sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
a0333d4e575bd6b90c40e47424ce6d439e3e5958b7182874e92ed07aa9b2993d | Python | 7,826 | 187 | import argparse
import os
import time
from datetime import datetime
import numpy as np
from skimage.metrics import peak_signal_noise_ratio, structural_similarity
from torch.utils.tensorboard import SummaryWriter
from inr import models
from utils import *
import torch
import skimage
from scipy.ndimage import zoom
import... |
12ba4ad37c49375f096d40bff5ba445db9cd739dc797f7b0a183fc9765adf101 | Python | 7,827 | 263 | #!/usr/bin/env python
#
# make_page.py creates a HTML page with links to files in given directories
#
# Copyright FJ Nedelec, 14.12.2007 -- 4.2015 & 7.3.2022
"""
Synopsis:
Generates an HTML page linking images & movies found in sub-directories
Usage:
make_page.py [recursive=1] [tile=INT] [width=INT] [he... |
56194162ee79e7b9e1dcc7b63263e1a1e74a87c93798addeb303b2c222bf9b9d | Python | 7,827 | 217 | import sys
import yaml
import os
import numpy as np
import matplotlib.pyplot as plt
import matplotlib as mpl
pathpath,run1,run2,stag1,stag2,ncluststr1,ncluststr2, cmethod = sys.argv[1:]
stags = [stag1,stag2]
'''
pathpath = 'PATHS/filepaths_carlen.yml'
run1 = 'runC00dMP3_brain'
run2 = 'runCrespZP_brain'
stags = ['spo... |
b5914b48ff4cc2e12a3261ad47f1f5b10f69ede774a27473e663987b5730bf9b | Python | 7,830 | 252 | import os
import shutil
from dataclasses import replace
from pathlib import Path
from typing import List, Tuple
from unittest.mock import Mock, create_autospec
import napari
import numpy as np
import pytest
import torch
from brainglobe_atlasapi.structure_class import StructuresDict
from PIL import Image
from pytest im... |
7f7107b42f5d3fd6339146bf461acb5bc08dbce1b7c5014f859add7bab61317c | Python | 7,831 | 233 | import functools
import time as pytime
from pathlib import Path
import click
import numpy as np
import pyvista as pv
import simple_mri as sm
import skimage
import SVMTK as svmtk
from loguru import logger
from panta_rhei.meshprocessing import mesh2xdmf, xdmf2hdf
from brainmeshing.utils import (
binary_image_surfac... |
a56a39abcacb352694d9f102a4fecbf13fda8abb5aba48ceced2f216cd8abdfc | Python | 7,831 | 210 | from typing import List, Optional, Union
import torch
import torch.nn.functional as F
from torch import Tensor
from torch.nn import Parameter
from torch_geometric.nn.inits import ones, zeros
from torch_geometric.typing import OptTensor
from torch_geometric.utils import degree, scatter
class LayerNorm(torch.nn.Modul... |
c0d0db41e771396f6ae22773bd463949a4c41052de104ff1e22a5e7b124c7bc6 | Python | 7,831 | 213 | #!/usr/bin/env python
"""Direct Globus Transfer + Globus Compute demo.
Stages the 5 .xyz fixtures to a remote HPC collection via Globus
Transfer, then runs MACE ``driver="thermo"`` on each pre-staged file
through Globus Compute. Workers read the structures from the HPC
filesystem (remote-path mode), not embedded inlin... |
a680ab5a110d4c495694fa7bf69ae187af7c0d1e9bf5056cdde3e33e73e61e66 | Python | 7,832 | 162 | import numpy as np
from itertools import product
from scipy.stats import ttest_1samp, ttest_rel
from scipy import stats
import matplotlib.pyplot as plt
import seaborn as sns
from utils.const import (SUBJECTS, LABEL_NAMES, CHANCE_LEVEL)
class PlotResults:
"""
Class for plotting decoding results.
"""
de... |
a9539cad9ce409d288de57516bdc7b02e8a392e16bd24ac14aed0afd8a7bb233 | Python | 7,834 | 188 | # Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import torch
from torch import nn
from torch.nn import functional as F
from typing import Any, Dict, List, Tuple
from .i... |
fc7f1da9916cc274e84f3ba1b66b4fc77f0ea518ee4213b7e231d09b57b32804 | Python | 7,835 | 177 | #############################################################################
# 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... |
4051925585cc3fe5b97351f7672d52c6c25d4ab6276fe1b43241b84dcfd7904e | Python | 7,836 | 191 | # Copyright (c) 2022, Kwanhyung Lee. All rights reserved.
#
# Licensed under the MIT License;
# you may not use this file except in compliance with the License.
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT W... |
98c5f468499b004bacbff4c76c0e49b0a1c1b9522ac1216536719aac6b34f5f4 | Python | 7,836 | 166 | """Score spike sorters against synthetic ground truth on a low-density MEA.
