sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
d5e543e65210a6ee5d59a918a5b407c966e206423f205ba70ba65b7ceb00b940 | Python | 1,889 | 45 | import numpy as np
from pytorch_grad_cam.base_cam import BaseCAM
"""Feature Explanation Method.
Fuad, K. A. A., Martin, P. E., Giot, R., Bourqui, R., Benois-Pineau, J., & Zemmari, A. (2020, November). Features understanding in 3D CNNS for actions recognition in video. In 2020 Tenth International Conference on Imag... |
145b7e3637bb7493c40ae1524e0375252f662b7832c7d29797b3e904a31f27a1 | Python | 1,890 | 39 | # Copyright 2020 Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany
#
# 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://w... |
92c9c06e7ce576dbe468a65eb94344753f7bf608fdfd008ccb88a69fa4cce38b | Python | 1,890 | 55 | """Command-line interface to print specified GO Terms from the DAG source
Usage:
goatools prt_terms [GO ...] [GO_FILE]
goatools prt_terms [GO ...] [GO_FILE] [options]
Options:
-h --help show this help message and exit
-i <file.txt>, --ifile=<sections_in.txt> Read or Write fil... |
4a5746b8837eef2722b66301ed6d9242127a74dafd99515458c2127d9a99ba29 | Python | 1,891 | 67 | # Copyright 2022 InstaDeep Ltd
#
# Licensed under the Creative Commons BY-NC-SA 4.0 License (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://creativecommons.org/licenses/by-nc-sa/4.0/
#
# Unless required by applicable law or a... |
b63272a6c01c12ac4f2dae40ed857403471280681f326eb36f7ef8ce503d3ad8 | Python | 1,893 | 77 | import numpy as np
from pytest import approx
import novae
from novae.monitor.eval import _jensen_shannon_divergence, entropy
from ._utils import adata_concat, adatas
true_distributions = np.array([
[0.2] * 5,
[0.4, 0.4, 0.2, 0, 0],
[0.75, 0.25, 0, 0, 0],
])
true_jsd = _jensen_shannon_divergence(true_dis... |
0caab7d19abf77a87a57edd7f2078842d3afe99fe01dc21007cdd1e3de6b8889 | Python | 1,894 | 63 | import cv2
import math
import random
import numpy as np
import os
def Show_Heatmap(beta, img=None):#(100, 100, 3, 25)
cv2.namedWindow('img')
cv2.namedWindow('img1')
if img is None:
img = cv2.imread(os.path.join("VOCdevkit\VOC2007\JPEGImages/000001.jpg"), 1) # the same input image
h,w,c = img.s... |
38687ef2ff063038319638f917d5d9729cd1f25e60d79b7dc3b0a896cde50692 | Python | 1,894 | 56 | import numpy as np
def Ent_Samp(data, m, r):
"""
function SE = Ent_Samp20200723(data,m,r)
SE = Ent_Samp20200723(data,m,R) Returns the sample entropy value.
inputs - data, single column time seres
- m, length of vectors to be compared
- r, radius for accepting matches (as a proportion of the... |
c54db1a1a9781f38ecafc6ffbc915e1387f2855ed2f758d7f083e9c74afc514b | Python | 1,894 | 60 | import unittest
from unittest.mock import patch
from pyecharts import options as opts
from pyecharts.charts import TreeMap
example_data = [
{"value": 40, "name": "我是A"},
{
"value": 180,
"name": "我是B",
"children": [
{
"value": 76,
"name": "我是B... |
08e39ff332df126a40811bb0d52bdbd38b8a47afb2218987ebac0781092f5b38 | Python | 1,895 | 65 | import numpy as np
import loompy
import numpy_groupies as npg
class Enrichment:
"""
Compute gene enrichment across clusters on already aggregated data
"""
def __init__(self) -> None:
self.nonzeros = None
def fit(self, dsout: loompy.LoomConnection, ds: loompy.LoomConnection) -> np.ndarray:
"""
Compute gene... |
5dfba375237d67a985f5333912757133779a10a8c9efa80a1433054d3e7916b0 | Python | 1,898 | 64 | import lucent
from setuptools import setup, find_packages
version = lucent.__version__
with open("README.md", "r") as fh:
long_description = fh.read()
setup(
name="torch-lucent",
packages=find_packages(exclude=[]),
version=version,
description=(
"Lucid for PyTorch. "
"Collection o... |
a742cb26c4bec9291c7249ecff97f5df424ba7e027b51ad4b301aa15b57de0a7 | Python | 1,898 | 29 | from predify.modules import PCoderN
from predify.networks import PNetSeparateHP
from torch.nn import Sequential, ReLU, ConvTranspose2d
class PVGG16SeparateHP(PNetSeparateHP):
def __init__(self, backbone, build_graph=False, random_init=False, ff_multiplier=(0.35,0.4), fb_multiplier=(0.25,0.4), er_multiplier=(0.01,0... |
cf4ef002a16f2692b4ecd991748fe0ec49100aa0e1f0885de3f0a9336146cb38 | Python | 1,898 | 57 | from __future__ import annotations
import sys
from typing import TYPE_CHECKING
from poetry.core.constraints.version import Version
from poetry.utils.env.python.providers import PoetryPythonPathProvider
from poetry.utils.env.python.providers import ShutilWhichPythonProvider
if TYPE_CHECKING:
from tests.types i... |
871a75c652b3f1ab1aed21ab6ce74bb5bf51f252e84dceabd9dd5419d25726e1 | Python | 1,899 | 51 | import os.path
import pandas as pd
os.chdir('../SCAD/')
