.pyplot as plt
import cv2
from interpreters import SGLRP, CLRP, LRP, GBP
from utils import *
def visua... |
fdcbf8e175b2217dfd3b8907a02d7033133c5d21c567262cd0f2d9c2b1cd8f52 | Python | 4,491 | 161 | import numpy as np
import time
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.autograd as autograd
from UBSIM.models import UNet
def reshape_psf(num_frames, psf):
"""
Reshapes a PSF from size [N,N] to shape [1,num_frames-1,N,N]
Parameters:
num_frames: the nu... |
2ca2cabe88f33685cdc83d6be9893458b332ea6b074f03bdd3489311a57f7a63 | Python | 4,492 | 97 | """
Script to run busyring example
"""
import argparse
import numpy as np
import neuron
from neuron import h
import parameters
from metering import RuntimeMetering
from ring_network import RingNetwork
# Parse commandline arguments
parser = argparse.ArgumentParser()
# Model and simulation parameters
parser.add_argumen... |
4697e5201816d08a7e50c58adb0fb020c17b62d9052d1eccd59bdc80c84c881a | Python | 4,492 | 142 | import sys
import yaml
import os
import numpy as np
import h5py
import matplotlib.pyplot as plt
import matplotlib as mpl
pathpath,myrun = sys.argv[1:]
#pathpath = 'PATHS/filepaths_carlen.yml'
#myrun = 'runC00dMP_M'
nclustvec = np.arange(2,21)
with open(pathpath) as yfile: pathdict = yaml.safe_load(yfile)
rundict_... |
9c827e3f357c505b00f395bba66af3a81adec24ce4d0a7a087af78f001a9b788 | Python | 4,492 | 83 | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file '/media/lg/disk2/PycharmProjects/ISAT_with_segment_anything/ISAT/ui/visual_prompt_dock.ui'
#
# Created by: PyQt5 UI code generator 5.15.10
#
# WARNING: Any manual changes made to this file will be lost when pyuic5 is
# run again. Do not edit... |
6ac12dcf93fb4a015ecb3c01f243c17307587f4c770239f6b6ffc23a856220e8 | Python | 4,494 | 130 | import tempfile
from pathlib import Path
from typing import Optional
import click
import numpy as np
import pymeshfix
import pyvista as pv
import SVMTK as svmtk
import tqdm
from loguru import logger
from brainmeshing.utils import (
fs_surf_to_stl,
pyvista2svmtk,
repair_triangulation,
svmtk2pyvista,
)
... |
1e786446bfeb9c6d3e55e6bf1e64a7c204d35ae541d649d1124712a39beee53a | Python | 4,495 | 125 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Visualize seeds as 3D points, with heatmaps corresponding to seed density
Example usages:
>>> scil_viz_tractogram_seeds_3d seeds.nii.gz --tractogram tractogram.trk
"""
import argparse
import logging
import nibabel as nib
import numpy as np
from fury import window, ... |
ddfe3567ea0e017545c79a57a1701d2f3d0f5325cb649fecc2bca76259b80f10 | Python | 4,495 | 131 | """Contains HLA interaction PRS functions"""
import pandas as pd
from ..core.score_bcf import score_bcf
from .grouped_scoring import score_grouped
def generate_dosage_table(dq, config, variant_log_path=None, prs_name=None):
"""Generate and rename the dosage table."""
# Select the correct position column base... |
110941c88a6c5769a95c09423b5f3e5b9755d10ab09eb9fa5073657a9dc8671c | Python | 4,496 | 113 | #---------
# Figure 1-source code 1
# Related to Figure 1d
# sub*_mri_record.txt files are also available from the Science Data Bank at https://doi.org/10.57760/sciencedb.18351
# csv_plot_pos.csv file is also accessible at https://github.com/ZHANGneuro/Greeble_PyGame_fMRI_task/blob/main/csv_plot_pos.csv
# Bo Zhang
# Fe... |
6b5d2782c2e8b41a37bff8e866e752159e66c9f76abbcf9fab206f08ce74e5f5 | Python | 4,497 | 117 | #!/usr/bin/env python
"""
HAL interface to Crystal Technologies AOTFs.
