sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
a1fa730baf004c32d9ee947a6221fed206eb4eac8d90609956e9bf546e4a4e11 | Python | 2,136 | 67 | import torch
import torch.nn as nn
import torch.nn.functional as F
class CNN(nn.Module):
def __init__(self, input_shape, num_classes):
super().__init__()
self.conv1 = nn.Conv2d(1, 16, kernel_size=3, stride=1, padding=1)
self.relu = nn.ReLU()
self.dropout = nn.Dropout(p=0.1)
... |
e9cd960dec465e22f96b38c8985c7187107346b75a05a5d12ee2012211c0c66b | Python | 2,136 | 75 | import torch
import torch.nn as nn
from torch_geometric.nn import GINEConv, global_mean_pool, global_max_pool
class GaussianSmearing(nn.Module):
def __init__(self, start=0.0, stop=5.0, num_gaussians=32):
super().__init__()
offset = torch.linspace(start, stop, num_gaussians)
self.coeff = -0... |
2d1a00536ac9c673d942eeecd12e9780faa9b155b6ce7956a4ef6f6fe7ea22ee | Python | 2,137 | 59 | # coding=utf-8
# Copyright 2018 The HuggingFace Inc. team.
#
# 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... |
c25ff240cfa8546027445cabb2cc7671bfb2bfa4f076129b76474d4a4c1f1b5e | Python | 2,137 | 54 | """
============================================================================
fig03or_perfusion_channel_split_merge__20241106_1_6dc029b9.py — Fig 3r perfusion
============================================================================
What this script does: Jython for ImageJ: 3-channel deinterleave/merge. One cano... |
d62604d0e62458a1d2bb98535385ff540499f2db0ea68d2e633b6593c51cdde6 | Python | 2,137 | 56 | import kaldi_io
import numpy as np
import os
def get_parser():
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("w2v_dir", help="wav2vec feature and text directory")
parser.add_argument("tar_root", help="output data directory in kaldi's format")
parser.add_argument("split", h... |
93f9e1a4dc950fd274f329ba3f26634fe80c55c24f1f715c21f493dddce8aa7c | Python | 2,139 | 64 | """Tests for vak.eval.eval function."""
from unittest import mock
import pytest
import vak.config
import vak.common.constants
import vak.common.paths
import vak.eval
@pytest.mark.parametrize(
"audio_format, spect_format, annot_format, model_name, eval_function_to_mock",
[
("cbin", None, "notmat", "T... |
a49da2de5f69e403469ba892db3fbbe4daf15bda43fb8be6e466e93ade07daf1 | Python | 2,139 | 61 | # coding=utf-8
# Copyright 2018 The HuggingFace Inc. team.
#
# 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... |
cd7d2866516cc0765fac0b25b3b64b33c4582239bdf6625204e4ecae65784f6c | Python | 2,139 | 62 | #!/usr/bin/env python
import os
import argparse
import re
def argsParse():
"""
Parsing all sample names and peakfiles to perform IDR on multiple peak
files for a given sample name
"""
parser = argparse.ArgumentParser()
parser.add_argument("-sn", nargs='+', metavar="SAMPLENAMES", help="Enter a"... |
77c168100f8eae1d68e8cee7c0ed1bf11324b422972259ee7549400bad010006 | Python | 2,140 | 60 | class MODEL_CONFIG:
"""
This class contains all the configuration parameters for the project.
"""
frames = 20 # number of frames
channel_buffer_size = 150 # number of channels to buffer
max_regs = 41 # maximum number of regions
# feature extractor
# V3 PARAMS
ft_enc_dims = (64, 1... |
906787f097bb3fa7449a970eda740d4d7060d6f78ea998a9d907c004b8cf82bc | Python | 2,140 | 63 | # -*- coding: utf-8 -*-
""" Sample Application of Cellular Automata Tractography on FiberCup Phantom.
Copyright (C) 2019 Andac Hamamci
This program 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,... |
50957e328d741ae32a32dd5c4b7e976ac3834402869c873e017b761decab90d9 | Python | 2,141 | 65 | from xmljson import gdata
from xml.etree.ElementTree import fromstring
def create_settings_json(input_file):
with open (input_file, "r") as file:
file_string = file.read()
a = gdata.data(fromstring(file_string))
info_dict = { }
info_dict['software'] = 'Open Ephys GUI'
info_dict['ver... |
656f661c4c39161f286896ded8480c6ccc09c64bd3d32d665c4228a0e03f70bc | Python | 2,141 | 80 | # _ _
# | | | |
# ___ __ _ __ _ ___| |_ ___ ___ | |___
# / __/ _` |/ _` / __| __/ _ \ / _ \| / __|
# | (_| (_| | (_| \__ \ || (_) | (_) | \__ \
# \___\__,_|\__,_|___/\__\___/ \___/|_|___/
'''
A Convergent Amino Acid Substitution identif... |
83a2183849e225c7c463b31057132b10c147ebd1b1e678a583f484b5bef68201 | Python | 2,142 | 43 | """Get descendant/parent counts for all GO terms in a GODag and broad L0 and L1 terms."""