## GDSC drug log IC50 and binarized repsonse information extraction. The following processing step refer to:
## https://github.com/hosseinshn/MOLI/blob/master/preprocessing_scr/annotations.ipynb
# Download the following three files in data response folder
## ht... |
0d9ac33e74973337c413449cfe1581d744e5e4d3999931b9988f9e1361eb37aa | Python | 1,900 | 63 | import argparse
from pathlib import Path
import shutil
from utils.nsd_utils import NSDDataHandler
BUCKET = "natural-scenes-dataset"
ROOT = "nsddata_timeseries/ppdata"
NIFTI_REL_PATH = 'func1pt8mm/timeseries'
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument(
"--no-encoding", a... |
f9d36137edbb60018c460cfba532e97c0fcf05b7f4197f22c4d3363e49528e4b | Python | 1,900 | 61 | from typing import List
import numpy as np
from fairseq.data.audio.dataset_transforms import (
AudioDatasetTransform,
register_audio_dataset_transform,
)
_DEFAULTS = {"rate": 0.25, "max_tokens": 3000, "attempts": 5}
@register_audio_dataset_transform("concataugment")
class ConcatAugment(AudioDatasetTransform... |
27df2f9327834e8ad3568af615e539965d69533f93f0c3e405748108ff6cd759 | Python | 1,901 | 56 | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
import fairseq
import soundfile as sf
class Wav2VecFeatureReader:
"""
Wrapper class to run inference on Wav2Vec 2.0 mod... |
163240a2d95ef0ddba0d551d59e8e7071773aeeb3b1618e800a259bbc4bfca0f | Python | 1,903 | 41 | #!/usr/bin/env python3
import polars as pl
import sys
import argparse
def main():
parser = argparse.ArgumentParser("Filter for reads for PITA analysis")
parser.add_argument("--final_classification", action="store", type=str, required=True)
parser.add_argument("--orfanage_gtf", action="store", type=str, req... |
7e2b6e8df2d2feb40e9d6459764e5302cb342ab1de5d062b5c4602cd9a70cea8 | Python | 1,903 | 44 | #!/usr/bin/env python3
# MIT License
#
# Copyright 2024 Broad Institute
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to u... |
999064308beb34599e95cc63ef54efe7511e14c95a4a4450e0b3b41ac115a907 | Python | 1,903 | 70 | from scvi.utils import error_on_missing_dependencies
from ._callbacks import (
LoudEarlyStopping,
SaveCheckpoint,
ScibCallback,
)
from ._config import (
AdversarialTrainingPlanConfig,
ClassifierTrainingPlanConfig,
KwargsConfig,
LowLevelPyroTrainingPlanConfig,
PyroTrainingPlanConfig,
... |
6723216bc5f1ddb69c4e31cf60652b439be9cecf5b348e2dc21a53630e4dd26e | Python | 1,904 | 55 | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
from examples.textless_nlp.gslm.unit2speech.tacotron2.model import Tacotron2
from examples.textless_nlp.gslm.unit2speech.tacotro... |
ed2ed29922b5bc3ba06518b225f515257307ce9f9fb1590ec18b9ea35fb864f5 | Python | 1,904 | 58 | """
This module contains the ValveMapWidget, that is used in the UI.
"""
"""
Copyright (c) 2019, 2022 [copyright holders here]
This file is part of NoSeMaze.
NoSeMaze is free software: you can redistribute it and/or
modify it under the terms of GNU General Public License as
published by the Free Software Foundation... |
1f08bb7b004751f8c9e215d58d0408387701f7de648a87bb5e047fa55c33bfab | Python | 1,905 | 62 | # 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 random
from typing import List
from fairseq.data import BaseWrapperDataset, data_utils
class RandomInputDataset(BaseWrapperDataset):... |
7b8c68e98c2c13519f92722454bb6fe2931a9450d1f70cd9a4d66636207945d2 | Python | 1,905 | 53 | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import argparse
import sys
from typing import Callable, TypeVar, cast
from omegaconf import OmegaConf
R = TypeVar("R")
def get_config(argv: list[str] | None, config_cls: Callable[..., R]) -> R:
"""
Utility function to get OmegaConf co... |
bf7f291e4655535303f5e770761080861f00009439c0b2a3349230e3f6751e04 | Python | 1,905 | 57 | # scSGL - a python package for fene regulatory network inference using graph signal processing based
# signed graph learning
# Copyright (C) 2021 Abdullah Karaaslanli <evdilak@gmail.com>
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as pu... |
d0920fc6a351838339a3820835afce3e3831b836eb600dc8c6e4d0fd872647c0 | Python | 1,905 | 59 | from utils import MOUSE
from config import TrainConfig
from utils.choices import GenerativeType, ModelName
def prep_config_parm(pth, bat,
size, gpus,
stain, mouse,
nrna, srna=4,
method='ours',
is_test=False):
... |
26d6886768b943fc974fc112036b276eba60ec05593ada66142ef7614311ee9d | Python | 1,906 | 55 | """Run DeepLabCut fin tracking over a folder of videos.
One-time preprocessing step requiring a GPU and the `dlc` optional extra
(`uv sync --extra dlc`). Writes the pose `.h5`/`.csv` files (and optional labelled
videos) that `notebooks/02_fin_tracking` consumes.