This is what picks MEA-NAP's default sorter and validates its presets and
curation floors — see python/SPIKE_SORTING_PLAN.md §5. Run it after touching
``pipeline/spike_sorting.py``::
uv run python python/benchmark_spike_sorting.py --out l... |
57c617c7109a6f556725e02331ca35baa638a6e86378bf6168e19f4fc2668824 | Python | 7,838 | 161 |
import pathlib
import h5py
import matplotlib
import numpy as np
matplotlib.use('Qt5Agg')
import matplotlib.pyplot as plt
from postprocessing_modules.axonal_delay_kernel import get_axonal_delay_kernel
from helper_functions import __file__
from helper_functions.plotting_lib import round_sig_decimal
MODULE_BASE = pathli... |
23d8983f5741722aedc9ca80c129adcde1ee31a41aff6298e3e23b3295b7a5e8 | Python | 7,840 | 226 | import click as ck
import pandas as pd
from deepgo.utils import Ontology, propagate_annots
import torch as th
import numpy as np
from torch import nn
from torch.nn import functional as F
from torch import optim
import copy
from torch.utils.data import DataLoader, IterableDataset, TensorDataset
from itertools import cyc... |
052c82e14bc35a545126379451e8e3af58349ea516f7e5437b0b696dba0b44e5 | Python | 7,842 | 223 | """Normalization layers for 2D feature maps."""
from typing import Any, Union
import numpy as np
import torch
from torch import nn
__all__ = [
'SpikingBatchNorm2d', 'SpikingEiNorm2d'
]
class SpikingBatchNorm2d(nn.Module):
"""Batch normalization wrapper."""
def __init__(self, num_features: int, eps: fl... |
40830f4b6060f3d0f7fa83a013f0bd6e7a2b298c02658b762aecaf644d6404ea | Python | 7,842 | 224 | import json
import argparse
from chemgraph.tools.ase_tools import run_ase
from chemgraph.tools.cheminformatics_tools import smiles_to_atomsdata
from chemgraph.models.ase_input import ASEInputSchema
import datetime
import subprocess
def get_atomsdata_from_smiles(smiles: str) -> dict:
"""Return a workflow of conver... |
6eb0de7effd0f8ed119217656e6a708e649324e4187601b2e720822171ca87b8 | Python | 7,845 | 215 | # Copyright 2016 Numenta Inc.
#
# Copyright may exist in Contributors' modifications
# and/or contributions to the work.
#
# Use of this source code is governed by the MIT
# license that can be found in the LICENSE file or at
# https://opensource.org/licenses/MIT.
class ContextOperator(object):
"""
... |
56c01c0b4945d4753a20370062a582eea691d8f407066e1618e0dabfdb7302d7 | Python | 7,849 | 233 | """Defines functions for ADMET-AI plots."""
import re
from io import BytesIO
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
from rdkit import Chem
from rdkit.Chem.Draw.rdMolDraw2D import MolDraw2DSVG
from admet_ai.admet_info import (
get_admet_id_to_units,
get_ad... |
7ba591bc7d59a5a5d8e647eecb6f8be5f50d881db29a6be347b55346303f4d2f | Python | 7,849 | 181 |
import pandas as pd
from pathlib import Path
from pkg_resources import resource_filename
from natsort import natsorted
from tifffile import tifffile
from napari_dmc_brainmap.registration.sharpy_track.sharpy_track.model.calculation import fitGeoTrans, mapPointTransform
from napari_dmc_brainmap.utils import get_bregma, ... |
516b8134c5ec2868f52b509b010a45c9ba25da42ea8fcf60ec6a4889a333e095 | Python | 7,858 | 236 | import os
import csv
import pandas as pd
import numpy as np
import glob
from PIL import Image
from tqdm import tqdm
from pathlib import Path
import numpy as np
import staintools
import pandas as pd
from PIL import Image
import torch
from torchvision import models
from torchvision import transforms
from torch.utils.d... |
80491603fab912bc62336d19811d4f7b52c9d4cc97d3ac3da195596c01ed4673 | Python | 7,858 | 237 | import unittest
import numpy as np
import sigpy as sp
import torch
import torch.nn as nn
import torch.optim as optim
import torch.testing as ptt
from deepdwi import fourier, lsqr
from deepdwi.models import mri
from deepdwi.dims import *
if __name__ == "__main__":
unittest.main()
devices = [torch.device('cpu')... |
d4dbedbaa87e30ca3f2be3f8f80ed450b87129f2d6cc055d181ac1368125d378 | Python | 7,858 | 214 | #!/usr/bin/env python
"""
QGraphicsView customized for displaying camera images.
Hazen 3/17
"""
from PyQt5 import QtCore, QtGui, QtWidgets
class QtCameraGraphicsView(QtWidgets.QGraphicsView):
"""
This is responsible for handling the camera transforms
(flip_horizontal, flip_vertical, transpose). Hopefull... |
3762b68189cf9bf70495f22ca01d5f0f458f118774bd053b9bd83c646954f2ee | Python | 7,860 | 215 | #!/usr/bin/python3
#
import os
import sys
import argparse
import numpy as np
from uac import utils
# Create the parser
my_parser = argparse.ArgumentParser(description="Calculation of old atrial coordinates")
# Add the arguments
my_parser.add_argument("target_path", metavar="path", type=str, help="Path for the new ta... |
4bd9bd69551d404ec19c248598e2e76d1b20a4d2aaae49f2569e22dc87e49573 | Python | 7,860 | 255 | from collections import deque, Counter
import warnings
import pandas as pd
import numpy as np
from xml.etree import ElementTree as ET
import math
BIOLOGICAL_PROCESS = 'GO:0008150'
MOLECULAR_FUNCTION = 'GO:0003674'
CELLULAR_COMPONENT = 'GO:0005575'
HAS_FUNCTION = 'http://mowl.borg/has_function'
FUNC_DICT = {
'cc':... |
a682f015832a677851ef84bcaf17e4d1b713e105c52c974d3a0a5c50049cedfd | Python | 7,860 | 223 | from collections import Counter
from collections.abc import Iterable, Sequence
from statistics import mean
from typing import TYPE_CHECKING
import numpy as np
import torch
from torch.utils.data import WeightedRandomSampler
from eir.utils.logging import get_logger
if TYPE_CHECKING:
from eir.data_load.datasets imp... |
a30dd22aab87d76d395cc7580c02634e576d605044c2d8544f8f1e67ac666f20 | Python | 7,862 | 209 | from cc3d import connected_components
from numpy import unique, delete, zeros, isin, hstack, asarray, argmin, array, where
from numpy import min as npmin
from numpy import sum as npsum
from scipy.spatial.distance import cdist
from vg import normalize, perpendicular, angle, basis
from scipy.spatial.transform import Rota... |
78d152fe61cde65d66cec568f0f2559b6d6b7ba2d7febe140d711279d38c260d | Python | 7,864 | 210 | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn import init
from model.coatnet import conv_3x3_bn, MBConv # 确保这两个函数已定义
# ======================
# 激活函数和 SE 模块
# ======================
class hswish(nn.Module):
def forward(self, x):
return x * F.relu6(x + 3, inplace=True) /... |
d51b13f88d0327077a9b142b164979acf65b5ce69e5957b241c1672e4060f0a4 | Python | 7,864 | 207 | """Perform multidimensional scaling (MDS) on NSD-synthetic's and NSD-core's
(scan sessions 10 and 20) fMRI responses of all subjects and of all vertices
with ncsnr above a threshold.
