sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
383f00ca13affadabb18824f407d11cee9d0838ebf9c3079eb3b4361db20d5c7 | Python | 4,951 | 145 | # Copyright 2024 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, ... |
5fed56f071fab72c26b732c5341fc53add457fb95f0e49c8417bff431a6feb27 | Python | 4,952 | 117 | #!/usr/bin/env python3
# tools/export_optuna_trials.py
import json
from pathlib import Path
import optuna
import pandas as pd
def main():
# 1. 结果目录
results_dir = Path("results")
results_dir.mkdir(exist_ok=True)
# 2. 加载回归模型的 Optuna Study
study = optuna.load_study(
study_name="opt_reg",
... |
b18a5fb985b0c31cef38eded2b34d5af41920abe413494373ba215f1a38d2571 | Python | 4,952 | 114 | import nibabel as nb
import numpy as np
import subprocess
import os
import glob
from scipy.ndimage import morphology
root = '/media/sebastian/Data/S1ANFUNCO/raw_data/S1ANFUNCO_BIDS'
subs = ['sub-05']
for sub in subs:
# first, we have to inflate our ROIs
# Load
nii = nb.load(f'/home/sebastian/Desktop/pat... |
e1ec10c4629ed372e51bef96f74b83db3bd90ec55a2fdc7bf1351de1e6cfeac9 | Python | 4,952 | 125 |
import matplotlib
from numpy import loadtxt
from fig import module_utility
import scipy
import random
import numpy as np
import matplotlib.pyplot as plt
from pathlib import Path
sub_group = list(range(1, 29))
sub_group.extend([30, 32,33,34,35])
# exp data
num_subject = len(sub_group)
angle_colume = 19 # col20 subj1... |
e4882ebee6937743aaafa0728984333faa3f070704cc31a399a69de59ee404fc | Python | 4,952 | 154 | #############################################################################
### Recursively moves through directories and extracts parameters and the ###
### mean firing rates of neuronal subpopulations ###
#############################################################################
### Cop... |
62249eb1d94b0f293c3227aaad2d5651222d7b637ed6f011fbb6b61fa41d204a | Python | 4,954 | 116 | """
Adapted from the NSuite benchmarking framework (https://github.com/arbor-sim/nsuite.git).
"""
from neuron import h
import cell
import numpy as np
class RingNetwork(object):
def __init__(self, params, pc):
# Parallelization parameters
self.rank_id = int(pc.id()) # host process/rank ID... |
fa9bfae8a764aafe826f8e51c99c1533f00495837ee57609ce7d150625921ad4 | Python | 4,954 | 152 | """Test pipeline Step 3 — functional connectivity (STTC) parity with MATLAB.
Run from the repo root::
uv run python python/test_pipeline_step3.py
Two things are validated, since MATLAB's own pipeline only ever persists the
*stochastically thresholded* adjacency matrix (never bit-reproducible — see
``probabilisti... |
fbf2ecfdf8af94ab5d89871724316b91aca0b795f49481d8e4bb4b1721019e2d | Python | 4,954 | 142 | import numpy as np
import pandas as pd
import json
import os
import networkx as nx
import pickle as pkl
from textblob import TextBlob
from collections import Counter
import torch
from sklearn.manifold import TSNE
import matplotlib.pyplot as plt
from sklearn.cluster import KMeans
import matplotlib.colors as col
from mat... |
00b78274121c5f82acc87d8633e5e696d37465d79e3d50957cb0802aec657dab | Python | 4,955 | 142 | # 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... |
6a06b21b67eb7d830fd3223f52188f4e18f96752981d37d4393d041c0d9a9576 | Python | 4,955 | 167 | """Finetune an SFCN model from a JSON configuration."""
import argparse
import json
import logging
import os
from typing import Any
import pandas as pd
import tensorflow as tf
from pyment.configurations import (
CategoricalTargetConfiguration,
FinetuningConfiguration,
compile_target_encoder,
)
from pymen... |
fa2140fafbce4e593233329ddfff33d741bd67cea54699bb1693c12ba34649e6 | Python | 4,957 | 117 | # This file is part of connectome-manipulator.