Example:
python dlc/analyze_videos.py /path/to/vide... |
730bef6a56201b2812302cd1b89d2c7bc00169e6c80c5bfdea04298c806373af | Python | 1,908 | 61 | """Class that represents dataset table in configuration file."""
from __future__ import annotations
import pathlib
import attr.validators
from attr import asdict, define, field
from ..common.converters import expanded_user_path
@define
class DatasetConfig:
"""Class that represents dataset table in configurati... |
e7b5e3d9992e7d5141407d121b566588d5f2f561f5f235202a02384f48390643 | Python | 1,909 | 62 | """End-to-end smoke test of the sklearn surface on tiny synthetic data."""
import logging
import numpy as np
import pytest
from aestetik import AESTETIK
@pytest.mark.slow
def test_fit_transform_predict_smoke(small_adata):
"""fit -> transform -> predict on a tiny 6x6 grid, single epoch.
We don't check learn... |
e8ab0ff9f7026e1c13eb18e71b59ce6a44d1d9ea3dc9dca2a40faa418d31a303 | Python | 1,910 | 55 | import numpy as np
import pandas as pd
import pytest
from sklearn.utils.estimator_checks import parametrize_with_checks
from pgmpy.causal_discovery.TOPIC import TOPIC
@pytest.fixture
def linear_non_gaussian_data():
rng = np.random.default_rng(0)
n = 2000
A = rng.laplace(0.0, 1.0, n)
B = 1.5 * A + rng... |
263d3aa67b2219f2376ab8a3546df5cc6cc301ceb27e8e9d992bfc3ba22bb270 | Python | 1,911 | 70 | #!/usr/bin/env python
# Author_and_contribution: Niklas Mueller-Boetticher; created script
import argparse
parser = argparse.ArgumentParser(description="Calculate V-measure (scikit-learn)")
parser.add_argument(
"-l", "--labels", help="Labels from domain clustering.", required=True
)
parser.add_argument("-g", "-... |
2b62f35c08079f41291b6b9eff8cb3c9a5e15f036b752d09f27dd665b6499b47 | Python | 1,911 | 65 | from os.path import join
import pandas as pd
from matplotlib import pyplot as plt
# chr pos type
input_dir = '../../data/prostate/input/final/'
# output_dir= './processed'
output_dir = '../../data/prostate/processed'
# filename = 'P1000_final_analysis_set.maf'
filename = 'P1013_Clinical_Annotations_MAF.txt'
df = pd... |
5791d4880e9bfd553a6890c30ffe35e5520f40274a82746a3570e5fbb8513716 | Python | 1,911 | 69 | #!/usr/bin/env -S uv run
# /// script
# requires-python = ">=3.11"
# dependencies = [
# "tensorstore",
# ]
# ///
import json
import os
import pathlib
import shutil
import tensorstore as ts
def write_multiscale(
path, include_top_level_scales: bool, include_per_scale_downsampling_factors: bool
):
shutil.r... |
95bc7b3d979e5c720d42124ade5c9c8cf610b16a02b50c1735d52e19a88406ef | Python | 1,913 | 54 | from st_risk.paths import (
current_results_dir,
ensure_results_layout,
resolve_results_file,
results_file,
run_dir,
set_selected_run,
)
def test_results_file_creates_nested_layout(tmp_path):
base = ensure_results_layout(tmp_path / "run")
target = results_file(base, "tables", "risk_tab... |
055b9ecf018dd6ef7b6e0966d8a454243188ba3123e35c18b5cd596133cfbce2 | Python | 1,914 | 70 | """
This module read the rfid tag of the mouse present at the port.
"""
"""
Copyright (c) 2019, 2022 [copyright holders here]
This file is part of NoSeMaze.
NoSeMaze is free software: you can redistribute it and/or
modify it under the terms of GNU General Public License as
published by the Free Software Foundation,... |
2f14f6c19d11ec4efbb41e780c6b8c0f751bc970997c7fb37db7a05061bc3bee | Python | 1,916 | 53 | import json
import os
import torch
import torch.nn as nn
from sentence_transformers import models
class PoolingWithDropout(nn.Module):
"""
A pooling layer with dropout applied to the sentence embedding.
Parameters
----------
word_embedding_dimension : int
The dimension of the word embeddin... |
39489138bb87a773509791a6b922974b533668be63fa3b8bafac825cf446dd94 | Python | 1,919 | 30 | from predify.modules import PCoderN
from predify.networks import PNetSeparateHP
from torch.nn import Sequential, ReLU, ConvTranspose2d
class PVGG16SeparateHP(PNetSeparateHP):
def __init__(self, backbone, build_graph=False, random_init=False, ff_multiplier=(0.35,0.4), fb_multiplier=(0.25,0.0), er_multiplier=(0.01,0... |
554d70e062c96bf7e6f2cb6c838f44641b7d9c3ed72d008061cde42537db6ea5 | Python | 1,919 | 63 | #!/usr/bin/env python
# Author_and_contribution: Niklas Mueller-Boetticher; created template
# Author_and_contribution: Kirti Biharie; implemented homogeneity score
import argparse
parser = argparse.ArgumentParser(description="Calculate Homogeneity Score (scikit-learn)")
parser.add_argument(
"-l", "--labels", h... |
f9ecf7fa67ea3864b98d157a0e61648be194af27ccb5326c5a8b81bd5395a722 | Python | 1,919 | 41 | from config import *
PATH_SOURCE = Path(__file__).parents[2]
sys.path.insert(0, str(PATH_SOURCE/Path('source')))
from field_computation import FieldComputation
from construct_model import construct_model
from model_train import train
# run as: python .\main.py hidden_layers neurons seed activation init_coeff
# for... |
63454197ac481e3ca9fc3bbd94037ccb5bb3d7e346e972b08827227b030c0b84 | Python | 1,920 | 57 | # -*- coding: utf-8 -*-
from setuptools import setup, find_packages
import os
def get_version():
directory = os.path.abspath(os.path.dirname(__file__))
init_file = os.path.join(directory, 'tape', '__init__.py')
with open(init_file) as f:
for line in f:
if line.startswith('__version__')... |
adaf058e8b8f1e49a632da60d81e6c786e35e632b5c193ada123bc58a80de25f | Python | 1,920 | 58 | import csv
import logging
import os
import anndata
import numpy as np
import pandas as pd
from scvi.data._download import _download
logger = logging.getLogger(__name__)
def _load_cortex(save_path: str = "data/") -> anndata.AnnData:
"""Loads cortex dataset."""