Parameters
----------
subjects : list
List of the used NSD subjects.
ncsnr_threshold : float
Lower bound ncsnr threshold of the kept v... |
fc38404d95c7d4d7e4aedb7de4e9e1272eecb7fe9e3753e5898fea65de5d6ec1 | Python | 7,865 | 211 | import copy
import os
from pathlib import Path
import numpy as np
import pytest
import torch
from mcmlnet.utils.caching import (
np_cache_to_file,
torch_to_np,
)
class TestTorchToNp:
def test_torch_to_np(self) -> None:
"""Test conversion from torch tensors to numpy arrays."""
t = torch.t... |
93ba46c4d43dc938b9b7a4b42a07bf3db488b2cea5be34e2e332c5a44034c0d5 | Python | 7,869 | 257 | """
This module contains functions for visualizing training results,
such as parameter marginals and spectra.
"""
import matplotlib.pyplot as plt
import numpy as np
import torch
from mcmlnet.utils.logging import setup_logging
from mcmlnet.utils.process_spectra import coeff_of_variation
from mcmlnet.utils.tensor impor... |
d09454e20dfa9a3bc153788fa9a32eca9160d610aaa587b10f5f303ae62d29f5 | Python | 7,870 | 209 | import os
import sys
import pprint
import torch
from torchdrug import core
from torchdrug.utils import comm
from torch.utils import data as torch_data
from torchdrug import data, core, utils
import pandas as pd
sys.path.append(os.path.dirname(os.path.dirname(__file__)))
from biopathnet import dataset, layer, model, ... |
b8660654f579cd36eb9e519929444b934df719c25b8fcfe0e91da99a550a125a | Python | 7,871 | 161 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sun Mar 30 09:58:35 2025
@author: loesch
"""
from chiCa import *
import chiCa
import matplotlib.pyplot as plt
plt.rcParams["font.family"] = "Arial"
from labdatatools import *
import os
from glob import glob
from scipy.ndimage import zoom
#%%---Load the da... |
d35fea81b6018d6832d5f5cd284fe374efb6b8ea4d7e7e3250c6d4263d163407 | Python | 7,871 | 195 | import pytest
import os
from bannotator.data import Annotation
import numpy as np
TEST_ANNOTATION_FILE_LARGE = os.path.join("tests", "annotation", "annotation.txt")
TEST_ANNOTATION_FILE_SMALL = os.path.join("tests", "annotation", "annotation_small.txt")
TEST_CONFIG_FILE = os.path.join("tests", "annotation", "config.tx... |
b489c0f057cb77de65c1dc810bfe738de881abf167781d90a5afe6a07ea1427a | Python | 7,872 | 160 | from numpy import float32, expand_dims, array
from skimage.io import imread, imsave
from ants import from_numpy, registration, apply_transforms
from re import sub
from os.path import basename, dirname
from tifffile import TiffFile
from tqdm import tqdm
from os.path import exists
from novas3d.utilities import get_mov_fi... |
593ea9cd19b73236a4763cef279158f0b62f39da6a57e795db1eeebff66a1110 | Python | 7,876 | 238 | from __future__ import annotations
import shutil
import zipfile
from io import BytesIO
from pathlib import Path
from typing import ClassVar, Dict, List, Tuple
import requests
from loguru import logger
from rich.progress import Progress, SpinnerColumn, TextColumn
ATLASES_FOLDER = Path(__file__).parent.parent / "regis... |
a878a50ec51737747fe34340436532999dd73aa64d763caadf206d89bb6aa8cf | Python | 7,876 | 229 | """
Configuration management for ChemGraph Streamlit app.
"""
import copy
import toml
import os
from pathlib import Path
from typing import Dict, Any, Optional
from chemgraph.utils.config_utils import flatten_config as _flatten_config
from chemgraph.utils.calculator_defaults import get_default_mace_calculator_type
CO... |
bcde53a16b9bada1638fac20e479816d9854e489c846bddc69e5cf8d51ec9998 | Python | 7,876 | 215 | """
This is ported from Matlab code from the original TDR codebase.
"""
import numpy as np
import pandas as pd
import copy
def average_conditions(data, conditions):
task_index = {}
for key, value in conditions.items():
unique_values, indices = np.unique(value, return_inverse=True)
task_index[... |
ea69c948d8a5e2e0849ae41baeace887b59145182598262a5c6acafdd6364a6b | Python | 7,876 | 233 | #!/usr/bin/env python
"""
RS232 interface to a Zaber XY stage.