__copyright__ = "Copyright (C) 2016-present, DV Klopfenstein, H Tang, All rights reserved."
__author__ = "DV Klopfenstein"
from goatools.gosubdag.godag_rcnt_init import CountRelativesInit
class CountRelatives:
"""Get desce... |
e5938072caf5acd932a79c189bafbce2f2ed8b72a5435d4c2857624d536129ea | Python | 2,142 | 73 | #!/usr/bin/env python2
# piped script to take multimappers and randomly assign
# requires a qname sorted file!!
import sys
import random
import argparse
def parse_args():
'''
Gives options
'''
parser = argparse.ArgumentParser(description='Saves reads below a alignment threshold and discards all other... |
494808552b2d6435b9deed4a8beb7d27a9a9d117073b8e38676ccce86949db5f | Python | 2,143 | 65 | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
# If ex... |
3673ccaa3b058f40285e0f0a63a3a477901abc647f58fc8e94bac4f1893dffba | Python | 2,144 | 69 | #!/usr/bin/env python
# PYTHON_ARGCOMPLETE_OK
"""Print some basic information about an image file."""
import warnings
import argparse
import os
from mdt.lib.nifti import load_nifti, nifti_filepath_resolution
import textwrap
from mdt.lib.shell_utils import BasicShellApplication
__author__ = 'Robbert Harms'
__date__ = ... |
7479b42946f602caad23235b8c34666d7dfe7d8275355974922e463779aa1906 | Python | 2,144 | 73 | #!/usr/bin/env python
# ENCODE DCC fastq merger wrapper
# Author: Jin Lee (leepc12@gmail.com)
import sys
import os
import argparse
from encode_lib_common import (
assert_file_not_empty, copy_f_to_f, log, ls_l, mkdir_p,
run_shell_cmd, strip_ext_fastq)
def parse_arguments(debug=False):
parser = argparse.A... |
177adf331d6e1336745e0a7d4e39529e8cc31fe1bfc4a26696d8c583be2a6fe0 | Python | 2,146 | 69 | def ants_registration(
in_nii: str,
ref_nii: str,
out_nii: str,
prefix_out_tform: str,
typ: str,
opts_ants: dict = {},
) -> str:
"""
ANTs registration.
Parameters
----------
in_nii : str
Input nifti file.
ref_nii : str
Reference nifti file.
out_nii : ... |
62525138cc018564302c00827ac8d7dc9e87b93873d5801529d65b3a1dbecb1d | Python | 2,147 | 82 | import pytest
import torch
from torch import nn
from scvi.external.mrvi._components import (
MLP,
AttentionBlock,
ConditionalNormalization,
Dense,
NormalDistOutputNN,
ResnetBlock,
)
def _init_weights(m):
if isinstance(m, nn.Linear):
nn.init.xavier_uniform_(m.weight)
if m.b... |
ca7c89b6b912222aaff48fa709136546495fdb68f7bfa885827b43dfa3d5fdcd | Python | 2,148 | 47 | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'TabTextual.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_TabTextual(object):
def setupUi(self, TabTextual):
TabTe... |
18d8cd34eda1a662b586b6cc437b17a2eb4a81788c2c894777b169072d2d9578 | Python | 2,149 | 61 |
from pathlib import Path
from torch.utils.data import Dataset
import numpy as np
import os
from torch.utils.data import Dataset, Subset
class FetalBrainDataset(Dataset):
def __init__(self, data_dir, split = "train"):
self.data_dir = Path(data_dir)
self.split = split
self.data_... |
152b2311de530d41180396d51b24a6b919fbad333f61ba0b4764437f0299d850 | Python | 2,150 | 78 | # Copyright (C) 2025 ETH Zurich, Moritz Thürlemann, and other AMP contributors
import torch
import numpy as np
import torch.nn as nn
from torch import Tensor
def ff_module(
node_size,
num_layers,
input_size,
with_bias=True,
output_size=None,
activation=nn.SiLU(),
final_activation=None,
)... |
39e831153f7df874e6e2df56dfc9275fb196ad28b770d86f521c892e858319c5 | Python | 2,150 | 80 | from __future__ import annotations
from typing import TYPE_CHECKING
import pytest
from poetry.core.constraints.version import Version
from poetry.core.packages.package import Package
from poetry.__version__ import __version__
from poetry.factory import Factory
from poetry.installation.executor import Executor
from ... |
9c3339dd8733d327569340f47054b3192f5a2bcb87f78d82723470483ed92ddd | Python | 2,150 | 78 | import os
import sys
sys.path.append("..")
sys.path.append("../utils")
import numpy as np
import cv2
import random
import config.cfg_lodet as cfg
import torch
from tqdm import tqdm
import shutil
val_data_path = r"D:\FangX24\code\LO-Det-main\mnt\Datasets\DIOR_t/"
filename = cfg.TEST["EVAL_NAME"]+'.txt'
img_... |
b2641ca3b7031df622629742a85a67a5070c9834fffffd2aa1717ddf37a48949 | Python | 2,150 | 76 | #!/usr/bin/env python3
import numpy as np
def rect_PSP(zeta: int, tau_ref: int, tau_syn: int) -> float:
"""Rectangular PSP shape (1 within tau_ref, 0 elsewhere)."""