save_path = os.path.abspath(save_path)
url ... |
4f8b184619848adcd3a9f0f3fd3c50b0e53cd518666170c80d833c60852d7a9d | Python | 1,921 | 58 | # Copyright (c) Howto100M authors and Facebook, Inc. All Rights Reserved
import torch as th
from torch import nn
class GlobalAvgPool(nn.Module):
def __init__(self):
super(GlobalAvgPool, self).__init__()
def forward(self, x):
return th.mean(x, dim=[-2, -1])
def get_model(args):
assert ... |
5c9fd2f1abdc9d63a95bcbf7081919188e51e0911c4533e6659baa3ec6b53bd3 | Python | 1,922 | 63 | #!/usr/bin/env python
# Author_and_contribution: Niklas Mueller-Boetticher; created template
# Author_and_contribution: Kirti Biharie; implemented fmi score
import argparse
parser = argparse.ArgumentParser(description="Calculate Fowlkes-Mallows index (scikit-learn)")
parser.add_argument(
"-l", "--labels", help=... |
b518dbeabf2cf4289c94a606efa7c4c6c66d10e0a50709b5c6c57bef824905b5 | Python | 1,922 | 62 | import pytest
from mudata import MuData
from scvi.data import synthetic_iid
from scvi.external import METHYLVI
@pytest.mark.parametrize("dispersion", ["region", "region-cell"])
def test_methylvi_dispersion(dispersion: str):
adata1 = synthetic_iid()
adata1.layers["mc"] = adata1.X
adata1.layers["cov"] = ad... |
d7c874c11edfec50e60f4f22b5841239f8355ff58e30fcc39a66f7241663eb6c | Python | 1,922 | 63 | #!/usr/bin/env python
# Author_and_contribution: Niklas Mueller-Boetticher; created template
# Author_and_contribution: Kirti Biharie; implemented completeness score
import argparse
parser = argparse.ArgumentParser(description="Calculate Completeness Score (scikit-learn)")
parser.add_argument(
"-l", "--labels",... |
95a221675656a3274a98b9d8c073b08f016074275b6c50a40a4c2ec766b4f5aa | Python | 1,923 | 52 | import os
from pathlib import Path
import requests
from typing import Union
from moosez import constants
from moosez import system
def download_enhance_data(download_directory: Union[str, None], output_manager: system.OutputManager):
output_manager.log_update(f" - Downloading ENHANCE 1.6k data")
if not dow... |
b23f395022ef41c70714e6499bcea12ac54a042873f9d1ddbe6b8328e8f20aa4 | Python | 1,923 | 44 | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'scientific_number_scroller_widget.ui'
#
# Created by: PyQt5 UI code generator 5.10.1
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore, QtGui, QtWidgets
class Ui_ScientificScroller(object):
def setupUi(s... |
a19da848661704481f7b2e2ab0257dbddc8f6242df405252b0648b7c249d33f4 | Python | 1,926 | 63 | import subprocess
from multiprocessing import Pool
from typing import Any
from .config import BaseConfig
from .conversion import fasta_extraction
class mse_engine:
def __init__(self, config) -> None:
super().__init__(config)
self.sanity, self.ids, self.seqs = fasta_extraction(self.config.input_fa... |
fccc17529b2e6cb9d9573589f2f7e2b9ed2ef877771aee16ee89b6ff8f9c1490 | Python | 1,926 | 55 | # -*- coding: utf-8 -*-
"""
Generate synthetic data with the shape of the real recordings.
The ear-EEG recordings cannot be redistributed, so this produces files of the
same shape and dtype to verify that the pipeline runs end to end. The signals
are noise with a weak class-dependent oscillation, so accuracies are nea... |
0377bc5d24487320b06c0f878e505f5211a2594fc5a2942a831db5402eb1c4ef | Python | 1,927 | 63 | #!/usr/bin/env python3 -u
# 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.
"""
get intervals from .vads file, specify output data, and this script removes silences and saves the audio data in... |
1d91aa2b9029c4d033e934d9623ada761a854d4d795ce8fedccb3305f73a57fc | Python | 1,928 | 57 | # 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.
from .fairseq_encoder import FairseqEncoder
class CompositeEncoder(FairseqEncoder):
"""
A wrapper around a dictionary of :class:`Fai... |
6f4306583f8bfa9135410f707d722f4d00c81832c5223184d0223f8f41104fd7 | Python | 1,929 | 68 | import argparse
from pathlib import Path
import anndata
import numpy as np
import pandas as pd
from scipy.sparse import csr_matrix
def convert_to_h5ad(dataset_dir: Path):
res_path = dataset_dir / "adata.h5ad"
if res_path.exists():
print(f"File {res_path} already existing.")
return
regio... |
c6b0a73a6536511f0c6c7922c3087de8bbde40802f8f546bff94ed368b4956c7 | Python | 1,929 | 47 | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import numpy as np
from ase import Atoms
from ase.io import write
from mattersim.applications.batch_relax import BatchRelaxer
from mattersim.forcefield.potential import Potential
from mattersim.utils.logger_utils import get_logger
from pymatgen.c... |
9c99ed0e17e1f7b010a57100c249142cc2a702405dc47399d0982f3364f11a8a | Python | 1,930 | 50 | import numpy as np
from neuron import h
import os
def record_membrane_potential():
"""
Records the membrane potential from all segments in all sections of the NEURON model.