Hazen 04/17
"""
from PyQt5 import QtCore
import storm_control.hal4000.halLib.halMessage as halMessage
import storm_control.sc_hardware.baseClasses.amplitudeModule as amplitudeModule
import storm_control.sc_hardware.crystalTechnologies.AOTF as AOT... |
cf7b56addf3eb5a05a2a0fe6ea33953c265ec690db10bd8bf962f5aaaea94a42 | Python | 4,497 | 62 | from .data_augmentation import augmentation
from tensorflow.data import TFRecordDataset, AUTOTUNE, Dataset
from tensorflow.io import FixedLenFeature, parse_single_example
from .constants import IMAGE_SHAPE
def datasets_from_tfrecords(records_ref, records_src, buf_size_ref, buf_sizes_src, batch_size=1, compression_type... |
b6147461422f4fc1b1402b2e2aa0d09e2e989958a878889eb4597145f4fd7d8b | Python | 4,498 | 133 | #!/usr/bin/env python
"""
Interface to Logitech dual action joystick.
Hazen 9/12
"""
import pywinusb.hid as hid
class DualAction(object):
"""
This class encapsulates the interface to a Logitech dual action
joystick. It remains in the project for reference purposes
but it would not work ... |
3bb8174954bca5cb560ad6646043b44c3b17436e5830349207919fe8e0ef38e9 | Python | 4,499 | 131 | import pandas as pd
import numpy as np
import re
import os
def celegans_data():
ce_meta = prep_ce_meta()
# lin_data = prep_lin_data()
edge_df = prep_edge_df()
cook_meta = prep_cook_meta()
ce_meta = ce_meta.reset_index().join(cook_meta.add_prefix('Cook '), on='Neuron').set_index('Neuron')
ce_met... |
ca882f858619a6a1033d563f1090b6f47425f4d7494a90043e576a782f7f3593 | Python | 4,499 | 148 | # -*- coding: utf-8 -*-
# @Author : LG
# from https://blog.51cto.com/u_15872074/5841477
from PyQt5.QtCore import QRectF, Qt, QTimer, pyqtSignal
from PyQt5.QtGui import QColor, QFont, QPainter, QPainterPath, QPen
from PyQt5.QtWidgets import QWidget
class SwitchBtn(QWidget):
# 信号
checkedChanged = pyqtSignal(b... |
a0f4b50240263e6e40abcb12188f9ef8e91e5ce9d4e57e7c43ce9e6a61e2e200 | Python | 4,500 | 141 | import typing
from typing import List, Optional, Tuple, Union
import torch
from torch import Tensor
import torch_geometric.typing
from torch_geometric import EdgeIndex
from torch_geometric.edge_index import SortOrder
from torch_geometric.typing import OptTensor
from torch_geometric.utils import index_sort, lexsort
fr... |
a634e20d238617e78adaaf4859daa55189febcc16db2a5f4c529e2d645e94d73 | Python | 4,500 | 104 | import glob
import os
import numpy as np
import pytorch_lightning as pl
from monai.apps import download_url, extractall
from monai.transforms import AddChannel, Compose, EnsureType, LoadImage, RandFlip, ScaleIntensity
from sklearn import preprocessing
from torch.utils.data import DataLoader, Dataset
from {{cookiecutte... |
ba905e19e23ea68d38ec2ecc2a349f37da4ae958e6dfb8662ae346490298ccf4 | Python | 4,500 | 114 | from nipype.interfaces.base import BaseInterface, BaseInterfaceInputSpec, TraitedSpec, File, traits
import os
import csv
import numpy as np
import nibabel as nib
from nibabel.processing import resample_from_to
from cvdproc.config.paths import get_package_path
L_SCR = get_package_path("pipelines", "external", "alps",... |
4a2f78122ee7514392d11441eb884c4d6c1544ce15b408bd17df6d451b066274 | Python | 4,501 | 142 | import os
from pathlib import Path
import click
import numpy as np
import pandas as pd
import simple_mri as sm
from gmri2fem import segment_tools as segtools
from gmri2fem.masking import create_csf_mask
from gmri2fem.segmentation_refinement import (
extrapolate_segmentation_to_mask,
resample_segmentation,
)
... |
227fd01d32b2fdc81f62523caac38e479d8c31b73034d11852fcbb1e01a733bb | Python | 4,502 | 119 | import os
import time as tm
import pandas as pd
import warnings
warnings.filterwarnings("ignore")
import tensorflow as tf
tf.logging.set_verbosity(0)
import Cell_BLAST as cb
import numpy as np
from numpy import genfromtxt as gft
import rpy2.robjects as robjects
def run_Cell_BLAST(DataPath, LabelsPath... |
715bbc5b112f99dfee9c1e9f09321ff865dcc6228dc34aa3605b7dc22853689f | Python | 4,502 | 137 | import unittest
from toolkit.models import GINModel
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