return np.heaviside(-zeta + tau_ref, 0.0) * np.heaviside(zeta, 1.0)
def exp_PSP(zeta: int, tau_ref: int, tau_syn: int) -> float:
"""Expone... |
6883e0ede16d1105e001d40b84e3a3a287f61824a5afa49b759d2e7d180d52d3 | Python | 2,151 | 54 | # 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 math
import torch.nn as nn
from fairseq.models.transformer import TransformerEncoder
from .linformer_sentence_encoder_layer import Li... |
b88ae6f35e6aadb7862f0e381d57e13b2b03ae523ad5ea8037cd39222621244b | Python | 2,151 | 66 | import argparse
import neuroglancer
import neuroglancer.cli
if __name__ == "__main__":
ap = argparse.ArgumentParser()
neuroglancer.cli.add_server_arguments(ap)
args = ap.parse_args()
neuroglancer.cli.handle_server_arguments(args)
viewer = neuroglancer.Viewer()
with viewer.txn() as s:
s... |
44544b5b1593903ed9e3aede06eb0e283c283fa467a10e5a0963c8c86709e5d6 | Python | 2,152 | 59 | import polars as pl
from src.utils import read_gtf
from SingleCell.ryp import r, to_py, to_r
r(
"""
library(GenomicRanges)
library(parallel)
"""
)
transdecoder = pl.read_csv("full_nt.fasta.transdecoder.gff3", separator = "\t", new_columns=["seqid", "source", "type", "start", "end", "score", "strand", "pha... |
0d64c6dfc5b63618d27ad5df7bc0f4bac2b31f4dd0207dc0b758691afd06584e | Python | 2,153 | 60 | import os
import pandas as pd
from BLRun.runner import Runner
class GENIE3Runner(Runner):
"""Concrete runner for the GENIE3 GRN inference algorithm."""
def generateInputs(self):
'''
Function to generate desired inputs for GENIE3.
If the folder/files under self.input_dir exist,
... |
0dbbb580f79b9ed88962bda4e312c0a53382c00a7f6eb0c358b535aeca1e3942 | Python | 2,153 | 72 | from __future__ import annotations
import types
import pandas as pd
import pytest
from src.features.telemetry_alignment.io.associated_file_locator import (
_filename_matches_date,
_matching_files_for_date,
TelemetryAssociatedFileLocator,
)
def test_filename_date_match_accepts_zero_padded_month_and_day(... |
cdb30281c431e8682207eaf09287e0f953d3fb5aa1e76ab7cb9cd3216fa8f23e | Python | 2,153 | 78 | # 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.utils.data.dataloader import default_collate
from . import FairseqDataset
class BaseWrapperDataset(FairseqDataset):
def __in... |
12362b309f67ed352d416cced9d237a4f305d0c73356f05cd2f6e9e1e0fd18fa | Python | 2,154 | 82 | from os.path import join
import numpy as np
import pandas as pd
# chr pos type
import seaborn as sns
from matplotlib import pyplot as plt
sns.set(style='ticks', palette='Set2')
sns.despine()
from config_path import DATA_PATH
input_dir = join(DATA_PATH, 'prostate_paper/raw_data')
# input_dir= '../../data/prostate/i... |
afba42ca5ba79816adc182892dc297dc3b166c248191abcbcf171f24e12bc5c8 | Python | 2,155 | 42 | # Source code:
# https://github.com/zbmed-semtec/doc2vec-doc-relevance-training/blob/main/code/train_model/train.py
# This file includes the modifications to the source codes according to this project!
import time
import logging
import utilities as utilities
def run(best_params, args):
# 1) Load the trainin... |
e2d2c58137d82dc99ba7ecf708bc75ae1c181ca66b3ab642dd82c1319cc92213 | Python | 2,155 | 59 | # coding=utf-8
# Copyright 2018 The HuggingFace Inc. team.
#
# 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... |
8eae9694a34d26bbdab86336d18bf24ce90203e1035544a2911d9b104bfafcb7 | Python | 2,157 | 61 | # Copyright 2023 BioMap (Beijing) Intelligence Technology Limited
from .transformer import pytorchTransformerModule
from .performer import PerformerModule
from .mae_autobin import MaeAutobin
def select_module(config, sub_config, module_name):
if module_name == 'performer':
return PerformerModule(
... |
963ee2787f3db2ff2f42c4d0c686ac2bb83020a16ed68f94bab88f8727cb2898 | Python | 2,157 | 61 | # coding=utf-8
# Copyright 2018 The HuggingFace Inc. team.
#
# 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... |
55b0aff5584d3dab26223c28ce41f6ce57d182b404e223c1f822593d1352e0ac | Python | 2,162 | 68 | import pandas as pd
from .power_divergence import PowerDivergence
class LogLikelihood(PowerDivergence):
"""
Log-likelihood ratio test for conditional independence on discrete data.
This class is a thin specialization of :class:`PowerDivergence` with
``lambda_="log-likelihood"``. In this implementati... |
2d62810110ffdac755b788b6ea4d16f843469fd646db0545dbb1e484b9a58734 | Python | 2,163 | 59 | import pytest
def test_import_optional_dependency():
"""Test the import_optional_dependency function."""
from pylossless.utils import check
# Test the case where the package is not installed.
package = "sdgssfersfsdesdfsefsdfsdt"
with pytest.raises(ImportError, match=f"Missing optional dependency... |
233019b5bb5f260d4153c600b4fc633e7b2a56c369212723f06b338bd092cd50 | Python | 2,164 | 64 | """Generate a dataset of entity names from the document database.