Returns:
tuple:
- v_segments (list): A list of segment objects where the membrane potential was recorded.
... |
d1e78f70aeb100a8293ba3598d43ac723f1506fd0a279b90d205a64f3417177c | Python | 1,931 | 30 | from predify.modules import PCoderN
from predify.networks import PNetSeparateHP
from torch.nn import Sequential, ReLU, ConvTranspose2d
class PVGG16SeparateHP(PNetSeparateHP):
def __init__(self, backbone, build_graph=False, random_init=False, ff_multiplier=(0.35,0.4), fb_multiplier=(0.25,0.0), er_multiplier=(0.01,0... |
eed8965f32049f31472d48dd20e7a7ba72101aa4b6c40b0cb6774bed89d14a3e | Python | 1,931 | 58 | # @license
# Copyright 2020 Google Inc.
# 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... |
d6598b62dca0b5100a8f4fce3f7bc2bead46dd8ca5cb0ceaf3fa4314d70f54b1 | Python | 1,933 | 56 | import click
import numpy as np
from sklearn.decomposition import FastICA, PCA
from scipy import signal
from scipy.ndimage import gaussian_filter1d
from kneed import KneeLocator
import warnings
def compute_pca_ica(matrix, sigma=2, max_iter=1000):
# Convert nan and inf to zero:
matrix = np.nan_to_num(matrix, posinf=... |
e66e2503c47b523ce907e789672ce4d0da9750227f9fab61cfbc222b9c9df483 | Python | 1,933 | 69 | import numpy
from numpy.core import (product, asarray, dot, transpose, multiply, newaxis, maximum)
def _rc(s, tolerance):
cutoff = tolerance * maximum.reduce(s)
return cutoff
def _ac(s, tolerance):
return tolerance
def crpinv(a, rcond=1e-15, epsilon=None):
"""Pseudo inverse, relative cutoff """
r... |
4f396fac8ed3e76613be610555d03f56dfade6ca5de92bc5352b3a303f7ee278 | Python | 1,935 | 52 | import qt, ctk, vtk, slicer
import os
import WarpDrive
import importlib
class AbstractToolWidget():
toolEffect = []
def __init__(self, name, toolTip):
self.name = name
# Tool Button
effectPixmap = qt.QPixmap(os.path.join(os.path.split(WarpDrive.__file__)[0], 'Resources', 'Icons', self.name + '.... |
ab5bdedbc86f688bfa2361f905a13080016afc31a0a84d9dbaee062488c5154e | Python | 1,937 | 52 | import numpy as np
from phantoms.phantom import phantom
import func.geometry_func as gf
import func.BphP_func as bf
class Clara_experiment_phantom(phantom):
def create_volume(self, cfg : dict, bg_mu_s=0.0) -> tuple:
# phantom is made from 1.5% agarose 3.5% intralipid emulsion
... |
2394fa6aaa5ea795a747f450f58e850a7f306c4bb86a6a4152659177b069777a | Python | 1,938 | 71 | ### This script is used to retrieve cell soma ids from cellxgene census
import cellxgene_census
from data_config import VALUE_FILTER, VERSION
from typing import List
import os
import argparse
parser = argparse.ArgumentParser(
description='Build soma index list based on query')
parser.add_argumen... |
59e99ad8ba734ad2acfcf7e0abc509952676def853b2481dc27b6d7372864cc0 | Python | 1,938 | 74 | # Copyright 2022 InstaDeep Ltd
#
# Licensed under the Creative Commons BY-NC-SA 4.0 License (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://creativecommons.org/licenses/by-nc-sa/4.0/
#
# Unless required by applicable law or a... |
f7515cead1fc9445163be84ffc5cef4f260e331444c24d8289077e280929f8f5 | Python | 1,938 | 59 | import vtk, slicer
import numpy as np
from ..Widgets.ToolWidget import AbstractToolWidget
from ..Effects.PointToPointEffect import AbstractPointToPointEffect
from ..Helpers import GridNodeHelper
class PointToPointToolWidget(AbstractToolWidget):
def __init__(self):
toolTip = ''
AbstractToolWidget.__... |
bb08a8d95550f18d6ee0251d390cb5ed1dbd90c9e3bf5f46f9ac3a56789ca96d | Python | 1,939 | 60 | """
Functions specific to memory profiling
(thanks to https://stackoverflow.com/questions/552744/how-do-i-profile-memory-usage-in-python)
"""
import linecache
import os
import tracemalloc
from datetime import datetime
from queue import Empty, Queue
from resource import RUSAGE_SELF, getrusage
def display_top(snapshot... |
f2223f9c3c2b259dd0079b5164e668aac4e9966b82ddc2f70b0de88f1a663575 | Python | 1,940 | 71 | """tests for vak.cli.eval module"""
from unittest import mock
import pytest
import vak.cli.eval
import vak.config
import vak.common.constants
import vak.common.paths
from . import cli_asserts
@pytest.mark.parametrize(
"model_name, audio_format, spect_format, annot_format",
[
("TweetyNet", "cbin", N... |
f44845b1fa5ed63008d738e59b5f9b83ca9f1a683407df7e1ffdfa4a1a82f608 | Python | 1,940 | 57 | # -*- coding: utf-8 -*-
"""
.. _example02_ref:
Example 2: Plotting volumetric data
===================================
This example shows how to project data from a NIFTI volume onto a surface, and
then display the result.