#
# SPDX-License-Identifier: Apache-2.0
# Copyright (c) 2024 Blue Brain Project/EPFL
"""Module to facilitate easier job management"""
from contextlib import contextmanager
from pathlib import Path
from .. import log, utils, profiler
class JobTracker:
"""Class to tr... |
31e279489abeaf687e2ea0eedb4a38e50cc5b4491d619a061ef500f950007f45 | Python | 4,958 | 125 | # Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved
import math
from typing import Optional
import torch
from torch import nn
class PositionEmbeddingSine(nn.Module):
"""
This is a more standard version of the position embedding, very similar to the one
used by the Attention is all y... |
3be9d2a2a0305c2cd77dc887ea8bbff80b55dc436d6517555ffb73de43d79a4d | Python | 4,958 | 123 | #############################################################################
### Recursively moves through directories and extracts parameters and the ###
### mean weights across neuronal subpopulations ###
#############################################################################
### Cop... |
66973927f729ab7a765d8bc4f37ba6e67e221efb85742b292c64a886bc283e1f | Python | 4,958 | 101 | import pytest
pytest.importorskip("fireants_fused_ops")
import torch
from time import time
from torch import nn
from torch.nn import functional as F
from fireants.interpolator.fused_grid_sample import fused_warp_composer_3d
from fireants.interpolator.grid_sample import torch_warp_composer_3d
# set seeds
seed = 4531
to... |
46a07eb2ab66abcbc75c3f0b9d0ef9f59bb884438b1fb17d4a713a0cac3934b1 | Python | 4,960 | 146 | #%% imports
from pathlib import Path
from benedict import benedict
import re
import time
import os
from deep_events.database.folder_benedict import get_dict, save_dict, set_dict_entry, handle_folder_dict
from typing import Union
from deep_events.database.convenience import glob_zarr
#%% setup
MAIN_PATH = benedict(os... |
4fbbf2fd466fdf9e7a8143a9ec91c46261d96e4f764445f90fd84e1e8b5f361c | Python | 4,960 | 155 | # Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved
import argparse
import json
import os
from collections import defaultdict
from iopath.common.file_io import g_pathmgr
from sam3.eval.saco_veval_evaluators import (
VideoCGF1Evaluator,
VideoPhraseApEvaluator,
VideoPhraseHotaEvaluator,
... |
9089d55c3bcf424a8fa9c724286a3b239724630ac1ddf073d6983b9c1ebf3d58 | Python | 4,960 | 145 | from qtpy.QtWidgets import (
QApplication,
QGroupBox,
QHBoxLayout, QVBoxLayout,
QLabel, QLineEdit,
QPushButton, QSpinBox,
QWidget
)
from qtpy.QtCore import QThread, Signal
import napari
from typing import TYPE_CHECKING
if TYPE_CHECKING:
import napari
from ._input_data_widget import InputD... |
217551254fd85cc6725c0144c4e1e4ae67450fc3cf7fc9ebf09870de24cf08be | Python | 4,961 | 139 | from __future__ import annotations
import dataclasses
from typing import Literal
from unittest.mock import patch
import numpy as np
import pytest
from PySide6 import QtCore
from PySide6 import QtGui
from PySide6.QtWidgets import QApplication
from labelme._shape import Shape
from labelme._widgets import _shape_render... |
f84bd32f27d11e503a0cfc6a6bc443a8b140a33556ece2e979ce8fd1172bad6a | Python | 4,961 | 136 | 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
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import cv2
from interpreters import SGLRP, CLRP,... |
56b07197718c6635cb2413249340595993714046c8989145fdfbf5efac3a792f | Python | 4,963 | 181 | from dataclasses import dataclass
from typing import TYPE_CHECKING, Any, ClassVar, Literal, Protocol, Union
import numpy as np
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... |
b9bda4db119b89df42b341eb1498b8cf2651c558ff11654b412278fd0b65f2b1 | Python | 4,963 | 131 | # Copyright 2024 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, ... |
fc6737e5e85175023014708dc8178e10a507dcb22480c2a996cd4223bba48947 | Python | 4,963 | 130 | import json
import numpy as np
import pandas as pd
def load_data_from_keys(json_file, key):
"""
Load data from a nested json file. Json file is opened and iteratively searched for specified key in data.
A dictionary is returned containing all matching entries.
Args:
json_file (str): path to jso... |
8d24c9abed731994f5cd15afe41cb206e038950763fc415ca226dd2e3450683a | Python | 4,964 | 117 | """ Random Erasing (Cutout)
Originally inspired by impl at https://github.com/zhunzhong07/Random-Erasing, Apache 2.0
Copyright Zhun Zhong & Liang Zheng
Hacked together by / Copyright 2019, Ross Wightman
"""
import random
import math
import torch
def _get_pixels(per_pixel, rand_color, patch_size, dtype=torch.float3... |
361f62bcc1d74d884515404d6e8695e60ab18af10764cb6d6b3c6d3792cd0d3e | Python | 4,966 | 166 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
from __future__ import annotations
import io
import mimetypes
from collections.abc import Sequence
from pathlib import Path
from typing import TYPE_CHECKING
from PIL import Image
from cvat_sdk.api_client import apis, models
from cvat_sdk.core.help... |
2f2bc83b996844b9b1f5a5ea898b39afb320207e84f26915f7ae680f00269bf3 | Python | 4,969 | 186 | """
Penn Action loader: MATLAB label files (.mat) -> normalized COCO-17 clips.
Directory layout expected:
Penn_Action/
├── frames/
│ ├── 0001/000001.jpg ...
│ └── ...
└── labels/
├── 0001.mat
└── ...
Each label file contains:
x, y : (T, 13) keypoint coordinates
vi... |
7182d9ca192346a933ab1b25fa3dd71ef2adb3ecc3256e08b19ae25d84227b03 | Python | 4,971 | 144 | ###############################################################################
#################### Boilerplate ########################
###############################################################################
import pandas as pd
import matplotlib.pyplot as plt
import os
import matplotlib... |
a1e61abc0f1cafe2818a3df0abc2569952544ede7b03f3104e8d92cc80a72810 | Python | 4,971 | 164 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Tests for select_optimal_pcs.