self.hidden_dim... |
333e81a1d72ff6062968c1d4ba6def6b2ba40ebbf7c802d9dfb8d78d05283f24 | Python | 4,503 | 165 | from dataclasses import dataclass
from typing import TYPE_CHECKING, Any, ClassVar, Literal, Protocol, Union
from eir.models.input.array.models_cnn import CNNModel, CNNModelConfig
from eir.models.input.array.models_identity import IdentityModel, IdentityModelConfig
from eir.models.input.array.models_linear import Linea... |
b4ac3a2e36a111d79dd653eda8a04b1e848076d4179fb4788a56a6348a6e3328 | Python | 4,506 | 121 | """
model of deep speckle. including the follow parts:
1. feature extractor
2. flow estimator
3. intensity estimator
4. regularizer for subpixel
5. refiner for flow and intensity
"""
from sys import argv
import torch
from module import FeatureExtractor, costvol_layer, Warping_layer, FlowEstima... |
60d3661c443f0489a4793f0fba749c5976b5d46bd645db732800e44079ed9fdd | Python | 4,507 | 142 | from pathlib import Path
from types import SimpleNamespace
import numpy as np
import pytest
import tifffile
from napari_dmc_brainmap.stitching import tiff_output
@pytest.fixture
def scratch_root(monkeypatch, tmp_path):
root = tmp_path / "app-cache" / "stitching" / "scratch"
monkeypatch.setattr(tiff_output, ... |
bd6837646185af91fa449c2638440fbe2c2a62ebf172254f139f054bfb71fa4d | Python | 4,509 | 142 | import logging
from pathlib import Path
import pytest
from brainways.utils.cell_detection_importer.qupath_cell_detection_importer import (
QupathCellDetectionsImporter,
)
@pytest.fixture
def importer():
return QupathCellDetectionsImporter(
threshold_1=0,
threshold_2=0,
threshold_3=0,... |
1d0b9c44aaf540b42413f0b2abddddd445a0502941cf1c9efa2ed57f2e551616 | Python | 4,510 | 126 | # -*- coding: utf-8 -*-
from dipy.io.utils import is_header_compatible
import logging
import nibabel as nib
import numpy as np
import os
from scilpy.utils import is_float
def load_img(arg):
"""
Function to create the variable for scil_volume_math main function.
It can be a float or an image and if image... |
aafcd188d7f91c6b30b14e643049fc1abeb5483bf558f2eea588f2ce85818126 | Python | 4,510 | 96 | import numpy as np
from brainscore_core.supported_data_standards.brainio.assemblies import BehavioralAssembly
from brainscore_core.supported_data_standards.brainio.packaging import package_data_assembly
import pandas as pd
'''
** NOTE: This benchmark (edge) has a very different stimulus sets/assemblies then others in... |
ba18bb363bc165b08a6466e879f6bbda77d9782a241293be8921e6afae6aa2d3 | Python | 4,511 | 106 | # -*- coding: utf-8 -*-
"""
Created on Wed Dec 4 14:19:39 2019
@author: Yoshi
"""
import numpy as np
def cell_excitatory_flagger(cell_number,correlation_coefficients,areas_under_curves,data,key,frequencies,intensities,threshold):
# Default flags
best_frequency,characteristic_frequency = "N/A","N/A"
... |
0efd2c581f6502408b7cf177bb1007ea69281e8be8d462c548838c77f86c2af3 | Python | 4,512 | 82 | #! /usr/bin/env python
"""Run pycurv on a vtp surface file
Usage: curvarture.py <vtp_file>"""
__author__ = "Benjamin Barad"
__email__ = "benjamin.barad@gmail.com"
__license__ = "GPLv3"
import os
import time
import sys
import click
from .curvature_calculation import new_workflow, extract_curvatures_after_new_workflo... |
88f423134d2d019e02d91e4054a552ac91d656f4d2b7734a1939de410d36c0db | Python | 4,514 | 89 | import csv
import os
from os.path import join as ospj
from numpy import savetxt
import pandas as pd
import re
import sys
import json
import shutil
"""
This script collates the pyAFQ tract profiles output across subjects in preparation for visualization and fitting GAMs.
Each pyAFQ tract profiles csv should be a 1D arr... |
c3adb3cb4f401de9e05b5487ca38f8733bfef9f857c508cdc42422b642e5e52a | Python | 4,514 | 95 | from typing import Callable
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
from dgl.nn.pytorch import SumPooling, WeightAndSum, AvgPooling, MaxPooling
from layers.pooling import AttentionPooling, AttentiveFPPooling, WeightAndMean, WeightAndMeanV2, \
WeightedSumInte... |
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