Data is a Left vs Right hand localizer contrast (t-map) for a single subject
of the Midnigh... |
087fe3ce39013afc1591583bec8be8f3cb6a885ff84a51dbd39ca2188c747627 | Python | 1,941 | 55 | import numpy as np
from dataclasses import dataclass
from typing import Dict, List, Tuple
def simple_random_sampling(
cur_entity: Tuple[int, int],
num_neg_sample: int,
true_triplet: Dict,
num_entity: int = None,
go_terms: List = None,
**kwargs
) -> List:
"""
A simple strategy of negati... |
7b01a1b68d235a5715b6b6730acf3176fe5f06399bd7a1eae0c4c3c90f819ff3 | Python | 1,941 | 61 | #!/usr/bin/env python3
from __future__ import annotations
import argparse
import json
from pathlib import Path
from typing import Any, Dict, List
from nnunetv2.training.distillation.evaluation.eval_nsd_hd95 import main as eval_main
def parse_args() -> argparse.Namespace:
p = argparse.ArgumentParser(description=... |
55c3c072ca1c6c934565c6f2a6503ceae74574fd7c69714c8d712a02cead9ad6 | Python | 1,942 | 50 | # 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.
"""
CamemBERT: a Tasty French Language Model
"""
from fairseq.models import register_model
from .hub_interface import RobertaHubInterface
fro... |
a49bbf04497f13638332ec0b4bd2b5d7ebaed75686d478812db831e7c8086a0e | Python | 1,942 | 65 | import argparse
import unittest
from typing import Any, Dict, Sequence
import torch
from fairseq.models import transformer
from tests.test_roberta import FakeTask
def mk_sample(tok: Sequence[int] = None, batch_size: int = 2) -> Dict[str, Any]:
if not tok:
tok = [10, 11, 12, 13, 14, 15, 2]
batch = t... |
5177e3814d796664d423f24a3b648bd3f4ee0d80033568ca8aadcef80e59e248 | Python | 1,943 | 46 | import subprocess
import os
def get_allowed_n_proc_DA():
"""
This function is used to set the number of processes used on different Systems. It is specific to our cluster
infrastructure at DKFZ. You can modify it to suit your needs. Everything is allowed.
IMPORTANT: if the environment variable nnUNet... |
f151b745ec0d49529a7746ddae28b457adff4aff55dd2808bb378eb40944c43c | Python | 1,943 | 83 | from src.utils import read_gtf, read_SJ, gtf_to_SJ
import polars as pl
from pathlib import Path
import os
from SingleCell.ryp import r, to_r
SR_SJ = (
pl.concat([read_SJ(file) for file in Path('nextflow_results/STAR_results').rglob('*_SJ.out.tab')], how='vertical')
.unique(['chrom', 'start', 'end', 'strand'])
... |
1516771b192f5f79cc49a324858b09e313379c0466bca50a73873b1500cc3a38 | Python | 1,945 | 61 | """Regression tests for FinerCAM:
1. Supports the `with FinerCAM(...) as cam:` protocol used by cam.py (K3).
2. Does not IndexError on models with fewer than 4 output classes (K8).
3. References self.base_cam._htcore (single underscore) so name-mangling does
not break HPU users (K10 — static check since no HPU hard... |
89de648a52d9a484915483712ecc61c7a64ea4ed3093db8546c3d24b92f268bb | Python | 1,945 | 54 | import scanpy as sc
def preprocess_adata(
adata,
min_cells_filter=10,
normalize_target_sum=1e4,
pca_n_comps=15,
variances_norm_cutoff=1,
n_top_genes=None,
use_highly_variable=True):
"""
Preprocess the anndata object.