Examples:
{"term": "Tyrosine translase", "class": "d3o:Enzyme", "entid": "3494"}
{"term": "Tyrosyl-tRNA ligase", "class": "d3o:Enzyme", "entid": "3494"}
{"term": "Escherichia coli", "class": "d3o:Bacteria", "entid": "2026"}
{"term": "ATC... |
f0dbce0042aba5adcf7f46869ae3d0c7eefc93defc80483245deae41bc5858d8 | Python | 2,164 | 62 | from ... import options as opts
from ... import types
from ...charts.chart import Chart
from ...globals import ChartType
class Calendar(Chart):
"""
<<< Calendar Diagram >>>
The calendar diagram is mainly used to represent the size of a value by
color and must be used in conjunction with th... |
2dacb52583a9d92f15754522ae21aaaf53b18618c286ff8a5fb933764fff5261 | Python | 2,166 | 64 | # 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 numpy as np
import os
import pickle
from mmpt.utils import ShardedTensor
class Shard(object):
def __init__(
self,
... |
68a7d90a346101b2ef47a6b1b47ce3afb47fb2583457472a3b8ff98e4f66ff7f | Python | 2,166 | 64 | import unittest
from unittest.mock import patch
from pyecharts import options as opts
from pyecharts.charts import LMap
from pyecharts.globals import ChartType
TEST_LOCATION = ["London"]
TEST_VALUE = [1]
class TestLMapChart(unittest.TestCase):
@patch("pyecharts.render.engine.write_utf8_html_file")
def test... |
89aedea28e4d08788fc595ef162bd6196a80a1db1b8c0b6203abc926b8950af1 | Python | 2,166 | 54 | import torch
import scvi
from scvi import REGISTRY_KEYS
def test_contrastive_dataloader(
mock_contrastive_adata_manager,
mock_background_indices,
mock_target_indices,
):
batch_size = 32
adata = mock_contrastive_adata_manager.adata
expected_background_indices = mock_background_indices[:batch_... |
6aa4c3f26c2b7b2b2aa38ee5a456a455261ca27286bd84ec43d48cfab7dd2684 | Python | 2,167 | 67 | import lightning as L
import torch
from torch import Tensor, nn
from torch_geometric.data import Batch
from torch_geometric.nn.models import GAT
from . import AttentionAggregation
class GraphEncoder(L.LightningModule):
"""Graph encoder of Novae. It uses a graph attention network."""
def __init__(
se... |
41c7075759f36c6ea05b0414b14b9975f1fc4b576356308f9788c4950850dc71 | Python | 2,168 | 71 | """ from https://github.com/keithito/tacotron """
import inflect
import re
_inflect = inflect.engine()
_comma_number_re = re.compile(r'([0-9][0-9\,]+[0-9])')
_decimal_number_re = re.compile(r'([0-9]+\.[0-9]+)')
_pounds_re = re.compile(r'£([0-9\,]*[0-9]+)')
_dollars_re = re.compile(r'\$([0-9\.\,]*[0-9]+)')
_ordinal_r... |
5b3fa0e9be5803918176d9e4ebc9bb5ee81bd48eb437be3fb491664d7ed40e33 | Python | 2,169 | 64 | from collections.abc import Iterator
import lightning as L
from lightning.pytorch.callbacks import Callback, EarlyStopping, ModelCheckpoint
from lightning.pytorch.loggers.logger import Logger
from lightning.pytorch.utilities.types import OptimizerLRScheduler
from torch import optim
from torch.nn.parameter import Param... |
2a871f316dc673fbfed8d0d497def8aca8991534d30f19e895c8dd24820b1cb2 | Python | 2,170 | 73 | #!/usr/bin/env python2
# piped script to take multimappers and randomly assign
# requires a qname sorted file!!
import sys
import random
import argparse
def parse_args():
'''
Gives options
'''
parser = argparse.ArgumentParser(
description='Saves reads below a alignment threshold and discards... |
58c4b11974a1cdbfec4796766f5abbbe18a4d3a0a9f33a12edf61b2d918644ab | Python | 2,170 | 55 | import polars as pl
from src.utils import read_gtf
classification = pl.read_parquet("nextflow_results/V47/final_classification.parquet")
polyA_site = pl.read_csv(
"data/atlas.clusters.2.0.GRCh38.96.bed",
separator="\t", new_columns=["chrom", "start", "end", "name", "score", "strand"],
schema_overrides={"... |
b49a3240de39c20af2c78ffc876c483f7018198c4971c80e972415a0eda9cd95 | Python | 2,170 | 61 | import numpy as np
import pandas as pd
from sklearn.base import BaseEstimator, RegressorMixin
class BaseCausalPrediction(RegressorMixin, BaseEstimator):
"""
Base class for causal prediction algorithms in pgmpy. Provides common
functionality for preparing and validating feature dataframes.
"""
def... |
450cce84e0552d2197be009b1afde5ce8733aed42ce0a28f8a64fe69c26f735f | Python | 2,171 | 67 | """Download GOA files from the Gene Ontology Annotation (GOA) resource http://www.ebi.ac.uk/GOA."""
__copyright__ = (
"Copyright (C) 2016-present, DV Klopfenstein, H Tang. All rights reserved."
)
__author__ = "DV Klopfenstein"
import os
import sys
from ..base import dnld_file
class DnldGoa:
"""Download fil... |
7622a347c8c49d9ad783bcef8e8cde8022056da9e55d3e434f12694d64266a0e | Python | 2,171 | 69 | import numpy as np
import theano.tensor as T
from lasagne import init
from .base import Layer
__all__ = [
"EmbeddingLayer"
]
class EmbeddingLayer(Layer):
"""
lasagne.layers.EmbeddingLayer(incoming, input_size, output_size,
W=lasagne.init.Normal(), **kwargs)
A layer for word embeddings. The inp... |
4ec05a641f7daa30c33f255eb92d8246de3e763928a8dee42d1a446153d9da45 | Python | 2,173 | 57 | import pytest
from sofa.plots.plots import plot_loadings, plot_top_loadings, plot_variance_explained, plot_variance_explained_factor, plot_variance_explained_view, plot_factor_metadata_cor, plot_fit, plot_enrichment
def test_plot_loadings(sample_model):
# Test plot_loadings function
ax = plot_loadings(sample... |
7092a95bf0849d5e0e99d41ad080c9f6b0844e1bd248c981655b7e08ad76e938 | Python | 2,174 | 72 | from __future__ import annotations
import logging
import sys
import textwrap
from pathlib import Path
from typing import TYPE_CHECKING
from typing import ClassVar
from poetry.console.logging.filters import POETRY_FILTER
from poetry.console.logging.formatters import FORMATTERS
if TYPE_CHECKING:
from logging imp... |
54af1099d359ca8995c17cd5ec067c37bc172866ebefca5af3c7d4093a3b38c9 | Python | 2,176 | 68 | #!/usr/bin/env python3
"""
Subset a CPAT ORF FASTA file to sequences listed in the CPAT best-ORF TSV (column 'ID').
