sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
ae5c2bd68823d24dc475851693a05506a733f2e5a6041b6a6255b708dcea69fa | Python | 2,786 | 61 | """Small, asymmetric DICOM volumes; no patient data or model download required."""
from pathlib import Path
import numpy as np
from pydicom.dataset import FileDataset, FileMetaDataset
from pydicom.uid import ExplicitVRLittleEndian, CTImageStorage, MRImageStorage, generate_uid
ORIENTATIONS = {
"axial": [1, 0, 0, 0,... |
7ee4844ce2863b7fe5b857b4fe38e6e0ff9327fb0899a29d4a8ff0179c43cbe8 | Python | 2,787 | 74 | import h5py
import numpy as np
import tensortools as tt
import pickle
import os
# Set parameters
num_animals = 12
replicate = 0
n_components = [3]
total_runs = 100
for run in range(0, total_runs):
print('Replicate: ', run+1)
print('\n')
output_dir = f"tca_factors"
os.makedirs(output_dir, exist_ok=Tru... |
df2e4a64ed57f38cefacd6715e19b3fc73d2bc7b956a29b12c695fdc5e9392c2 | Python | 2,787 | 65 | #!/usr/bin/env python3
"""Run selected bundled calculation examples in an external result directory."""
from __future__ import annotations
import argparse
from pathlib import Path
try:
from .common import DEFAULT_EXAMPLES, REPO_ROOT, load_cases, metadata_exit_code, resolve_selectors, run_matrix
except ImportErro... |
11a1a48b0330a4872d92b06ff105a1b354c3247baa190d1f6bdc27c35386a658 | Python | 2,788 | 92 | """Download associations from GOlr for a given species."""
from __future__ import print_function
__copyright__ = "Copyright (C) 2010-present, H Tang et al. All rights reserved."
__author__ = "various"
import argparse
import sys
def _get_argparser():
"""Return the CLI argument parser."""
parser = argparse.A... |
2c9217139a79dc8ac8262b03323fd02b9b29dc4f27c69d546a700a9b198f5962 | Python | 2,788 | 64 | #!/usr/bin/env python3
"""R1 ponto 5 (definir eta^2 e rho) e R1 ponto 4 (os 34 gaps negativos por par F-X).
Recalcula eta^2 pela ANOVA de um fator para conferir os valores da Tabela 3 e fixar a
definicao que entra no texto, e confere que o rho das Tabelas 4 e 1/7 e de SPEARMAN.
"""
import csv, json, re
from collection... |
0b2645e600b0af2d9793dfd3f5e31f2b64e12ab6d5682703930d71b66f4b4ad8 | Python | 2,790 | 77 | """TweetyNet model [1]_.
.. [1] TweetyNet was described in:
Cohen, Y., Nicholson, D. A., Sanchioni, A., Mallaber, E. K., Skidanova, V., & Gardner, T. J. (2022).
Automated annotation of birdsong with a neural network that segments spectrograms. eLife 11: e63853.
Paper: https://elifesciences.org/articles/63853
... |
0da71350fe0f69923d04d24a394beb37115d30d19678af28a9629fc7d0713d1d | Python | 2,793 | 102 | import gc
import math
from typing import Dict, List, Mapping, Optional, Tuple, Any, Union
import warnings
import torch
from torch import nn, Tensor
from torch.nn import TransformerEncoder, TransformerEncoderLayer
class CancerGPT(nn.Module):
def __init__(
self,
ntoken: int,
d_model: int,
... |
cc4278c80ca11c8d57709a9269c461cc3907a774f9e5f52160a5b9404513a382 | Python | 2,793 | 92 | # inspired by
# https://github.com/yuanli2333/CKA-Centered-Kernel-Alignment/blob/master/CKA.py
import math
import torch
import numpy as np
class CKA(object):
def __init__(self):
pass
def centering(self, K):
n = K.shape[0]
unit = np.ones([n, n])
I = np.eye(n)
H = I... |
3902b1d0d9a8cd6c128ded6e624391b7c47864998cf6f4d39d8f40dff824dfda | Python | 2,794 | 89 | from __future__ import annotations
import os
import platform
import site
import sys
import sysconfig
from pathlib import Path
from typing import TYPE_CHECKING
from packaging.tags import Tag
from packaging.tags import interpreter_name
from packaging.tags import interpreter_version
from packaging.tags import sys_tags
... |
19f13738d63856c850d048f1298ddda610ccae24f5facf80214b3f6eec544242 | Python | 2,795 | 85 | # /usr/bin/env python
'''
Written by Kong Xiaolu and CBIG under MIT license:
https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
'''
import numpy as np
import torch
import os
import scipy.io as sio
import CBIG_pMFM_basic_functions as fc
def CBIG_mfm_validation_desikan_main(gpu_index=0):
'''
This func... |
885a6d6f9f8f4874a1d44555b29ce190d98811ebb9bbc0abc44a886d6ad94abd | Python | 2,796 | 88 | import logging
from typing import Dict, List, Optional
import haiku as hk
import jax
import jax.numpy as jnp
from haiku import initializers
from typing_extensions import TypeAlias
from nucleotide_transformer.heads import UNET1DSegmentationHead
SequenceMask: TypeAlias = jnp.ndarray
logger = logging.getLogger(__name... |
0ead9200c1e8a1ced607c033d618468b0eea764b41be0e3b516999ec793727b5 | Python | 2,798 | 86 | #!/usr/bin/env python3
# MIT License
#
# Copyright 2022 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 use... |
3ae95a98af050435dd7e3bfbe9f867b149a4500d4921ac60a556820899daede4 | Python | 2,799 | 80 | """Landscape interface for the BO loop.