"""
import numpy as np
import pytest
from pcafeat.pca_feature_select import select_optimal_pcs
def test_select_optimal_pcs_basic():
"""Select PCs with high target scores and low noise scores."""
target_pcs_lists = [
[(0,... |
e005b96ad4fc95fe6a3545622deaea6a78308453614c3bffa7b9ff40d12256aa | Python | 4,971 | 140 | from __future__ import annotations
import pytest
from PySide6 import QtCore
from PySide6 import QtGui
from PySide6 import QtWidgets
from pytestqt.qtbot import QtBot
from labelme._widgets._label_dialog import LabelDialog
@pytest.mark.parametrize(
"modifier",
[
QtCore.Qt.KeyboardModifier.NoModifier,
... |
e17d660fc79490ffd8ce461a780928f5942d806e3401fc9db09284ac25fe7799 | Python | 4,971 | 154 | from torch import nn, cat as tcat, tensor, save as tsave, load as tload, no_grad, zeros
from torch import normal, rand, exp, log, randn, arange
from torch import float32 as tfloat, ones_like
from numpy import sqrt, linspace, meshgrid, concatenate, newaxis, polyfit, polyval
from matplotlib.colors import TwoSlopeNorm
imp... |
bcd23d4242789f83419a849f7218032e1b3596c982ba86c800209d3095706b06 | Python | 4,972 | 147 | import pandas as pd
from sys import argv
import pickle as pk
import os
import annotate as ann
import optimize_FLAMES as optf
def add_into_single_df(list_of_dfs):
df = pd.concat(list_of_dfs)
df = df.reset_index(drop=True)
df["locus"] = pd.factorize(df["filename"])[0]
return df
def create_XY_train(df, f... |
c082c30e1a88db5ad4f3d16a414da00398fd1b6f74749f1f8bcac2a0bea851e3 | Python | 4,972 | 135 | import numpy as np
from argclz import argument, AbstractParser, int_tuple_type, union_type
from neuralib.persistence import persistence
from neuralib.persistence.cli_persistence import get_options_and_cache
from rscvp.spatial.main_cache_occ import ApplyPosBinCache
from rscvp.spatial.util import sort_neuron, normalized... |
3e1c00b95765a0b7ef2fdcd14946b20bfbbee61fd396c177ecc9ddd06bf700ee | Python | 4,973 | 147 | """
Various transformations used for data preprocessing
RR van de Leur, MN Bos and MB Vessies
"""
import torch
import numpy as np
from scipy import interpolate
class ToTensor(object):
"""
Converts the ECG waveform and label numpy arrays to FloatTensors.
"""
def __call__(self, sample):
wavefo... |
01dc4ce33230c638f0b553799159f3d7fe5a1ee5d74b68d5a20d6cba0f405db4 | Python | 4,974 | 132 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
from __future__ import annotations
import unittest
from types import SimpleNamespace
from unittest import mock
from rest_framework.exceptions import ValidationError
from cvat.apps.quality_control.models import QualityReport, QualityReportTarget
fr... |
af9f1bc3d342279140f005115fbc3af4b755e8364cf21b8d7ff34376ff3da9a5 | Python | 4,977 | 107 | import argparse
import os
import glob
import re
import subprocess
def main():
parser = create_args()
args = parser.parse_args()
chroms = get_union_chroms(args.datasets)
print('combining files from', len(chroms), 'chromosomes over', len(args.datasets), 'datasets...')
combine_longs(args.datasets, chr... |
244d59daa2549f11deb0e9493160687db59c22b12519f609603d3c3858da7848 | Python | 4,979 | 113 | """Train linearizing encoding models using the NSD-core subject-unique image
features and fMRI responses, and use them to predict fMRI responses for the:
(i) NSD-core ID test images.
(i) NSD-core OOD test images.
(iii) NSD-synthetic 284 images.
Parameters
----------
subject : int
Number of the used NSD subject.
data_... |
b6b13f2af4a07c568b8651190eecf2e7414a39a27a8ff32493788c67cb9d91dc | Python | 4,980 | 131 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
from django.contrib.auth import get_user_model
from django.core import mail
from django.test import override_settings
from django.urls import reverse
from rest_framework import status
from cvat.apps.engine.tests.test_rest_api import create_db_users
... |
422b66c50d5196d12e87e3aa860cd1cc29524ea596ebb989c43f6b4fb46d1fc5 | Python | 4,983 | 141 | # %%
import torch
from torch_geometric.nn import SAGEConv, to_hetero,GeneralConv
from torch.nn import Linear
import torch.nn.functional as F
from sklearn.metrics import roc_auc_score,average_precision_score
import numpy as np