"""
import argparse
import sys
def load_best_ids(tsv_path):
ids = set()
with open(tsv_path) as fh:
header = fh.readline().split('\t')
id_col = header.index('ID')
for lin... |
8adebc961a3ac58e2375715d00d58057ead7fb1f10cf6600464b0c47f3a29410 | Python | 2,177 | 87 | #!/usr/bin/env python
# Author_and_contribution: Niklas Mueller-Boetticher; created script
import argparse
# TODO adjust description
parser = argparse.ArgumentParser(description="log1p transformation using scanpy")
parser.add_argument(
"-c", "--coordinates", help="Path to coordinates (as tsv).", required=True
)... |
e784a427951c27f5242ffe5adc6a0c34fc5a6fb086e7b5f7e93340533e4aec28 | Python | 2,177 | 56 | import os
import shlex
import subprocess
import progressbar
from time import time
from pathlib import Path
def find_all_files(path_dir, extension):
out = []
for root, dirs, filenames in os.walk(path_dir):
for f in filenames:
if f.endswith(extension):
out.append(((str(Path(f)... |
fbf7e3bcff0f9d7df084f5920a3e91d9199eb7d078b295b700b6b07eafbf307d | Python | 2,179 | 55 | from nnunetv2.dataset_conversion.generate_dataset_json import generate_dataset_json
from batchgenerators.utilities.file_and_folder_operations import join, subdirs, subfiles, maybe_mkdir_p
from nnunetv2.paths import nnUNet_raw
if __name__ == '__main__':
"""
this dataset does not copy the data into nnunet format... |
88e958ec0c70a6658ae4558bbedbefa0cb0e3ba5daaa8492426ad968cfae3350 | Python | 2,182 | 68 | from __future__ import annotations
import pytest
from poetry.console.exceptions import ConsoleMessage
@pytest.mark.parametrize(
("text", "expected_stripped"),
[
("<info>Hello, World!</info>", "Hello, World!"),
("<b>Bold</b>", "Bold"),
("<i>Italic</i>", "Italic"),
],
)
def test_st... |
971c87f42ade25b0da9b6a9f1d6b5e33503c5845c66f711886ccf38b619c2a52 | Python | 2,182 | 79 | from torch import nn
from scvi.module.base import SupervisedModuleClass
from scvi.nn import FCLayers
class Classifier(nn.Module, SupervisedModuleClass):
"""Basic fully-connected NN classifier.
Parameters
----------
n_input
Number of input dimensions
n_hidden
Number of nodes in hi... |
fe09aaee81f54eb8f1d879709e2bac3f2f938bfcedf571ca37ef1bb3fc60c276 | Python | 2,182 | 63 | import pytest
from pathlib import Path
from numpy.testing import assert_array_equal
import pylossless as ll
raw_sim = ll.datasets.load_simulated_raw()
# LOAD DEFAULT CONFIG
config = ll.config.Config()
config.load_default("infants")
config["noisy_channels"]["outliers_kwargs"]["lower"] = 0.25
config["noisy_channels... |
3f690dc5fc0e395d4f1ffe6396717548d18bd04f4518258308bbe5f392703f5f | Python | 2,184 | 68 | import torch
import torch.nn as nn
class Normalize(nn.Module):
def __init__(self, num_features: int, eps=1e-5, affine=False, subtract_last=False, non_norm=False):
"""
:param num_features: the number of features or channels
:param eps: a value added for numerical stability
:param af... |
ddbdb677442f0ad39b07046636a7c7a750f0c061d1615167878d3c8b23b28b18 | Python | 2,184 | 66 | from collections.abc import Hashable
from pgmpy.structure_score.log_likelihood_cond_gauss import LogLikelihoodCondGauss
class AICCondGauss(LogLikelihoodCondGauss):
r"""
AIC structure score for Bayesian networks with mixed discrete and continuous variables.
This score penalizes the conditional-Gaussian l... |
538b0a8579bce4db6e349265eb53229d9a791fb4d8845ff58f7ffcb90cecdc65 | Python | 2,189 | 46 | #!/usr/bin/env python3
"""Tiny mechanical InferRef3D smoke test for CPU or Colab T4; not performance evidence."""
import argparse
import json
from pathlib import Path
import sys
import tempfile
import time
import zipfile
sys.path.insert(0, str(Path(__file__).resolve().parents[1]))
import inferref3d_backend as infer
im... |
abbce01aab6620b95e33f971c19ad1291f1d8fc0dd3aa8f5dd103da1850a9165 | Python | 2,189 | 82 | """
Wrappers for VTK lookup tables.