Reads fitness from CSV, writes proposed sequences to CSV.
Acts as the communication channel between the BO engine and external scoring.
"""
import os
from typing import Sequence
import numpy as np
import pandas as pd
from Bio import SeqIO
class EXPLandscape:
"""CSV-based ... |
2c571113a305a0d26b4eb64fed5e831c2b4c56f169cd8cff082cc4a5195c2ce3 | Python | 2,800 | 94 | #!/usr/bin/env -S uv run --script
# /// script
# requires-python = ">=3.12"
# dependencies = [
# "numpy",
# "crackle-codec",
# ]
# ///
# @license
# Copyright 2026 William Silversmith
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the Lice... |
72265bcd7a27436a185b03553cfe165ec732ad7f5173eaa7ddd96579441cf032 | Python | 2,800 | 71 | from functools import partial
import jax
import jax.numpy as jnp
import pytest
from oneqmc.data import as_dict_stream, as_mol_conf_stream, simple_batch_loader
from oneqmc.device_utils import DEVICE_AXIS
from oneqmc.sampling.multi_system_sampler import NaiveMultiSystemSampler
from oneqmc.sampling.samplers import OneSy... |
e35e9efae7d097b3d358531e624349cddc9a33ab6469f0fbadaaa1e045dea003 | Python | 2,800 | 102 | """
Nodes that implement the dHCP pipeline for fetal data.
Version from <https://github.com/GerardMJuan/dhcp-structural-pipeline>
, which is a fork of the original dataset
<https://github.com/BioMedIA/dhcp-structural-pipeline>
with several fixes and changes
The docker image, where everything works "well", is:
<https:... |
5c7361298a41265620b7b4c353dd7e1328f7c9385920568daba86682f0ebccfa | Python | 2,801 | 93 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Simple, generic tools"""
from typing import Optional
import warnings
import numpy as np
from .models import Cell, Region
def retrieve_cell_region_uid(objs: list, uid: int) -> Optional[Cell | Region]:
"""Returns cell or region with requested uid from list"""
... |
d5dd878ad1562991760d798649381ddf1d9ff18334f6f658875bc144fdf4179a | Python | 2,802 | 88 | #!/usr/bin/env python3
import argparse
import functools
import os
import pickle
import shutil
import sys
import yaml
import h5py
import numpy as np
import medaka.features
import medaka.labels
import medaka.models
def main():
parser = argparse.ArgumentParser(
description='Update a pre-version-0.9.0 mode... |
307f8856f69502ee4801832a32030667622f2e0e07e4a3f5ee66b1d6cb99387a | Python | 2,805 | 88 | from __future__ import annotations
from typing import TYPE_CHECKING
from typing import Any
from poetry.utils.env.null_env import NullEnv
if TYPE_CHECKING:
from packaging.tags import Tag
from poetry.utils.env.base_env import MarkerEnv
from poetry.utils.env.base_env import PythonVersion
class MockEnv(N... |
560e55350fe52380e36b68b311f305e7563831741ece47cfbef13b45b6cfa5f4 | Python | 2,810 | 101 | """Plot a GO term lineage using the GODag drawing helpers."""
__copyright__ = "Copyright (C) 2010-present, H Tang et al. All rights reserved."
__author__ = "various"
import argparse
import os
from ..obo_parser import GODag, GraphEngines
def _get_argparser():
"""Return the CLI argument parser."""
parser = a... |
eac1a50630a116e7fea407e0e5fd6cb8432d53cc869e760d5153fd175ca07f6a | Python | 2,810 | 73 | """Power-law analysis for E_total(L) and E/N(L) on percolation clusters.