import random
import pandas as pd
import itertools
SEED = 666
random.seed(SEED)
... |
8199415977ea4a4e21710701f15764407f189cbf7cc1c1ec9353f26419f695ad | Python | 4,983 | 134 | import os
import csv
from typing import Tuple
import pandas as pd
import logging
from xnat.mixin import ImageScanData
from step1_dataimport.xnatconnectionprovider import XNATConnectionProvider
class DataOverview:
"""
Generates an overview csv-file with DICOM properties and other metadata (subject-, session-, ... |
cf3414848a2378cb0fac7bf86039e9bd65d18e6c0594c2e40b219727f45e4ac3 | Python | 4,983 | 176 | import logging
import os
import random
from collections.abc import Callable, Iterable, Sequence
from functools import wraps
from pathlib import Path
from typing import Any
import numpy as np
import torch
from aislib.misc_utils import ensure_path_exists
from eir.train_utils.distributed import (
in_distributed_env,... |
ed653f76bfa12adb9e483137face034f5cbad9dec060fffc78ce4e33303dd407 | Python | 4,983 | 100 | #encoding=utf-8
import sys
sys.path.append("../")
import jieba
def cuttest(test_sent):
result = jieba.cut(test_sent,HMM=False)
print(" / ".join(result))
if __name__ == "__main__":
cuttest("这是一个伸手不见五指的黑夜。我叫孙悟空，我爱北京，我爱Python和C++。")
cuttest("我不喜欢日本和服。")
cuttest("雷猴回归人间。")
cuttest("工信处女干事每月经过下属科... |
4ffede7faa7f629959c93d290c4276b9b7705243b0f63f37db97b8545f18e659 | Python | 4,985 | 78 | 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 macularCellGenerator import load_json as load_cell_json
from macularSynapseGenerator import load_json as load_synapse_json
def load_jsons(json_dir):
cells_json_da... |
4d8919def3ac7002c7c20a7b0cf201c34020550ad5234c9e4e1b5eb269808988 | Python | 4,986 | 86 | #!/usr/bin/env python
import pandas as pd
import numpy as np
from PAINTeR import global_vars
from PAINTeR import misc
from PAINTeR import qst
# load tables
df_bochum = pd.read_csv(global_vars._BOCHUM_TABLE_)
df_essen = pd.read_csv(global_vars._ESSEN_TABLE_)
df_szeged = pd.read_csv(global_vars._SZEGED_TABLE_)
# calc... |
1ef8c1fbee85c4088e2fe2cee774cf5e90ec128e8c99f9409edfa2e37ef060c0 | Python | 4,990 | 145 | from collections import OrderedDict, namedtuple
from pprint import pformat
from neuro_data.static_images.data_schemas import StaticScan
from neuro_data.static_images.configs import DataConfig
from .utils import gitlog, set_seed
from . import logger as log
import datajoint as dj
from .configs import NetworkConfig, Seed,... |
337c74296a8aed185d24b85a7e0fca60ef0c8a65f1406ab232d1e3ee10457e42 | Python | 4,990 | 134 | """
(C) Copyright 2019 IBM Corp.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
... |
86a57cf9c36d408fbabc272925b0e0207d9cb894bb5a397846f1b206681c7e38 | Python | 4,990 | 211 | """
very simple ini parser and tools
tested on python 3.6
contact: adalca at csail.mit.edu
TODO: see
from collections import namedtuple
instead of Struct
"""
# built-in modules
# we'll need python's ini parser: 'configparser'
import configparser
def ini_to_struct(file):
"""
very simple ini parser that... |
e69500cdb342010319230dbb9869f5661797e4a6eb7341ac277bd7d486da2030 | Python | 4,990 | 101 | #encoding=utf-8
from __future__ import print_function
import sys
sys.path.append("../")
import jieba
def cuttest(test_sent):
result = jieba.cut(test_sent,cut_all=True)
for word in result:
print(word, "/", end=' ')
print("")
if __name__ == "__main__":
cuttest("这是一个伸手不见五指的黑夜。我叫孙悟空，我爱北京，我爱Pytho... |
1b7678a2186a6570153df969b6e3a192dc2e71b5b7b60f05c926fb813b41ada1 | Python | 4,991 | 128 | import numpy as np
from impyute.ops import matrix
from impyute.ops import wrapper
# pylint: disable=invalid-name, too-many-arguments, too-many-locals, too-many-branches, broad-except, len-as-condition
@wrapper.wrappers
@wrapper.checks
def moving_window(data, nindex=None, wsize=5, errors="coerce", func=np.mean,
... |
2ca3948ba9af8efa85fb7d6edc9b1792730a3d5677ae54bb7de15bec0b5764a2 | Python | 4,991 | 149 | '''
GeH4OH
'''
import numpy as np
import sys
def intro():
print("""
SHORT List of potential energy surfaces for GeH4OH:
P: potential energy, G: Gradient, D: Nonadiabatic coupling vector
This is listed at the end of description to show the availability.