Hazen 04/17
Jeff 04/21
"""
import traceback
import storm_control.sc_hardware.serial.RS232 as RS232
import storm_control.sc_library.hdebug as hdebug
class ZaberXYRS232(RS232.RS232):
"""
ZaberXY stage RS232 interface class.
"""
def __init_... |
c4e201ad96f1b904b7c2a094f79fa5ad79f8c5d87b37f3ae18f6e915d4fdfcb4 | Python | 7,877 | 150 | import os
import json
import ijson
import argparse
import pandas as pd
import numpy as np
from feature_engineering import feature_preprocess
from feature_twibot22 import preprocess
from feature_supplement import preprocessing
from sklearn.ensemble import RandomForestClassifier
from sklearn.metrics import accuracy_score... |
f77d5207ea4a1c3f099ce412bf1b0e36a42164de6771aa8202bcfa57d99075fa | Python | 7,878 | 198 | # -*- coding: utf-8 -*-
"""
Created on Fri May 29 09:25:58 2020
文本分类 双向LSTM + Attention 算法
@author:
"""
import copy
import torch
import torch.nn as nn
import torch.nn.functional as F
from data_processor import DataProcessor
torch.manual_seed(100) #保证每次运行初始化的随机数相同
vocab_size = 50000 #词表大小
embedding_size = 25 #词向... |
31bc62026eae791910fe3ab88ef1b88b6c8572d4a5942f4d800c5116e2688247 | Python | 7,879 | 213 | import tensorflow as tf
from tensorflow.keras.losses import Loss
class MyLoss(Loss):
"""
A custom TensorFlow loss that computes exchange-correlation (XC) energies
for multiple test sets and molecules, using model predictions.
The loss internally:
1) Splits predicted tensors to compute average XC ... |
318bf81030558863a4ec6effea3c9d063a297f299367e379a58b89c24e3f421f | Python | 7,881 | 168 | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
import numpy as np
from ultralytics.utils.metrics import batch_probiou, bbox_ioa
try:
import lap # for linear_assignment
assert lap.__version__ # verify package is not directory
except (ImportError, AssertionError, AttributeError):
fr... |
5d5f6e700e9b69e1250c514130b12c44e1cd9f9a17b2b088a92b8f36029b07d3 | Python | 7,883 | 243 | # Imports
import glob
from pathlib import Path
import numpy as np
import numpy.typing as npt
import pandas as pd
import ase.io
import joblib
import pickle
from modules.build_data.fhi_aims.crosscheck_names import crosscheck_parts_with_xyz
from modules.tools.system_cutoff import find_closest_atoms_to_mol
from modules.... |
9893add2d17329eb506c8d42e5d5846e942497f2b4872913d37f43b25d1cf185 | Python | 7,885 | 223 | """Plot data extractors.
The responsibility of these classes is to extract the data from the
EvaluationResults objects to match the requested plot.
"""
import abc
from sklearn import metrics
from . import curve_data_makers, plots
from ...metrics.weight_metrics import calculate_covariate_balance
class BaseEvaluati... |
beb5bc84c224a7690b854dc7f5b0424a4ff22dceae5adfa04ecb69b24da6fe57 | Python | 7,887 | 193 | """Cao et al. (2019) sustained-attention driving dataset access layer.
Cao, Z. et al. "Multi-channel EEG recordings during a sustained-attention
driving task", Scientific Data 6:19 (2019), figshare 10.6084/m9.figshare.6427334
(CC BY 4.0). Twenty-seven participants, sixty-two sessions, 30-channel EEG at
500 Hz in EEGLA... |
c2d3fd4a6327f7f1718ba3054290db54566444041a66c54c5473ceb3d7159215 | Python | 7,889 | 252 |
import os
import json
import torch
import optuna
import pandas as pd
from logits import (
AttentiveNet,
GATNet,
GINet,
MPNNet
)
from attentive import AttentiveMod
from gat import GATMod
from gin import GINMod
from mpnn import MPNNMod
def load_data(file_path):
df = pd.read... |
1f57e6d7a4e447bee6765d2b782b6d051868777e97ae09a37c59ba3f38f7d35d | Python | 7,890 | 246 | import os
import numpy as np
import pytest
pytest.importorskip("fabio")
pytest.importorskip("PySide6")
from musclex.utils import file_manager
class _ImmediateFuture:
def __init__(self, value):
self._value = value
def result(self):
return self._value
class _ImmediatePool:
def __init__... |
91b72de8205b1a7fc7b36fb7e6c633496e5424e20d417f3cac8cacd03d6cfb16 | Python | 7,891 | 181 | """Attach the matches ROICaT declined, when position alone settles them.
ROICaT clusters on footprint similarity and is conservative about it. Audited
over the Mecp2 run (93 chains): for every tracked cell and every day it was
missing from, what sat at its expected position in that day's ROIs?
=======================... |
80eb9deb69f2be6db651ec1aab572b2e876d72cbbf2f9ea719b11eb3351f3d3f | Python | 7,892 | 197 | import sys
import math
import os
from PyQt5 import QtWidgets, QtGui, QtCore
class ImageWidget(QtWidgets.QWidget):
# Signal to communicate updated center coordinates (as text)
centerChanged = QtCore.pyqtSignal(str)
def __init__(self, image_path, parent=None):
super().__init__(parent)
# Set... |
4dc85e45a90f71f52b0069e4e2f3d1078c1f5f170ab7527e3d6e1f1ef1feaf36 | Python | 7,895 | 237 | # FetMRQC: Quality control for fetal brain MRI
#
# Copyright 2023 Medical Image Analysis Laboratory (MIAL)
#
# 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/licens... |
8bacfd1c664b18d96cc41ad7b4374b8c5c5b1fb480ecdd53a5bbfa071cfde9cc | Python | 7,896 | 183 | #!/usr/bin/env python
# author: Jannes Spangenberg
# github: https://github.com/JannesSP
# website: https://jannessp.github.io
import pandas as pd
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, Namespace
def parse() -> Namespace:
parser = ArgumentParser(
formatter_class=ArgumentDefaul... |
7ae36fdb85e7fe65436731ac140951d3f13cb6bce205c677bc12a239dd75663c | Python | 7,897 | 244 | import torch
import torch.nn as nn
from .base import WaveformModel, WaveformPipeline
class DeepPhasePick(WaveformPipeline):
"""
Note: ...