Two regimes are interesting:
(a) Total energy: E_total ~ L^{D_E} with D_E ≈ D_f = 91/48 ≈ 1.896
(extensive part of the energy ∝ cluster mass).
(b) Per-atom energy: E/N − ε_bulk ~ L^{−α}
with α expected in [|D_h − D_f|, |D_e ... |
aa5376a85ee856c6b4d0ead77392e9e1b3fdf3ec418e815962a0b92717dd48c3 | Python | 2,814 | 85 | from __future__ import annotations
from pathlib import Path
from typing import Any
import pandas as pd
from st_risk.data.io import open_h5ad
from st_risk.models.base import BaseSpatialModelOutput, BaseSpatialModelRunner
class PrecomputedTableRunner(BaseSpatialModelRunner):
model_name = "precomputed"
def i... |
4c3207841e79e25c3c46662df0a7ef08d91a8f4f6af6474c75269776f5682e9d | Python | 2,816 | 81 | #!/usr/bin/env python
# Copyright (c) 2017-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
# NOTE: This requires PyTorch! We do not provide installation scripts to install PyTorch.
# It is up t... |
511fbc83198db1a7c54c83f6003f01725dc691167f38afe56d5da44e509e1039 | Python | 2,816 | 95 | import mudata
import numpy as np
import pytest
import scvi
from scvi.data import synthetic_iid
from scvi.external import Tangram
modalities = {"density_prior_key": "sp", "sc_layer": "sc", "sp_layer": "sp"}
def _get_mdata(sparse_format: str | None = None):
dataset1 = synthetic_iid(batch_size=100, sparse_format=s... |
0a618aa0fc5312bd0fe6ce7cadc0ae4ba08fe2cff05febf0dc5b9231fcf73c8e | Python | 2,817 | 96 | from __future__ import annotations
import os
from typing import TYPE_CHECKING
from typing import ClassVar
from cleo.helpers import argument
from cleo.helpers import option
from packaging.utils import canonicalize_name
from poetry.config.config import Config
from poetry.console.commands.command import Command
from p... |
da06fe0c81ce2ba2c153d4e4cdfc360ee9ef69ec7941e8d2e3b42b8c5a0da600 | Python | 2,817 | 84 | import os
from pathlib import Path
import torch
from utils.data.dataholder import DataHolder
from utils.data.misc import to_batch
def on_test_epoch_start_func(self) -> None:
"""Reset test metrics and prepare output directory."""
self.test_step_outputs = []
save_dir = self.cfg.test.save_dir or "test_outpu... |
f041c05493b61d5d312c4206255f0e9d64dba430dab3fe3dc97f283d7722709d | Python | 2,819 | 75 | # -*- coding: utf-8 -*-
"""
Created on Fri May 3 14:54:08 2019
@author: Patrick Cody | pac94@pitt.edu | pcody1@gmail.com
"""
#based upon: https://rochefort-lab.github.io/fissa/examples/cNMF%20example.html
#%% INPUT PARAMS
###################### ONLY EDIT THIS (after 'r') #########################
#a... |
31575be097ab964baa3f92b001eca3d1482c0cd6549c7afc509a553cfe57d09e | Python | 2,821 | 73 | """Run SIESTA SZP on the 50 active-learning iter-3 (non-strain) picks."""
from __future__ import annotations
import argparse
import json
import sys
import time
from concurrent.futures import ThreadPoolExecutor, as_completed
from pathlib import Path
from ase import Atoms
ROOT = Path(__file__).resolve().parents[2]
sys... |
3eb34442ca9b4974363b4f89c9e44bb8b77f1b687184bb70522d2b747a2c2a9d | Python | 2,821 | 70 | from os.path import join, dirname
import numpy as np
import pandas as pd
from sklearn.model_selection import train_test_split
current_dir = dirname(__file__)
input_dir = 'raw_data'
output_dir = 'splits'
input_dir = join(current_dir, input_dir)
output_dir = join(current_dir, output_dir)
def get_response():
filen... |
f6a84cfbb90eca254a43c8a941151c4856fb43eecc51883476cbe2bb98514146 | Python | 2,821 | 73 | """Run SIESTA SZP on the 50 active-learning iter-2 (non-strain) picks."""
from __future__ import annotations
import argparse
import json
import sys
import time
from concurrent.futures import ThreadPoolExecutor, as_completed
from pathlib import Path
from ase import Atoms
ROOT = Path(__file__).resolve().parents[2]
sys... |
29dc5274fdcd2998aa5126dafeb7974665bbf440af96516f6b1de19fbaf2090e | Python | 2,825 | 89 | # Copyright 2016 Google Inc. All Rights Reserved.