For example: P/G means both potential energy... |
c8d8c4b15b2c6cda1fefd5de390a40495adb69b5349b6184801e9cb312ab40a8 | Python | 4,993 | 162 | import os
import numpy as np
from tqdm import tqdm
from glob import glob
from scipy.stats import mode
from fiberpipeline.utils import get_basename
from nicety.conf import get_conf
from tqdm import tqdm
from joblib import Parallel, delayed
from sklearn.decomposition import PCA
from collections import defaultdict
de... |
e5866d379bad9d16b2e302d732c3eec4197c9acc201306f67ef74c58e983e124 | Python | 4,993 | 147 | #!/usr/bin/env python
import warnings
warnings.filterwarnings("ignore", message="numpy.dtype size changed")
warnings.filterwarnings("ignore", message="numpy.ufunc size changed")
import pandas as pd
import numpy as np
from sklearn.externals import joblib
from PAINTeR import global_vars
import PAINTeR.connectivity as con... |
aca8aab6a99873010cdf02b8e8c57336694999f41df72d5f9e15b8fdde5b0ded | Python | 4,994 | 141 | import json
import os
import os.path as osp
from itertools import product
from typing import Callable, List, Optional
import numpy as np
import torch
from torch_geometric.data import (
Data,
InMemoryDataset,
download_url,
extract_zip,
)
from torch_geometric.utils import remove_self_loops
class PPI(I... |
0be8e1850456ac164043923e569c5470a06bf293bc06b12ff446c3a511e09c0b | Python | 4,995 | 157 | # vessap open graph benchmark dataset
import os
import os.path as osp
import sys
import sys
sys.path.insert(0, '../')
sys.path.insert(0, '../../')
sys.path.insert(0, '../../ogb')
import torch
import numpy as np
import pandas as pd
import scipy
import argparse
import networkx as nx
import torch_geometric.transforms as... |
8afbd1c02abd2bf334bc9d0984f96da92c5892e2a02c4a03f106cc68f15daca1 | Python | 4,995 | 139 | # -*- coding: utf-8 -*-
"""
Created on Wed Feb 2 08:16:52 2022
@author: Avlant-MIT
"""
import numpy
import torch
######## MML activation
def MMLactivation(x, leak=0.01):
#x[x<0] = leak*x[x<0]
#x[x>=0.5] = 0.5 * (1 + (1./(0.5/(x[x>=0.5]-0.5) + 1)))
x = numpy.where(x < 0, x * leak, x)
x = numpy.where(x... |
e3d6440c49db2bde8b0dca63baf155b063db9f4433efbaa1ec0bd39803d87bab | Python | 4,995 | 150 | # This file is part of Zennit
# Copyright (C) 2019-2021 Christopher J. Anders
#
# zennit/types.py
#
# Zennit is free software: you can redistribute it and/or modify it under
# the terms of the GNU Lesser General Public License as published by the Free
# Software Foundation; either version 3 of the License, or (at your ... |
ddd4e12ebae0200d9d62b094d5ed1587682c5b3ca7fb4fa47763bcc996091ee1 | Python | 4,996 | 136 | import argschema as ags
import numpy as np
import pandas as pd
from skeleton_keys.io import (
load_default_layer_template,
write_dataframe_to_csv,
read_csv,
read_json_file,
)
from skeleton_keys import cloudfields
class ProfilesFromAlignedCoordsParameters(ags.ArgSchema):
coordinate_file = cloudfiel... |
e604cfe7211589db99c3e6a17dc2b64a5581ec92ce0db825bb51ed0e618632de | Python | 4,996 | 112 | # flake8: noqa
"""run_youtube_vis.py
Run example:
run_youtube_vis.py --USE_PARALLEL False --METRICS HOTA --TRACKERS_TO_EVAL STEm_Seg
Command Line Arguments: Defaults, # Comments
Eval arguments:
'USE_PARALLEL': False,
'NUM_PARALLEL_CORES': 8,
'BREAK_ON_ERROR': True, # Raises exc... |
d21621eac0fcbf19dc263d9793550da672425ef68b56ad58577570d724078c02 | Python | 4,998 | 161 | """
A DeepReg Demo for classical affine iterative pairwise registration algorithms
"""
import argparse
import os
import shutil
import h5py
import tensorflow as tf
import deepreg.model.layer_util as layer_util
import deepreg.util as util
from deepreg.dataset.preprocess import gen_rand_affine_transform
from deepreg.reg... |
24a1a4a5e985eb0418a432c8be94572016a35ce62270050dabb287c081aa39cf | Python | 4,999 | 151 | from typing import Tuple, Type
from dipy.utils.optpkg import optional_package
from scilpy.ml.utils import IMPORT_ERROR_MSG
torch, have_torch, _ = optional_package('torch', trip_msg=IMPORT_ERROR_MSG)
""" The classes in this file are from the SAM-Med3D repository:
https://github.com/uni-medical/SAM-Med3D
"""
cl... |
34dd41919cd3a79942a27df5837ef7ac8a08392abe8a3076c822ffe93de8109b | Python | 4,999 | 136 | # Copyright (C) 2019-2022 Intel Corporation
# Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
import shutil
from datumaro.components.annotation import AnnotationType
from datumaro.components.dataset import Dataset
from datumaro.components.transformer import ItemTransform
from cvat.apps.dataset_man... |
997a193bfa845aac160a3c5b870bbc71d5ba5f14641ba140df4d9e386c487eed | Python | 5,000 | 154 | from __future__ import absolute_import
from collections import defaultdict
import math
import numpy as np
import copy
import random
import torch
from torch.utils.data.sampler import (
Sampler, SequentialSampler, RandomSampler, SubsetRandomSampler,
WeightedRandomSampler)
def No_index(a, b):
assert isinsta... |
bb770f0b7e87805e2499496653e97252e1a7702d385a91a165cfb4df4adba68c | Python | 5,001 | 187 | # -*- coding: utf-8 -*-
"""
Convolve volumetric data with a 3d kernel, optimized for memory / float32 use
Based on `scipy.signal <http://docs.scipy.org/doc/scipy/reference/signal.html>`_
routines.
Author
""""""
Original code from `scipy.signal <http://docs.scipy.org/doc/scipy/reference/signal.html>`_.