Parameters
----------
ad... |
b3cffc257fa369e5f7652af24bf59fc95b8d3c44850f579d3e8b1699ebbbbeb2 | Python | 1,945 | 29 | from predify.modules import PCoderN
from predify.networks import PNetSeparateHP
from torch.nn import Sequential, ReLU, ConvTranspose2d
class PVGG16SeparateHP(PNetSeparateHP):
def __init__(self, backbone, build_graph=False, random_init=False, ff_multiplier=(0.35,0.4), fb_multiplier=(0.25,0.0), er_multiplier=(0.01,0... |
0f46d9a985e8aef8b485d0a73c314f2d7f2e6bb15ef2968c8be5503e6c521a93 | Python | 1,947 | 50 | import requests
from bs4 import BeautifulSoup
import os
class PDBSummaryExtractor:
def __init__(self, summary_folder='./summary'):
self.summary_folder = summary_folder
if not os.path.exists(self.summary_folder):
os.makedirs(self.summary_folder)
def fetch_and_save_summary(self, pdb_... |
1b6fdb5eb63f4beac3408db211fd8aa436ae8793a2aa99b9f23b10257098615f | Python | 1,947 | 56 | __author__ = 'heroico'
import logging
from . import Utilities
class Gene(object):
def __init__(self, name, base_position, chromosome_name, ens_id):
self.name = name
self.base_position = base_position
self.chromosome_name = chromosome_name
self.ens_id = ens_id
@classmethod
... |
d07bb8d5c3d12cf593d55e8daa956d4d3ca4700aebdd25d97a8e04813bbe3aeb | Python | 1,947 | 43 | # created by DebarpanB
# date 26th August, 2022
import argparse, configparser
import pickle
import pandas as pd
import librosa
import numpy as np
import torchaudio
import torch
from pdb import set_trace as bp
def main(annotation_file, metadata_file, pathfile, outlist, outpath):
df_metadata = pd.read_csv(metadata_... |
4969be17c0f39f67b4a6578219ab68b4e21ddd693b46d7797292b22714002099 | Python | 1,949 | 59 | from selenium.webdriver.common.by import By
rec.begin(
{
"layers": [
{
"type": "image",
"source": "precomputed://gs://neuroglancer-public-data/flyem_fib-25/image",
"tab": "source",
"name": "image",
}
],
... |
7b2e8db6d4e844dc3bfce49ebc477039263d4574f19272ca02904ebb717624ce | Python | 1,949 | 66 | import re
from typing import Iterator
from brenda_references.config import config
from taxonomy import ncbitax
from tinydb import TinyDB, where
from tinydb.middlewares import CachingMiddleware
from tinydb.storages import JSONStorage
from tinydb.table import Document, Table
from tqdm import tqdm
def strain_queries(st... |
a38652fc3e70292709f69ee7f8e21d107f33302b3040cd08792260cd2f5bf880 | Python | 1,950 | 72 | import h5py
import numpy as np
import torch
from torch.utils.data import TensorDataset, DataLoader
from DeepMathedFilterModel import EncoderDecoder
useTemplates = True
useHe = False
print(torch.backends.mps.is_available())
device = torch.device("mps" if torch.backends.mps.is_available() else "cpu")
model = EncoderDeco... |
7a693873e25d4c1b6998d8322897c2232978bb697479f62104608c7c7768ced8 | Python | 1,951 | 29 | from predify.modules import PCoderN
from predify.networks import PNetSeparateHP
from torch.nn import Sequential, ReLU, ConvTranspose2d
class PVGG16SeparateHP(PNetSeparateHP):
def __init__(self, backbone, build_graph=False, random_init=False, ff_multiplier=(0.35,0.4), fb_multiplier=(0.25,0.0), er_multiplier=(0.01,0... |
61e813bbe6fcc95bc2afdd98538eb0184c4b6036dfcdaaf1c422657adb193ff3 | Python | 1,952 | 43 | """Convert the bundled CHARMM PSF/CRD system to dry GROMACS inputs."""
import parmed as pmd
# Load the PSF and its matching coordinates.
psf = pmd.load_file('step3_input.psf')
psf.coordinates = pmd.load_file('step3_input.crd').coordinates
# Match the solvent and ion removal used for the XTC generated with cpptraj.
p... |
1c4dc9ab17f43f030cb230972079b0035c55e3aa27d9a03ccccaef6966b80520 | Python | 1,953 | 44 | import olga.generation_probability as pgen
import olga.load_model as load_model
import pandas as pd
# pip install olga
params_file_name = 'default_models/human_T_beta/model_params.txt'
marginals_file_name = 'default_models/human_T_beta/model_marginals.txt'
V_anchor_pos_file = 'default_models/human_T_beta/V_ge... |
706ab5c5645c9a653e025a3c216a32e32cc22ca4a1dc3a03b49a8e84638d652a | Python | 1,957 | 61 | #!/usr/bin/env python
import os
import logging
from metax import Logging, Utilities
import numpy as np
import h5py
import pandas
def run(args):
if os.path.exists(args.output):
logging.info("Output exists, delete it or move it if you want it generated again")
return
Utilities.ensure_requisite_... |
c3adec35eca784efdc1a7897b7fc854d6e70269a3feb07b8a8aadb4b1d862ab5 | Python | 1,960 | 61 | # Build g0/g1 pairs per session AND per task (Python 3.5 compatible)
import os, glob, re, numpy as np
IN_DIR = r"E:\Implementation LKIS\timeseries_standard"
OUT_DIR = r"E:\Implementation LKIS\data_standard"
if not os.path.isdir(OUT_DIR):
os.makedirs(OUT_DIR)
SES_RE = re.compile(r"ses-(\d+)")
TASK_RE ... |
178c390f0a23470f36cf4328af2ee858110271de11cc06bdbf2751e865ef4b8c | Python | 1,963 | 56 | import uuid
from jinja2 import Environment
from ..charts.mixins import ChartMixin
from ..commons.utils import OrderedSet
from ..globals import CurrentConfig
from ..options import ComponentTitleOpts
from ..render import engine
from ..types import Optional, Union
class Image(ChartMixin):
def __init__... |
bd68c42c785befb06e51120f0a477a9c9216898d36845bdbd3f500de04a76172 | Python | 1,965 | 56 | # 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.