"""
# Author: Oualid Benkarim <oualid.benkarim@mcgill.ca>
# License: BSD 3 clause
from vtk.util.vtkConstants import VTK_STRING, VTK_UNSIGNED_CHAR
from .base import BSVTKObjectWrapper
from ..decorators import unwrap_input
class BSScalarsToColors(BSVTKObjectWrapper):
"""... |
e822821f77464d0cff7d7ec5658d59b77dfceba26ba2f025be55ec2d8d2c1de9 | Python | 2,189 | 59 | import serial
import serial.tools.list_ports as s_ports
import time
import sys
from Sensors import constants
def configure_serial():
"""Method to send ID commands to sensors connected to COM ports
Sensornodes store their respective IDs in non-volatile memory
"""
constants.SNIds = []
# Iterate ... |
7c6b7260550fe7675589cfee69f1b39af340270758fa57f9e1ee86e6c748c477 | Python | 2,191 | 61 | from umap import UMAP
import tensorflow as tf
import numpy as np
import os
import cv2
from pathlib import Path
import joblib
from msi_visual.normalization import spatial_total_ion_count, total_ion_count, median_ion
from msi_visual.utils import normalize
def norm_umap_channel(channel, low=0.01, high=99.99):
... |
01424d409f32ebea8430f2f20962dd84e71a108acac2ab1443a3ecdde5cd243d | Python | 2,193 | 65 | from collections.abc import Hashable
from pgmpy.structure_score.log_likelihood_gauss import LogLikelihoodGauss
class AICGauss(LogLikelihoodGauss):
r"""
AIC structure score for Gaussian Bayesian networks.
This score penalizes the Gaussian log-likelihood using a sample-size independent complexity term. Th... |
738e8ed6697b46678549d17a190d3c905c1f7624473cfd6b380fde695db314fe | Python | 2,194 | 55 | from lightning import LightningModule
from lightning.pytorch.callbacks import BaseFinetuning
from torch.optim.optimizer import Optimizer
import re
import yaml
def _is_parent_module_unfrozen(module_name, potential_parent_modules):
for potential_parent_module_name in potential_parent_modules.keys():
if modu... |
957e12c4a91e63bbc91be5304e5e254cd1488c6839d9d79ba8748124bff183bd | Python | 2,195 | 71 | import os
from pathlib import Path
import pandas as pd
from anndata import AnnData
from scipy.io import mmread
def read_10x_atac(base_path: str | Path) -> AnnData:
"""Read scATAC-seq data outputted by 10x Genomics software.
Parameters
----------
base_path
Path to directory with matrix, bed f... |
7e022780d7abd6a68b5f26342302b1f9e1e8efbc1c64a0f6cc942150c3d6821f | Python | 2,196 | 73 | import pickle
import numpy as np
from functools import reduce
from celltype_ibl.params.config import KENJI_ALLEN_PATH
def get_kenji_allen_wvf_acg_pairs(
data_path: str = KENJI_ALLEN_PATH,
return_optotagged: bool = True,
return_half: bool = True,
return_id: str = "unit",
selected_project: str = "bo... |
c83db4a95ec6d98d63932c907246d0ab0b113f89d057a91de2c6f9a43d89df3d | Python | 2,196 | 66 | import os
import subprocess
import shutil
class PLIPProcessor:
def __init__(self, pdb_path, output_dir='./data/visualize'):
self.pdb_path = pdb_path
self.output_dir = output_dir
self.temp_dir = './temp_plip_files'
if not os.path.exists(self.output_dir):
os.maked... |
19ea8a2dd7e9156ec5154c8fcbd7dc6be9b0f66f2941900d4175bd8b4a615954 | Python | 2,198 | 79 | from __future__ import annotations
from typing import TYPE_CHECKING
from poetry.core.packages.package import Package
from poetry.factory import Factory
from poetry.mixology.failure import SolveFailureError
from poetry.mixology.version_solver import VersionSolver
if TYPE_CHECKING:
from collections.abc import Ma... |
1ce5bbbdfda03d2b92b89fc2786434521b8860afe08ecab47dd65a8241df0bff | Python | 2,199 | 72 | import os
import numpy as np
import random
import pandas as pd
import time as tm
from operator import itemgetter
from sklearn.model_selection import train_test_split
import pickle as pkl
import scipy.sparse
from metrics import *
from gutils import *
from graph import *
#' data preperation
def input_data(DataDir):
... |
3da94b92fd2130f81fb635961d0ada35497a62b67e230ffc04e835caca5e022f | Python | 2,199 | 68 | import numpy as np
import pandas as pd
def g_rand_data(N=5000, M=128):
label = np.random.randint(2,size=N)
data = np.random.rand(N,M)
line = ""
for i in range(N):
datastr = " ".join(["{:d}:{:.3f}".format(j, data[i,j]) for j in range(M) ])
line += "{:d} {:s}\n".format(label[i], datastr... |
efa4afff02e251d1371e30c30c55e94a374d819f69ef17d89ea2182a8b195a28 | Python | 2,200 | 53 | #!/usr/bin/env python3
# MIT License
#
# Copyright 2025 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... |
7607ccae0df71583fcf059b67fca77b3ff550921db7400b8d9bcaffc81c01be4 | Python | 2,201 | 42 | # Source code:
# https://github.com/zbmed-semtec/doc2vec-doc-relevance-training/blob/main/code/train_model/train.py
# This file includes the modifications to the source codes according to this project!
import time
import logging
import utilities as utilities
def run(best_params, args):
# 1) Load the trainin... |
63aee6e320e7628941b8b6d5cf84c52d95791e5d348d6993a9f6611e3e9e1d75 | Python | 2,202 | 68 | """Implementation of utilities to load a pretrained Borzoi model in Trix."""
from typing import Callable, Tuple
import haiku as hk
import jax.numpy as jnp
from nucleotide_transformer.borzoi.model import (
BorzoiConfig,
build_borzoi_fn_with_head_fn,
)
from nucleotide_transformer.enformer.features import FEATU... |
5193663059d99bdbefd3cf3bdbf522e08bbc49f755fb4fc8b6364fa7222d1131 | Python | 2,203 | 68 | import numpy as np
import loompy
from .utils import div0
class Normalizer:
"""
Normalize and optionally standardize and batch-correct a dataset, dealing properly
with edge cases such as division by zero.