Modifi... |
3debf29bb0ac35869af56ea43d11a430dc9e90b2260acb70a32a7cb50481e819 | Python | 5,002 | 134 | import datajoint as dj
from staticnet_analyses import base
from staticnet_experiments import models as static_models, configs as static_configs, utils
from neuro_data.static_images.configs import DataConfig
from neuro_data.static_images import stats
import numpy as np
from itertools import count
schema = dj.schema('zh... |
68bf502a5ca7d1c8fc469076684723a27e4336c979552723139b3f20ef8b94f0 | Python | 5,002 | 136 | import torch
from torch import Tensor
from bism.utils.morphology import binary_erosion
from yacs.config import CfgNode
import numpy as np
def _make_neighborhood(radius: int = 1, device='cpu'):
"""
Creates a matrix of pixel connected components.
:param radius: distance of connected components
:param d... |
9b53b9b23c4a0957b1931241934c13e75ce503906d164b8fda2f6e2cb063956e | Python | 5,002 | 119 | """
file: Graph_Analysis_Demo.py
author: Tiago Ferreira, Cameron Arshadi
version: 20190402
info: Demonstrates how to handle neurons as graph structures[1] (graph theory)
in which nodes connected by edges define the morphology of the neuron.
SNT represents neurons as directed g... |
a343ac633d2bc6d3bae0c6b2e9bf74f09cc41701bae437a1c88d2988a328dae4 | Python | 5,002 | 96 | import os
from nipype.interfaces.base import (
CommandLine,
CommandLineInputSpec,
TraitedSpec,
File,
traits,
isdefined,
)
class PlotTckOnSliceCmdInputSpec(CommandLineInputSpec):
# Must appear immediately after "python" in the command
script_path = File(exists=True, mandatory=True, arg... |
ba2acc17123916ddd51487259c792ac1d7ab409cb8f6b30564f3171342a09452 | Python | 5,004 | 145 | import argparse
import glob
import os
import random
import shutil
import sys
import numpy as np
import pytorch_lightning as L
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.data as data
import torchvision as tv
from lightning.pytorch import loggers as pl_loggers
from pytorch_ligh... |
c0ea9b0d9bc4fd8c5e4eed2e8bd13a609862c4e669d9ab41cd348c0a704c4e32 | Python | 5,004 | 161 | from typing import Optional
from pathlib import Path
import typer
from typing_extensions import Annotated
from importlib.metadata import version
from brainles_preprocessing.modality import Modality, CenterModality
from brainles_preprocessing.normalization.percentile_normalizer import (
PercentileNormalizer,
)
fro... |
ea3eed1312eedd6c32ac63f6753389f05359bdab373219dbb1e11204287f4aa8 | Python | 5,004 | 123 | #!/usr/bin/env python
"""
HAL module for Coherent laser control.
Hazen 04/17
"""
import storm_control.hal4000.halLib.halMessage as halMessage
import storm_control.sc_hardware.baseClasses.amplitudeModule as amplitudeModule
import storm_control.sc_hardware.baseClasses.hardwareModule as hardwareModule
class CoherentL... |
166c04c29b2138cdd2da5b151b6e90c6d42b21ac5db61d706a2ac807246021c4 | Python | 5,005 | 131 | #############################################################################
# Copyright (C) 2020-2026 MEmilio
#
# Authors: Henrik Zunker
#
# 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 Lice... |
e67a227e016254b5415eb7c444d7ef9b887c6603a51424860615e7d8d6a59a0b | Python | 5,005 | 131 | # Copyright 2024 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, ... |
29cd4a567ee8e826d1e1315e8679108f44605c9861537955dcfa31e8a3542eea | Python | 5,008 | 161 | """
Loss Functions for AVPENet.
Implements the composite loss function from Section "Loss Function Design",
Equations 24–27:
L_total = α · L_MSE + β · L_ordinal + γ · L_smooth
where:
L_MSE = mean squared error (primary metric)
L_ordinal = ordinal consistency loss (encourages rank ordering)
L_smoo... |
3878ca3aa35b95e628f10bfca8895ba5826e99005a998b5cc839293d2f054147 | Python | 5,008 | 121 | import skimage.io as skio
import numpy as np
from natsort import natsorted
from skimage.morphology import label
from napari_simpleitk_image_processing import label_statistics
import time
from tqdm import tqdm
import os
import glob
import parameter_search.helper as helper
import pandas as pd
# Setting up the parameters... |
560910a96f5505ab71de071a28a9726232bbe45e14137e18a840f1a89c094ef7 | Python | 5,008 | 130 | import warnings
from typing import Optional, Union
import torch
from torch import Tensor
import torch_geometric.typing
from torch_geometric.nn.conv import MessagePassing
from torch_geometric.nn.dense.linear import Linear
from torch_geometric.typing import OptPairTensor # noqa
from torch_geometric.typing import OptTe... |
f4f63b81a39e15d991421e23bcf87ca093063ff533f5e7623c4d20225712baac | Python | 5,009 | 148 | import argparse
import os
import os.path as osp
import time
import numpy as np
import torch
import torch.nn.functional as F
from sklearn.metrics import f1_score
import pandas
import json
import torch_geometric.transforms as T
from tqdm import tqdm
import spacy
import re
from vaderSentiment.vaderSentiment import Sentime... |
1e511cc06cd94b7751e08f6cb91580d78d4a330ad535b83223cec04a4282aea0 | Python | 5,010 | 174 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Common io helper functions
"""
import os
import argparse
import pickle
def str2bool(arg_in):
"""
Convert a string argument to a boolean.