"""
# TODO: update
def __init__(
self,
in_channels=3,
classes=3,
phases=None,
sampling_rate=100,
pred_sample=... |
8fccd78e22870e5578ef596447fb193f60e42e77858a3b000f87c1426a2a27eb | Python | 7,897 | 96 | from brainscore_core import Metric
from brainscore_vision import load_metric, Ceiling, load_ceiling, load_dataset
from brainscore_vision.benchmark_helpers.neural_common import NeuralBenchmark, average_repetition, apply_keep_attrs
from brainscore_vision.model_helpers.brain_transformation.temporal import assembly_time_a... |
15814ad5408089112435de386eec8bd838fccd28bad93e28a618e75767906cff | Python | 7,899 | 182 | import pytest
pytest.importorskip("fireants_fused_ops")
import torch
from time import time
from fireants.losses.cc import LocalNormalizedCrossCorrelationLoss
from fireants.tests.cc_mem_test import fast_lncc
from fireants.losses.fusedcc import FusedLocalNormalizedCrossCorrelationLoss
# from fused_ops.ops.fusedcc import... |
3ce3ebe8b5ae2247660a0010c6d23a757e6861f418949a06a5ae448c0ff362d3 | Python | 7,899 | 221 | import fcn_megfmri
import numpy as np
import pandas as pd
import seaborn as sns
import scipy.stats as stats
import matplotlib.pyplot as plt
# get custom colormaps
cmap_seq, cmap_seq_r, megcmap, megcmap2, categ_cmap = fcn_megfmri.make_colormaps()
plt.rcParams['svg.fonttype'] = 'none'
plt.rcParams['font.sans-serif'] =... |
9a6e0cbd728454b4d4edfde46f9042bb7f3167b78da87f14bda64db2b486bc79 | Python | 7,902 | 191 | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from ultralytics.utils import SETTINGS, TESTS_RUNNING
from ultralytics.utils.torch_utils import model_info_for_loggers
try:
assert not TESTS_RUNNING # do not log pytest
assert SETTINGS["wandb"] is True # verify integration is enabled
im... |
7500a31f718ed9baa7e7ace7e287e5d43894b33b2741ea4a34b322ab8d1bd3b8 | Python | 7,903 | 280 | #!/usr/bin/env python
"""
This parses a log file series (i.e. log, log.1, log.2, etc..) and
outputs timing and call frequency information for HAL messages.
Hazen 5/18
"""
from datetime import datetime
import os
pattern = '%Y-%m-%d %H:%M:%S,%f'
class Message(object):
"""
Storage for the timing of a single m... |
9eedb2b7b4df2a53db91f7dfbb0964527aa3f80be52b38caf41681445818cb60 | Python | 7,903 | 224 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
import re
from unittest.mock import MagicMock, patch
from allauth.account.models import EmailAddress
from django.core import mail
from django.test import override_settings
from django.urls import re_path, reverse
from django.views.generic import Red... |
801d1e158f49530a6d282ba6d4ceaed3bd599819ea0de3781168b5a67926ce7f | Python | 7,904 | 250 | class SetConv(torch.nn.Module):
def __init__(self, nb_feat_in, nb_feat_out):
super(SetConv, self).__init__()
self.fc1 = torch.nn.Conv2d(nb_feat_in+2, nb_feat_out, 1, bias=False)
self.bn1 = torch.nn.InstanceNorm2d(nb_feat_out, affine=True)
self.fc2 = torch.nn.Conv2d(nb_feat_out, nb_... |
6c2faa1fb3cd0578c1dde16df81e317cc749a7c74f0f7d9b2b092087e35beacf | Python | 7,905 | 229 | import numpy as np
import soundfile as sf
import matplotlib.pyplot as plt
import tkinter as tk
from tkinter import filedialog
from tkinter import ttk
class WaveViewer:
"""
Class to load audio files and visualize them in time and frequency domains.
"""
def __init__(self, audio_path: str, channel_mode: s... |
41a68f1e9ad43c1026d81526b03e1248bdda06dcec9a7d0d70c528e5ac910a8a | Python | 7,908 | 213 | import numpy as np
from sklearn.base import BaseEstimator
from .alignment import ProcrustesAlignment
from .kernels import compute_affinity
from .embedding import PCAMaps, LaplacianEigenmaps, DiffusionMaps
def _fit_one(x, app, kernel, n_components, random_state, gamma=None,
sparsity=0.9, **kwargs):
... |
5919688a0fd0b1fef16050f0d4b45dcd4f3dfe429f4259ec4ef4980306a56cfd | Python | 7,908 | 214 | import torch
import numpy as np
import pandas as pd
from tqdm import tqdm
from datetime import datetime as dt
from dataset_tool import fast_merge,df_to_mask
import os
print('loading raw data')
node=pd.read_json("../datasets/cresci-2015/node.json")
edge=pd.read_csv("../datasets/cresci-2015/edge.csv")
label=pd.read_csv(... |
005bc8d98cbda49fb1a1d51474245884e0a333d8d18cbe82b8d68cb0a5b1da7b | Python | 7,909 | 196 | '''ResNet in PyTorch.