"""
def __init__(self, standardize: bool = False, layer: str = "") -> None:
self.standardize = standardi... |
d389672a56e4638b032828e6db3099253b5be38cfdf0a848a7eb8bb75a5bb0d1 | Python | 2,203 | 72 | from typing import Any
import numpy as np
from sklearn.preprocessing import LabelEncoder
color_alphabet = np.array([
[240, 163, 255], [0, 117, 220], [153, 63, 0], [76, 0, 92], [0, 92, 49], [43, 206, 72], [255, 204, 153], [128, 128, 128], [148, 255, 181], [143, 124, 0], [157, 204, 0], [194, 0, 136], [0, 51, 128], [25... |
0615ab31a45ac9593a5a5d7936ed71b29ca4937749f83ee6b3169f92075f8758 | Python | 2,204 | 68 | # /usr/bin/env python
'''
Written by Kong Xiaolu and CBIG under MIT license:
https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
'''
import os
import numpy as np
import torch
import CBIG_pMFM_basic_functions as fc
import warnings
def CBIG_mfm_test_desikan_main_highres(gpu_index=0):
'''
This function ... |
37f937915b610fde31884b43081486f6c8f49017f49353ad9f5e3dd4de8869e3 | Python | 2,205 | 66 | from functools import partial
import jax
import jax.numpy as jnp
import numpy as np
import pytest
from packaging.version import Version
from folx import forward_laplacian
@pytest.mark.skipif(
Version(jax.__version__) < Version('0.7.1'), reason='jax version too old'
)
def test_shard_map_bug_integer_pow():
# ... |
99fccd68215db92432729e14d7ff941d3a863aceca8f35dadc87796f78d1e276 | Python | 2,205 | 51 | # basic Charts
from ..charts.basic_charts.amap import AMap
from ..charts.basic_charts.bar import Bar
from ..charts.basic_charts.bmap import BMap
from ..charts.basic_charts.boxplot import Boxplot
from ..charts.basic_charts.calendar import Calendar
from ..charts.basic_charts.chord import Chord
from ..charts.basic_charts.... |
ddbfcc70e058876f41362bcf150902b19c221b33161dba4acc42d685182181b8 | Python | 2,207 | 63 | from datetime import datetime
import os
import time
import pytest
import vak.common.constants
import vak.common.paths
def results_path_matches_expected(
results_path, root_results_dir, before_timestamp, after_timestamp
):
assert results_path.parent == root_results_dir
assert results_path.name.startswith... |
fe47d3c4efbe905c39b179b9cb6ab4651323b448425ce0e811e2701a13fe6199 | Python | 2,207 | 65 | #!/usr/bin/env python
# PYTHON_ARGCOMPLETE_OK
"""Print some basic information about a protocol."""
import argparse
import os
import mdt
from argcomplete.completers import FilesCompleter
import textwrap
from mdt.lib.shell_utils import BasicShellApplication
__author__ = 'Robbert Harms'
__date__ = "2015-08-18"
__maintai... |
6d60bdbc6d6b186bf906cfbfa954f8437ec590563d1b12343ceed6b1932b4570 | Python | 2,210 | 59 | # @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... |
57593820f0b3c5c6af4c6d7559387f7065a55bff3aadb702ac965fe2ec2bbe02 | Python | 2,212 | 43 | # Source code:
# https://github.com/zbmed-semtec/doc2vec-doc-relevance-training/blob/main/code/train_model/train.py
# This file includes the modifications to the source codes according to this project!
import time
import logging
import utilities as utilities
import gensim
def run(best_params, args):
# 1) Lo... |
d09843f3373e3701bcf12e1c5cc441c488c71a82f8de4cdcb99b9cf47a0e2c4b | Python | 2,212 | 75 | import pytest
import torchvision
import cv2
import numpy as np
from pytorch_grad_cam import GradCAM, \
ScoreCAM, \
GradCAMPlusPlus, \
XGradCAM, \
EigenCAM, \
EigenGradCAM, \
LayerCAM
from pytorch_grad_cam.refine_cam import RefineCAM
from pytorch_grad_cam.metrics.arcc import ARCC
from pytorch_gr... |
da21f032d880decc0f65d1b597477cc1a77e46ddca75dd3e813d293c55475ed1 | Python | 2,213 | 51 | import os
import random
# dior
# input_dir = "D:\\FangX24\\code\\LO-Det-main\\mnt\\Datasets\\DIOR\\ImageSets\\train_s2_cat\\base_base"
ks=10
# nwpu
input_dir = "D:\Projects\LFODet-main\mnt\Datasets\\NWPU\ImageSets\\train_cat\\base_all"
output_file = "D:\Projects\LFODet-main\mnt\Datasets\\NWPU\ImageSets\\random5\... |
8ebafebf02b7288d5b825028ac23da6ce48e4a32b691e6b93c2b70dd77986cdb | Python | 2,214 | 66 | import numpy
import numpy.testing
import unittest
from metax import misc
from metax.misc import FeatureMatrix
from . import SampleData
EXPECTED_A = \
[[ 0.1 , 0.01, 0.07],
[ 0.01, 0.02, 0.02],
[ 0.07, 0.02, 0.06]]
EXPECTED_B = \
[[ 3.5 , 3.84 , 3.67 ],
[ 3.84 , 4.44 , 4.14 ],
[ 3.67 , 4.14 , 3.905]]
... |
28da78b68b305873a8c051f11f16e6e7382efdc5383349d90e0d245341b5e807 | Python | 2,215 | 56 | import SimpleITK
import nibabel
import numpy as np
from batchgenerators.utilities.file_and_folder_operations import *
import shutil
from nnunetv2.dataset_conversion.generate_dataset_json import generate_dataset_json
from nnunetv2.paths import nnUNet_raw
if __name__ == '__main__':
base = '/home/isensee/Downloads/... |
9c19507d206b3c27e064c39abfc597722a12e5e837c90c4823fea22a99b2d2de | Python | 2,215 | 60 | """
Infer trees from windowed VCF
"""
import tsinfer
import zarr
import yaml
import numpy as np
import os
output_dir = os.path.dirname(snakemake.input.yaml)
vcz = zarr.open(snakemake.input.vcz, "r")
sync = zarr.sync.ProcessSynchronizer(output_dir)
root = zarr.open(snakemake.input.zarr, "a", synchronizer=sync)
chunk... |
bd575061bf78ad24de8aaa51cf5d95ee9fb5f843500a9ba63e79a906cec43f03 | Python | 2,216 | 58 | from sklearn.model_selection import RepeatedStratifiedKFold
import numpy as np
class StratifiedKFoldHandler:
def __init__(self, n_splits, n_repeats, random_state=None):
"""
Initialize the StratifiedKFoldHandler with RepeatedStratifiedKFold parameters.
Parameters:
- n_splits... |
c5f7d7dfcced2cfe3e52583aa97584d06ae6bb8f7583b679909eb7a4c4fb5250 | Python | 2,216 | 43 | from argschema import ArgSchema, ArgSchemaParser
from argschema.schemas import DefaultSchema
from argschema.fields import Nested, InputDir, String, Float, Dict, Int, Bool
from ...common.schemas import EphysParams, Directories, WaveformMetricsFile
class QualityMetricsParams(DefaultSchema):
isi_threshold = Fl... |
e794b4e79b8f59b924f442251feaa5094a41b44aeea9bc4450eb0964524c762b | Python | 2,216 | 57 | import torch
import tqdm
from pytorch_grad_cam.base_cam import BaseCAM
class ScoreCAM(BaseCAM):
def __init__(
self,
model,
target_layers,
reshape_transform=None):
super(ScoreCAM, self).__init__(model,
target_layers,
... |
0e285ad71c36a1b47700319ea747047758666ea2e03548520fd33d33150ce134 | Python | 2,217 | 72 | #!/usr/bin/env python
"""Report code nothing uses, through deadcode, and fail when there is any.
Exit codes: 0 nothing unused · 1 unused code found, or nothing was checked.
Settings live in `[tool.deadcode]`; rationale for the gate, and for this
wrapper rather than the `deadcode` command: docs/how-to/run-the-checks.md... |
1f9bed86751d0773113eebf7fd9709bbab8946d7158a95d985d12985a2d66205 | Python | 2,219 | 69 | from __future__ import annotations
from typing import TYPE_CHECKING
import pytest
from poetry.repositories.parsers.html_page_parser import HTMLPageParser
if TYPE_CHECKING:
from tests.types import HTMLPageGetter
@pytest.fixture()
def html_page(html_page_content: HTMLPageGetter) -> str:
links = """
... |
2b681db274615466db06fc2a70a89ed9dfd32acb1a013aa3855288eb439f6e49 | Python | 2,220 | 51 | import numpy as np
from typing import Tuple
from matplotlib.collections import LineCollection
def dendrogram(z: np.ndarray, *, leaf_positions: np.ndarray = None, orientation: str = "top", skip_top: int = 0) -> LineCollection:
"""
Create a dendrogram, in the form of a matplotlib LineCollection, in data space, and op... |
76603d15f5526332c41f25fd5317f9adbb15afb365a30ea83e9b60eceaedcac6 | Python | 2,220 | 56 | import ez_setup
ez_setup.use_setuptools()
import setuptools
import os
# Use app's version
import metax
# Use the readme as the long description baked into the application itself
def read(fname):
return open(os.path.join(os.path.dirname(__file__), fname)).read()
setuptools.setup(name="MetaXcan",
... |
7e8e293ceb03cf9a63df9238ca5556983fa5bbdddf6f2d2bfbbabd3a58173ac4 | Python | 2,220 | 56 | """Grounding a tagger's aggregated-axis spans in an external document's own
char offsets: the same window merge `aggregate_embeddings` gives the
embeddings, applied to the stored offset mapping instead, with no BRENDA
mention store consulted."""
import numpy
import torch
from d3text.mention_metrics import PredictedMen... |
01b92ebc107c66b9d2419deab014eb82230d5d4f7fe39deec81203bc9824697a | Python | 2,221 | 71 | from __future__ import annotations
import sys
from pathlib import Path
import pytest
from poetry.utils._compat import is_relative_to
@pytest.mark.parametrize(
("path1", "path2", "expected"),
[
("a", "a", True),
("a/b", "a/b", True),
("a/b", "a", True),
("a", "a/b", False),
... |
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