#
# 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 a... |
35b2709eaa5cb3a92bbcc28333b61aafe1fa36e42e45dbbbecb809cb4a1a751c | Python | 2,825 | 96 | # -*- coding: utf-8 -*-
"""
Created on Mon Aug 26 22:18:56 2019
@author: 俊男
"""
# In[] KMeans
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import time
from sklearn.cluster import KMeans
from sklearn.preprocessing import MinMaxScaler
class KMeansCluster:
__cluster = None
__best_k =... |
a6cf052e86de3f6819a2defdcacc7724380ca1b6c5213b76c68af86681e88653 | Python | 2,827 | 72 | import torch
from torch import nn
from ..downstream_module import DownStreamModule
class SelfAttention(DownStreamModule):
"""
contact predictor with attention
"""
def __init__(self, backbone_args, backbone_alphabet, num_classes, symmetric=False, depth_reduction="mean"):
"""
:param depth... |
a10fb087023026940105fe2442c9d770ecbba8fb918b507c4fc8693fe946e684 | Python | 2,828 | 88 | import pytest
import torch
import vak.metrics.boundary_detection
from .conftest import PRECISION_RECALL_FSCORE_RVAL_TEST_CASES
@pytest.mark.parametrize(
'test_case',
PRECISION_RECALL_FSCORE_RVAL_TEST_CASES,
)
@pytest.mark.parametrize(
'metrics',
[
"precision",
"recall",
"fsco... |
e8a956d87533de74efc7227183c9d9e4923012c35b18b98f155e7fbeb0a87b84 | Python | 2,829 | 87 | """U-Net for dense segmentation (with optional bilinear upsampling)."""
import torch
import torch.nn as nn
import torch.nn.functional as F
class SingleConv(nn.Module):
"""Convolution => BN => ReLU => Dropout."""
def __init__(self, in_channels, out_channels):
super().__init__()
se... |
0bc1e35bc30af26820833d7de55067fdfba900cdad71e71c2e7330acc0ab500b | Python | 2,830 | 104 | from __future__ import annotations
from typing import TYPE_CHECKING
from typing import Any
from typing import cast
from poetry.core.poetry import Poetry as BasePoetry
from poetry.__version__ import __version__
from poetry.config.source import Source
from poetry.pyproject.toml import PyProjectTOML
if TYPE_CHECKING:... |
50b5c8366a86b91a08eff9e0bae452d11e4b9a5993b9aa7eff29e3fc6bf08645 | Python | 2,830 | 93 | __author__ = 'heroico'
import sqlite3
import numpy
from .. import KeyedDataSet
from .. import Exceptions
import os
class DBLoaders(object):
@classmethod
def loadKeyedDataSetFromDB(cls, db_path, table_name, key_column, value_column):
if not os.path.exists(db_path):
raise Exceptions.BadFil... |
5782b04d3fd0414c799ca3224294b0a4c695aaa6b559460d650a82dc4a743b1d | Python | 2,831 | 139 | # -*- coding: utf-8 -*-
"""
Created on Thu May 8 17:56:53 2025
@author: hanna
"""
"""
Main script for executing all processing scripts on (sample) data
[Step 1] process behavioral+neural data files (.hdf) & decoder files (.pkl).
[Step 2] determine trial lengths for each trial
[Step 3] compute behavior... |
a46118e8df73a76d5e5e212a24eb384233ef5702955c37b284a8a977c96a6e77 | Python | 2,831 | 47 | #!/usr/bin/env python
'''
(c) 2016-2020 Oleksandr Frei, Alexey A. Shadrin, Dominic Holland
MiXeR software: Univariate and Bivariate Causal Mixture for GWAS
'''
import logging
import sys
import argparse
import common.utils_cli
import bivar_mixer.figures
from version import VERSION as __version__, MASTHEAD
if __name_... |
394e75709d8c48d3eade2e5fabf563fa757d399fa85f42cda3fc9d2a593b8686 | Python | 2,834 | 78 | # -*- coding: utf-8 -*-
# Copyright (C) 2023 Phillip Alday <me@phillipalday.com>
# License: BSD (3-clause)
"""Savitzky-Golaf IAF tests."""
from nose.tools import assert_raises, assert_sequence_equal
from philistine.mne import attenuation_iaf, savgol_iaf
from philistine.mne.utils import _generate_raw
def test_basic_... |
b831f5e2f8aa87a3e471fca7a5952206e1531e8aec5c6311b0210d3d347f74fa | Python | 2,835 | 63 | #!/usr/bin/env python -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.