Parameters:
-----------
arg_in : str or bool
Input argument to be converted.
Returns:
... |
b61a31405305fe28a490f5a49cd1efb53eb0b1d5e19d6e237bc45dbbe8a24dbd | Python | 5,010 | 149 | import argparse
import os
import os.path as osp
import time
import numpy as np
import torch
import torch.nn.functional as F
from sklearn.metrics import f1_score
import pandas
import json
import torch_geometric.transforms as T
from tqdm import tqdm
import spacy
import re
from vaderSentiment.vaderSentiment import Sentime... |
cbe9b2fb4d6242ffff627fa791ae1334cfd60a22b4d07b1790343ad07b529532 | Python | 5,010 | 149 | import argparse
import os
import os.path as osp
import time
import numpy as np
import torch
import torch.nn.functional as F
from sklearn.metrics import f1_score
import pandas
import json
import torch_geometric.transforms as T
from tqdm import tqdm
import spacy
import re
from vaderSentiment.vaderSentiment import Sentime... |
41834af965b6af07965c2303c625e0ab7a09c59a95a090eb048d58e707dd75d5 | Python | 5,011 | 115 | import os
import numpy as np
import skimage.io as skio
import dask_image.imread
COORDS = {
'LADAF-2020-27':{
'2.58um_to_12.1um':{
"x_range": (765, 1049), # last already + 1
"y_range": (819, 1103), # last already + 1
"z_range": (123, 1281), # last already + 1
... |
4b369adf102102091589c92fdae075ac456dbf15d91cbc60d424664bc33d9ba5 | Python | 5,011 | 140 | # Copyright 2024 DeepMind Technologies Limited
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agree... |
38e44b2368c9a7d8020e33032a6ef5e9e168eacf61a698c1b1378ffc365cbc81 | Python | 5,013 | 131 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Evaluate graph theory measures from functional connectivity matrices.
The functional connectivity matrix is assumed to come from fMRI bold
correlations (-1 to 1 values). Hence, the matrix is first
made strictly positive (absolute value) and thresholded above a certain
... |
e94e332502ed82c6d302d877f366d06202d024e7006f3d7543cb0229f29d3205 | Python | 5,013 | 157 | from collections import OrderedDict
from collections.abc import Sequence
from dataclasses import dataclass
from typing import TYPE_CHECKING, Literal
import torch
from torch import nn
from eir.models.layers.mlp_layers import MLPResidualBlock, ResidualMLPConfig
from eir.models.models_utils import (
calculate_module... |
216fabfd49f3f8c19debf40cbc657fcdb98d04e6635820965e6847cd77d88134 | Python | 5,014 | 171 | """
Task manager for organizing parallel processing results.
Handles task submission, completion tracking, and result organization.
"""
import threading
import time
from dataclasses import dataclass, field
from typing import Optional, Dict, Any, List
from enum import Enum
class TaskStatus(Enum):
"""Status of a p... |
29651cc70dba2ed7149a8868a48453657a2fc8ad252af038af13b55cb88c2386 | Python | 5,014 | 92 | import os
def setup_environment(system_mode="local-H-Drive"):
if system_mode == "local-H-Drive": # Example structure for local path management regarding this project
os.environ['DATA_PATH'] = r"H:\Users\Username\Data"
os.environ['COMPLETE_TRIPLE_PATH'] = r"H:\Users\Username\Data\filenames_csv"
... |
a94ef23fa9a1af017cba712cf9d5244477189f00edb55762e8ae0484c1713165 | Python | 5,014 | 135 | """
Concatenates and normalizes EEG data
Saves a .mat file with task- and period-specific EEG for all participants.
Also optionally saves a .mat file with the nonnormalized, task and period specific EEG concatenated for all participants
"""
import mne
import os
import glob
import numpy as np
import pandas as pd
from ... |
3ab38b1915444983bb5e0d0d11eda49a4bf6cbbfaf49f2916f527b2342534786 | Python | 5,016 | 133 | # Kai Sandbrink
# 2023-02-01
# This script computes the learning curves for specified test models
# %% LIBRARY IMPORTS
import torch
import pandas as pd
import numpy as np
from utils import Config, get_timestamp, flatten
from utils_project import load_config_files
from test_case import test
import os, copy, pickle
imp... |
6c6274fd59639b4f6968f027a50061b7a75b0f5aeef159d2cba99c959ea97b35 | Python | 5,016 | 145 | import sys
import yaml
import os
import numpy as np
import h5py
import matplotlib as mpl
import matplotlib.pyplot as plt
pathpath,myrun,ncluststr,cmethod = sys.argv[1:]
'''
pathpath = 'PATHS/filepaths_carlen.yml'
myrun = 'runC00dMP3_brain'
ncluststr = '8'
cmethod = 'ward'
'''
ncl = int(ncluststr)
with open(pathpa... |
956529675b59c31575c3204fcf3338e07343b0775fb78bbea939bcb7153bb23b | Python | 5,016 | 138 | """
This module contains functions for calculating selectivity and related metrics.