For Pre-activation ResNet, see 'preact_resnet.py'.
Reference:
[1] Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun
Deep Residual Learning for Image Recognition. arXiv:1512.03385
'''
'''
Code from https://github.com/kuangliu/pytorch-cifar
'''
# resnet18 adaptpooling 1x4
import torch
import t... |
1b432acab05cbc9e4876a9f622c8c0470911601a6d1bc439b0daff8d0b61eb1f | Python | 7,912 | 196 | import torch
from torch import nn
from eir.models.input.array.models_cnn import CNNResidualBlock
from eir.models.layers.mlp_layers import MLPResidualBlock
from eir.models.layers.projection_layers import get_1d_projection_layer
from eir.models.tensor_broker.projection_modules.cnn import (
get_conv_params_for_dimens... |
a1e975ef008602c0dc11e05cda4942e07abf2e2be14a63e673b77a197b35cf57 | Python | 7,913 | 191 | import torch
import torch.nn as nn
from torch.hub import load_state_dict_from_url
from typing import Union, List, Dict, Any, cast
__all__ = [
'VGG', 'vgg11', 'vgg11_bn', 'vgg13', 'vgg13_bn', 'vgg16', 'vgg16_bn',
'vgg19_bn', 'vgg19',
]
model_urls = {
'vgg11': 'https://download.pytorch.org/models/vgg11-8a... |
ac9d86b16dffbae9d0ef266e8bcdef263c5a405bc0561fe46c348e5e7497fc5e | Python | 7,916 | 245 | #!/usr/bin/env python
"""Smoke test for ParslBackend on an HPC compute node.
Must run **inside** a PBS interactive allocation on Polaris or Aurora::
# Polaris
qsub -I -A <proj> -l select=1 -l walltime=01:00:00 -q debug
# Aurora
qsub -I -A <proj> -l select=1,walltime=01:00:00 -q debug -l filesystems=ho... |
150254f0dd087c021ccba1adfcd747c4bc42a9ed1889ae76ec792b7d13fb1ba7 | Python | 7,918 | 284 | from copy import deepcopy
from typing import TYPE_CHECKING
from unittest.mock import create_autospec
import pytest
import torch
from eir.setup.input_setup_modules.torchtext_port.vocab import Vocab
from eir.train_utils.evaluation_modules.evaluation_handlers_utils import decode_tokens
from eir.train_utils.evaluation_mo... |
aee5baf60f06216bceb6cbb528ce29d9fee0ecfd25ad02817eee6fc5e6437d27 | Python | 7,919 | 195 | # -*- coding: utf-8 -*-
"""
Functions to gather iamge statistics in large volumetric images
The main routines extract information from a large volumetric image, such as
the maximum or mean.
"""
#:copyright: Copyright 2015 by Christoph Kirst, The Rockefeller University, New York City
#:license: GNU, see LICENSE.txt fo... |
3a6014388d8e1cf92654c6931d523a3f036ed98f00f61c15a67d1a0ae5d8598d | Python | 7,920 | 216 | import sys, os, subprocess, argparse, time
import numpy as np
import util, slurm
def task(cmd, jobnum=False, timeout=None, run=True):
print(cmd)
if run:
result = subprocess.run(cmd, timeout=timeout, capture_output=True, encoding='utf-8', shell=True)
print(result.stdout)
if jobnum:
... |
9492a6a15efe88050de555ec8fc2af9d8ade5bf6208e4098cd4b032a57be46d2 | Python | 7,921 | 223 | import torch
import torchvision
from torch import Tensor
import torch.nn as nn
import math
import numpy as np
import torch.nn.functional as F
from torch.hub import load_state_dict_from_url
from .functions import ReverseLayerF
class ResNet10(torchvision.models.resnet.ResNet):
def __init__(self, track_bn=True):
... |
b45b94699ceba8c58629672cf5d81373eb193016bfa020a56c501d709ba7010d | Python | 7,921 | 221 | import numpy as np
from scipy.spatial.transform import Rotation
from scipy.interpolate import RBFInterpolator
from sklearn.kernel_approximation import Nystroem # Nyström 近似
from sklearn.neighbors import NearestNeighbors
def kernel_interpolate(
Y, # (N, D) target points
y, # (M, D) source points
... |
196d603c69ce6be3ed739fb8a8edc7d5031d213b2a7c9b082e0c867c05f9ad65 | Python | 7,923 | 237 | """GLM Permutations base class."""