from torch import nn
class ModuleProxyWrapper(nn.Module):
"""
Wrap a DistributedDataParallel module and forward requests for missing... |
c741ee32b3432c1620b7f0c0ee4b2676f4972904adaf11f02bd10b0e29a63dc0 | Python | 1,965 | 65 | import numpy as np
import pytest
import novae
@pytest.mark.multimodal
def test_he_embeddings():
import sopa
import torch
sdata1 = sopa.io.toy_dataset(as_output=True, genes=50)
sdata2 = sopa.io.toy_dataset(as_output=True, genes=50)
novae.data.compute_histo_embeddings(sdata1, "dummy", patch_overl... |
cbe6c9290c4063abb44a14c875e70141b800c6347f98c7f031e598ec1b7866cf | Python | 1,965 | 65 | def timeit(t0):
''' function to print elapsed time since t0'''
import time
var = (time.time()-t0)/60
print('time: %.3f mins' % var)
def save_as_tiff(X, path):
import tifffile as tf
ext = '.tif'
if len(X.shape) == 2:
data = X[None].astype('float32')
if len(X.shape) == 3:
... |
fcbbdcfab7764719d2895a17a0b276e62db9790b327b80843f1e117c4c044c8d | Python | 1,965 | 31 | from predify.modules import PCoderN
from predify.networks import PNetSeparateHP
from torch.nn import Sequential, ReLU, ConvTranspose2d
class PVGG16SeparateHP(PNetSeparateHP):
def __init__(self, backbone, build_graph=False, random_init=False, ff_multiplier=(0.35,0.4), fb_multiplier=(0.25,0.0), er_multiplier=(0.01,0... |
5f11ef639a42ccff4852b32b9e3b549d7e702ea20ec60c6ad8df27d4e41fbea7 | Python | 1,966 | 50 | import torch
class RotaryPositionalEmbedding(torch.nn.Module):
def __init__(self, dim, base=10000, precision=torch.half):
"""Rotary positional embedding
Reference : https://blog.eleuther.ai/rotary-embeddings/
Paper: https://arxiv.org/pdf/2104.09864.pdf
Args:
dim: Dimens... |
921df2c8c5f1f278efe9dd79119435b59d8ce726be25490b9e90392cf5131813 | Python | 1,967 | 67 | """Run xtb GFN-FF single-point on every perovskite in structures.json.
Saves energies back to the same structures.json (adds energy_total_eV and
engine fields) so fit_subset.py can read them directly.
"""
from __future__ import annotations
import json
import sys
import time
from pathlib import Path
import numpy as n... |
391e2da306c21171f107f662ae54726c61ae4530876f999206c3cb9e43ae180a | Python | 1,968 | 81 | from __future__ import annotations
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from poetry.mixology.incompatibility import Incompatibility
class IncompatibilityCauseError(Exception):
"""
The reason and Incompatibility's terms are incompatible.
"""
class RootCauseError(IncompatibilityCauseE... |
6ceeca2f2a59bef0d99de039e33b7b52643783089e495336a6d9d6a05bb78618 | Python | 1,968 | 45 | import torch
import argparse
from pathlib import Path
from experiment import train
from config_parm import prep_config_parm
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='')
parser.add_argument('--batch_size', '-b', type=int, default=32,
help='batch size (all ... |
89a56388f40033050d2a40eca5c43b8f1ef5cdc8ca6de59bea978b3071416129 | Python | 1,969 | 96 | # -*- coding: utf-8 -*-
"""
Created on Thu Jan 23 16:30:42 2025
@author: hanna
"""
import numpy as np
from scipy.optimize import curve_fit
def degChange(PD1, PD2):
radA = PD1 * (np.pi/180)
radB = PD2 * (np.pi/180)
a = np.array( (np.cos(radA),np.sin(radA)) )
b = np.array( (np.cos(radB),np.sin(rad... |
024f610b56ed1ff90ee17985fcbc73776cfbd2f9f71f937b190b6a4469755910 | Python | 1,970 | 60 | import torch
import neurovfm.models.vit as vit_mod
class _LinearDense(torch.nn.Linear):
"""CPU-friendly stand-in for flash_attn FusedDense used in ViT modules.
Subclasses ``nn.Linear`` so it exposes ``weight``/``bias`` attributes,
matching what the ViT code expects when it rescales layer weights.
""... |
03b3cebcd6e7eab054c88781f4e11a5a95612f9f6c87b056f98cd39bba27f499 | Python | 1,970 | 46 | import torch
import torch.nn as nn
import torch.nn.functional as F
class TraditionalMatchedFilter(nn.Module):
def __init__(self, templates, normalize=True):
"""
templates: PyTorch Tensor or NumPy array of shape (4, template_length)
or (1, 4, template_length).
normalize: I... |
0932e7cba8a3616c8ae7569f32cd7035794c3e03929cd05fe540a3099225ac51 | Python | 1,970 | 38 | import torchaudio
import argparse
import json
def main():
parser = argparse.ArgumentParser(description="example: python create_hifigan_manifest.py --tsv /checkpoint/felixkreuk/datasets/vctk/splits/vctk_16khz/train.tsv --km /checkpoint/felixkreuk/experiments/hubert/hubert_feats/vctk_16khz_km_100/train.km --km_type ... |
1c162c5e545ac960814c04b1ac827f87034f507667ce82c64e4378f5ca1e8a4d | Python | 1,970 | 70 | #!/usr/bin/env python3
# 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.
"""
Replabel transforms for use with flashlight's ASG criterion.
"""
def replabel_symbol(i):
"""
Replabel sy... |
24e5ca3f135c6259671656868b19d1236c323a5c92f3560869c12eea8356cc04 | Python | 1,970 | 31 | from predify.modules import PCoderN
from predify.networks import PNetSeparateHP
from torch.nn import Sequential, ReLU, ConvTranspose2d
class PVGG16SeparateHP(PNetSeparateHP):
def __init__(self, backbone, build_graph=False, random_init=False, ff_multiplier=(0.35,0.4), fb_multiplier=(0.25,0.4), er_multiplier=(0.01,0... |
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