"""
import numpy as np
from sklearn.metrics import roc_auc_score
def bootstrap_rate_diff(condition1, condition2, n_reps=1000):
"""
This function performs a bootstrap test to assess the significance of the difference
in fi... |
f00044ee2ffcea9ba29f9f723c3bb5a43bc00bef100934703044b2db7a442433 | Python | 5,017 | 114 | # flake8: noqa
"""run_youtube_vis.py
Run example:
run_youtube_vis.py --USE_PARALLEL False --METRICS HOTA --TRACKERS_TO_EVAL STEm_Seg
Command Line Arguments: Defaults, # Comments
Eval arguments:
'USE_PARALLEL': False,
'NUM_PARALLEL_CORES': 8,
'BREAK_ON_ERROR': True, # Raises exc... |
eba817296c79fb07ea6e3bbe9e26b4e52ea9813b96754a9dd619cda7334aa8b5 | Python | 5,019 | 151 | """
Audio Encoder for AVPENet.
Modified ResNet-34 architecture adapted for mel-spectrogram processing.
Input: (B, 1, 128, 300) — mel-spectrogram
Output: (B, 512) — audio embedding
Reference: Section "Audio Encoder Architecture" of the paper.
"""
import torch
import torch.nn as nn
import torch.nn.function... |
27dc4df11464f18a981a00096d8f914137b35a5acb0dd543116940c509b9afb9 | Python | 5,021 | 135 | from typing import Any, Callable, Dict, List, Tuple, TypeVar, Iterable, Iterator
import re
import torch
import numpy
JsonDict = Dict[str, Any]
# If you want to have start and/or end symbols for any reason in your code, we recommend you use
# these, to have a common place to import from. Also, it's important for some e... |
4c5aa8e356401ed30c56619587946f2c8f0dc676dea3c8bb8d64b432542fc747 | Python | 5,021 | 152 | import tkinter as tk
from tkinter import messagebox, simpledialog, filedialog
from impedancefitter import Fitter, available_file_format
directory = None
def browse_button():
global directory
directory = filedialog.askdirectory()
class MainWindow(tk.Frame):
def __init__(self, master=None):
tk.F... |
53606f1cb2f35aa4e3be4d7579e4c419b022d1263960e621d3993edb6f26a8d6 | Python | 5,023 | 138 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
from collections.abc import Iterator
from datetime import datetime
from pathlib import Path
from typing import Any, ClassVar
from attrs import field, frozen, validators
from django.apps import AppConfig, apps
from django.utils import timezone
from r... |
1a741f3a85b41abc423cc2e85cb16ab4a76166a47537dfd67b6a16b1fd0ebd37 | Python | 5,024 | 116 | import numpy as np
from scipy import stats
from utils import Recorder_select, Q_nak
from mitochondria import Mito
import matplotlib.pyplot as plt
from figure_properties import *
from default_ca_conc import ca_freq_concs
dt = 0.1
seed = 11
np.random.seed(seed)
def generate_spiketrain(rate, duration): # duration giv... |
af2a6da4cc6d5a412789ded4eb1732414bfb6db85379c2f0fb614a18980943d6 | Python | 5,026 | 141 | ## ------------------------------------------------------------
## IMPORTS
## ------------------------------------------------------------
import torch
import torch.nn as nn
from LSTMConvCell import *
## ------------------------------------------------------------
## Explain the block
## -----------------------------... |
9d79b25ee03fdc85c5d5efef00460c390153f6da6c7804c4bdfd8697bc90688b | Python | 5,027 | 115 | # Copyright 2024 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, ... |
ff349f4719fc95f6bd77b38251440cdc9426d09bc6164c436e289b679682b0b4 | Python | 5,027 | 160 | #%% imports
from convenience import get_collection
from construct import reconstruct_from_folder
from sys import platform
import pandas as pd
import yaml
from pathlib import Path
collection = 'mito_ideas_models'
if platform == "linux" or platform == "linux2":
main_folder = Path("/mnt/LEB/Scientific_projects/deep_... |
82a35c49f76904620d4b0b0d4b93cf25ac604379c8b8bffde58599a874d29201 | Python | 5,028 | 128 | #! /usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Detect sign flips and/or axes swaps in the gradients table from a fiber
coherence index [1]. The script takes as input the principal direction(s)
at each voxel, the b-vectors and the fractional anisotropy map and outputs
a corrected b-vectors file.
A typical pipeline... |
afdd488e3eb080d42785d1a5c449b0f9ff01b1cc03d8151a573195bda7159a56 | Python | 5,028 | 119 | # Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved
# 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 warnings
import torch
import torch.nn as nn
import torch.nn.functional as F
from torchvision.t... |
87317ccf030deb907b52deea1118d73e57507bfc5571c35b7c37fe2213ea66fa | Python | 5,033 | 120 | """
Run decoding analyses by eccentricity.
"""
from utils.prepare_data import PrepareData
from utils.foveal_decoding import FovealDecoding
import matplotlib.pyplot as plt
import pandas as pd
accuracies_exp_all = pd.DataFrame()
accuracies_control_all = pd.DataFrame()
accuracies_cross_all = pd.DataFrame()
se_exp_all = ... |
08b450e09fb4046506a6599be6f4e7958103ec648aaaa0b196823b5a31d99ff7 | Python | 5,035 | 129 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
"""Attach an S3-compatible bucket to CVAT as a cloud storage, then list,
retrieve, and update it. Any S3-compatible service works (AWS S3, minio, ...)
via the AWS_S3_BUCKET provider and a custom endpoint URL.
There is no high-level proxy for cloud s... |
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