import logging
from typing import Dict, Optional
import numpy as np
from scipy import stats
from pqdm.processes import pqdm
from tqdm.auto import trange
from osl_dynamics.glm.base import Design, GLM
from osl_dynamics.glm.ols import osl_fit
_logger = logging.getLogger("osl-dynamics... |
1a4296f6dc76da3bcb1775b12156fe4a3ef1768b5d381a4855753559117b549c | Python | 7,924 | 182 | import numpy as np
import matplotlib.pyplot as plt
import OptimalBattery.evaluate as ev
import Functional_Fusion.atlas_map as am
import OptimalBattery.util as ut
import OptimalBattery.construct as ct
from scipy.optimize import brentq
from Functional_Fusion.dataset import DataSetLanguage
from scipy.stats import ttest_re... |
98d3503e5e1f515b896585014a70dfccb758232c9dcda7b2d323511af0a7749b | Python | 7,925 | 185 | import argparse
import json
import warnings
import torch
import os
import sys
import yaml
import numpy as np
import pandas as pd
from torch import nn
from torch_geometric.loader import DataLoader
from numpy import nan
from typing import *
from tqdm import tqdm
from scipy.stats import spearmanr
from transformers import ... |
66eb3bced49098c57212b6a4f31238ae3cc4f7886db51d319614fabdbda8ac34 | Python | 7,927 | 225 | '''
C3H7NO
'''
import numpy as np
import sys
def intro():
print("""
SHORT List of potential energy surfaces for C3H7NO:
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... |
c5f835ad7c3a95004a73b03cc5b4d43c051314f89163165205f9aeb9ff8f880c | Python | 7,927 | 156 | ## ------------------------------------------------------------
## IMPORTS
## ------------------------------------------------------------
import torch
import torch.nn as nn
from LSTMConvCell import *
# Phase Embed Dynamic
class PhaseDecoder(nn.Module):
def __init__(self, gpu_id, ch_mult):
super(PhaseDeco... |
7e7fdd9694547e9e0306f02c9fdc72dca69cc677b0777f43415f44d094cccc40 | Python | 7,930 | 138 | import os
class PipelineManager:
def get_pipeline(self, pipeline_name, subject, session=None, output_path=None, **kwargs):
"""
Retrieve an instance of the specified pipeline.
:param pipeline_name: str, pipeline name
:param subject: BIDSSubject instance
:param session: option... |
4c2e2b234f7dc79e24ad50175eade2565b877dec48f1449c74908562b0ee508f | Python | 7,937 | 184 | #!/usr/bin/env python
# author: Jannes Spangenberg
# e-mail: jannes.spangenberg@uni-jena.de
# github: https://github.com/JannesSP
# website: https://jannessp.github.io
import pandas as pd
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, Namespace
def parse() -> Namespace:
parser = ArgumentParse... |
0b7345c856d6b644d9bc6c2a90c728411a0ac34cab44133ad4337d528b12ce29 | Python | 7,938 | 225 | # 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
# distributed under th... |
3654c1080d4ae4a8f94f405fe526259351d6f3a49ce40c21b2c79df1c35cf6b0 | Python | 7,940 | 236 | import matplotlib.pyplot as plt
import numpy as np
try:
from rsatoolbox.vis.colors import rdm_colormap_classic
except:
print('[WARNING] rsatoolbox is not installed')
try:
from nilearn import masking
from nilearn import image, plotting
except:
print('[WARNING] nilearn is not installed')
try:
impo... |
daddec26ff33da33d7cc0ed088c7852802b0c18ca599d6fcbdf2c544fb9c2e24 | Python | 7,941 | 223 | import torch
import tifffile
import pandas as pd
import numpy as np
import os
def process_boxes(input_df, tif_path,marker='marker', device=None):
"""
Process bounding boxes to calculate min and std of expanded regions in a 16-bit TIFF image.
Args:
input_df (pd.DataFrame): DataFrame containing ... |
3e78a56b54e8ebadaee0c0f132aee35364b920af4e195a9bba991d5553d820d0 | Python | 7,942 | 191 | """ Methods for correcting for signal drift. """
import numpy as np
import json
from ivim.io.base import data_from_file, file_from_data, read_im
def temporal(im_file: str, bval_file: str, outbase: str, roi_file: str | None = None, order: int = 2, ctm: str = 'mean', voxelwise: bool = False) -> None:
"""
Correc... |
5780fcd2dff44fbbd634ec72089c13f75d16d4db93892121f81bad88c39da9b2 | Python | 7,944 | 242 | #!/usr/bin/env python3
import argparse
import re
from pathlib import Path
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
SAMPLE_COL = "Sample"
LEFT_COL = "LeftBreakpoint"
RIGHT_COL = "RightBreakpoint"
def safe_name(s):
"""Sanitize a string for safe use in filenames.
Replaces char... |
c37282302a0204ce3bc8e1f85d40857d6cd941589260477c83be06c18ba4e950 | Python | 7,946 | 190 | #! /usr/bin/env python
"""Measure intra-surface distances and optionally verticality for a pycurv-generated triangle graph file.
Usage: python intradistance_verticality.py file.gt [options]
"""
__author__ = "Benjamin Barad"
__email__ = "benjamin.barad@gmail.com"
__license__ = "GPLv3"
import click
import vtk
import n... |
9f7d91020f00a87694b4331c5f2eaa7475a81242247ed097daec52de67b79723 | Python | 7,947 | 237 | """
Tests for deepreg/dataset/preprocess.py in
pytest style
Some internals of the _gen_transform, _transform and
transform function, such as:
- layer_util.random_transform_generator
- layer_util.warp_grid
- layer_util.resample
Are assumed working, and are tested separately in
test_layer_util.py; as such we... |
da870e70c975591f7aa4523bc3e384a345d4f1fe72fd21cb9657bfc5b37542e4 | Python | 7,948 | 243 | """
Core data classes and ``FitterAdapter`` protocol for the A/B framework.
The schema is intentionally **library-agnostic**: a ``FitCase`` is a pure
Python + NumPy snapshot of one fit invocation, plus a frozen reference
result. Any adapter (lmfit/scipy/VarPro/iminuit/...) can replay it without
touching the original `... |
5ff901b3ec399bcf781bd848f5484a2080564c12acebe40027b8f1e0853ff6fa | Python | 7,949 | 203 | import os
import os.path as op
import sys
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.patches as patches
from matplotlib.gridspec import GridSpec
import matplotlib.image as mpimg
from matplotlib.offsetbox import OffsetImage, AnnotationBbox
import seaborn as sns
from eelbrain... |
e5a0935e473d78709c506ae6d9aebd09deb997372e14254f3706534e6326a3cd | Python | 7,949 | 212 | import sys
import yaml
import os
import numpy as np
import h5py
pathpath,myrun,ncluststr,cmethod = sys.argv[1:]
"""
pathpath = 'PATHS/filepaths_carlen.yml'
myrun = 'runC00dMP3_brain'
cmethod = 'ward'
ncluststr = '8'#
"""
with open(pathpath, 'r') as myfile: pathdict = yaml.safe_load(myfile)
sys.path.append(pathdict... |
7b9ab0c4d852506955a57500e4f9d5d2077d53e829c9596e49a14775f6a4eeee | Python | 7,953 | 259 | """Morphology loading and coordinate-to-volume transformation.
SWC is whitespace-delimited but writers disagree on which whitespace: the
Allen files use a single space, while MorphIO (v3.3.3 was the version reported
in issue #8) pads its columns so runs of spaces separate the fields. Splitting
on a literal single spac... |
9e4b17e5df61a1862fc9f601707a5c3bd567c4ccb35d0bff9590b31d47f924e0 | Python | 7,953 | 202 | # 1. link prediction. negative pair and positive pair prediction
# 2. prediction result see the correlation pearson and spearman
#remember that need to down sample to equal instance
from gensim.models.keyedvectors import KeyedVectors
import argparse
import random
import numpy as np
from sklearn import linear_model ... |
b4a52a27443b5b9a4c9ffc0d9250f4ec134a41875fafe3acaf1fc5f2682bf90d | Python | 7,953 | 198 | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved
"""Various utility models."""
from __future__ import annotations
import math
import numpy as np
import torch
from torch import Tensor, nn
class DotProductScoring(torch.nn.M... |
f9e3f3fdd9750074b48bf43d10ac497bb2bd08a6ef9eec172a7670bf799e5a00 | Python | 7,953 | 211 | # script to load the trained model
# first, evaluates on the validation and full test set
# then evaluates on the validation and test_pred.txt
# finally predicts for test_pred.txt
# to double check with performances seen during training if all loaded correctly
import os
import sys
import pprint
import torch
from torc... |
e5a6fa57f9c458d272696216c1fa402038ce96f559a1bc4a31da24c6884319f1 | Python | 7,954 | 231 | # -*- coding: utf-8 -*-
# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
# vi: set ft=python sts=4 ts=4 sw=4 et:
"""This module provides interfaces for workbench surface commands"""
import os
from nipype.interfaces.base import TraitedSpec, File, traits, CommandLineInputSpec
from nipype.interfa... |
3b9d97099d76bb5f39b544719dc9e416fb100eea59e84b61d56c27904920e195 | Python | 7,956 | 265 | """Brain-Score wrapper for DeepEISNN EI-SNN CIFAR10 VGG19."""
from __future__ import annotations
import functools
import json
import sys
from collections import OrderedDict
from pathlib import Path
from typing import Any, Iterable
import numpy as np
if not hasattr(np, "int"):
np.int = np.int32
import torch
fro... |
03ac88d2abd7db8380202a324516e5fa09f7dd30307b553337cf012e4546c683 | Python | 7,958 | 292 | # Copyright (c) DP Technology.
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import bisect
import time
from collections import OrderedDict
from typing import Dict, Optional
try:
impo... |
e9a8236d4c87313cc2bcbabbcb8970447e57263916c3095987e88c8a187e7050 | Python | 7,959 | 233 | """ Generating structure graphs for graph convolutional neural networks """
import os
import argparse
from os.path import isfile
from enum import Enum, auto
import numpy as np
from scipy.spatial.distance import cdist
import networkx as nx
from biopandas.pdb import PandasPdb
import constants
import utils
class GraphT... |
e9d016afe68b1650adc3683015965d464bcae56e554283d829a4249dfa0f0136 | Python | 7,961 | 185 | import os
import Bio
import Bio.AlignIO
import numpy as np
import math
import torch
import seaborn as sns
import matplotlib.pyplot as plt
import pandas as pd
#对每一个序列进行PSSM打分
def pssm(proseq,outdir):
# 一个命令函数，依据pdb文件。使用blast生成pssm文件
def command_pssm(content, output_file, pssm_file):
os.system('psiblast \... |
9f72a0f441b0feeb6425f2254d0d9f65f70c316bde66e78c3cece6fcedff7457 | Python | 7,964 | 182 | import numpy as np
import librosa
from scipy import signal
def preemphasis(wav, k, preemphasize=True):
if preemphasize:
return signal.lfilter([1, -k], [1], wav)
return wav
def inv_preemphasis(wav, k, inv_preemphasize=True):
if inv_preemphasize:
return signal.lfilter([1], [1, -k], wav)
... |
af82b52d696e8d0fe073410134beeef32a342b66abb048761a955ddc942909ef | Python | 7,964 | 221 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Jun 21 18:51:41 2024
@author: costantino_ai
"""
# Imports necessary libraries
import os
import logging
from pathlib import Path
import numpy as np
from scipy.io import loadmat
from brainscore_core.supported_data_standards.brainio.assemblies import Neu... |
d846774bd213aa5ada75597a79c068fc9769f31e246311defa174edb2e6d37d4 | Python | 7,964 | 132 | import json
import numpy as np
from copy import deepcopy
from napari_dmc_brainmap.registration.sharpy_track.sharpy_track.model.calculation import fitGeoTrans, mapPointTransform
from napari_dmc_brainmap.registration.sharpy_track.sharpy_track.view.TreRow import TreRow
class MeasurementHandler:
def __init__(self, mea... |
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