import argparse
import soundfile as sf
import tempfile
from pathlib import Path
import os
import subprocess
import sy... |
268e1a85441029b7fee4f91cb5f34f903315a66dfbc7824eeb484a68484a9349 | Python | 2,838 | 92 | from __future__ import annotations
import os
import re
import subprocess
from typing import TYPE_CHECKING
from typing import Any
from poetry.utils._compat import WINDOWS
from poetry.utils.env.virtual_env import VirtualEnv
if TYPE_CHECKING:
from pathlib import Path
from poetry.utils.env.base_env import Env... |
54dc36107d06636d829d21ae0ad345a80e3aeae4982fda3f736100e252c73329 | Python | 2,838 | 76 | from __future__ import annotations
from os.path import join
import pytest
import torch
from scvi.nn import Embedding
@pytest.mark.parametrize("num_embeddings", [10])
@pytest.mark.parametrize("embedding_dim", [5])
@pytest.mark.parametrize("init", [2, [0, 1]])
@pytest.mark.parametrize("freeze_prev", [True, False])
d... |
ac6b82704dc8d3f4e8f0803d87b2b9d96c4e4eadf7f1805bc08dce66b66adf2c | Python | 2,838 | 92 | __author__ = 'heroico'
import numpy
import logging
import Utilities
import Exceptions
class MTF(object):
"""Matrix table format"""
GENE = 0
RSID_1 = 1
RSID_2 = 2
VALUE = 3
def loadMatrixFromFile(file):
class MatrixBuilder(object):
def __init__(self):
self.build_up = {}
... |
790add6776f3580fda15244b7e4ac31002e14f08e3b3cd71a5a23b28de7400eb | Python | 2,842 | 71 | import pandas as pd
import os
def get_events(edfpath,contains_regex=None,min_dur=None,max_dur=None,min_onset=None,max_onset=None):
from mne.io import read_raw_edf
# Load annotations from .edf file
annots = read_raw_edf(edfpath,
preload=False, verbose='ERROR'
... |
a9c4c0ae777673712ff17ee2bb425d0eda26ef55ea7fc74e6e78199937c8047a | Python | 2,842 | 80 | # Copyright 2017 Google Inc. All Rights Reserved.
#
# 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 a... |
35cae684701b08981c46bb4a3096428c747ea59599413259169d96fbb13bba03 | Python | 2,843 | 79 | #!/usr/bin/env python
# PYTHON_ARGCOMPLETE_OK
"""Launches the MDT maps visualizer."""
import argparse
import os
import textwrap
from argcomplete.completers import FilesCompleter
from mdt import view_maps
from mdt.visualization.maps.base import SimpleDataInfo
from mdt.lib.shell_utils import BasicShellApplication
__auth... |
d0ff9b8a23d20c24c8f15c2582f93c57b31b63236ed46167b783e0d0f225bbbd | Python | 2,844 | 83 | import functools
from typing import Any, Callable, Sequence, TypeVar
import jax
import jax.numpy as jnp
import jax.tree_util as jtu
F = TypeVar('F', bound=Callable)
def batched_vmap(
fn: F,
max_batch_size: int,
in_axes: int | None | Sequence[Any] = 0,
out_axes: Any = 0,
) -> F:
if isinstance(in_... |
fdcf8bc77e66c44a7eee81bcb87d7ffb1dce3729fbb452f3cf762e71a9a1ec79 | Python | 2,846 | 90 | """Tests for ``aestetik.utils.utils_data`` (prepare_input_for_model,
build_grid, calibrate_transcriptomics_morphology_ratio).
"""
from __future__ import annotations
import numpy as np
import pytest
from aestetik.utils.utils_data import (
build_grid,
calibrate_transcriptomics_morphology_ratio,
prepare_inpu... |
c9683fbaba45d210185bd98c76937e6a5f1da5821e4c1d8ca53925b0701d8a2f | Python | 2,847 | 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 fairseq.model_parallel.modules import ModelParallelMultiheadAttention
from fairseq.modules import TransformerDecoderLayer, TransformerEnc... |
41ad9cb2adb688ac66f2272a73a59f3ef39dbc6523c403719f9e5cd57e42f121 | Python | 2,848 | 87 | import re
from typing import Collection, Iterator
from brenda_references.config import config
from taxonomy import ncbitax
from tinydb import TinyDB
from tinydb.middlewares import CachingMiddleware
from tinydb.storages import JSONStorage
from tinydb.table import Document, Table
from tqdm import tqdm
def strain_queri... |
c04ad2aa394b430a2be8d8c8a0dc446c94699f3654909f8e516105c6117fd4b7 | Python | 2,849 | 86 | from pathlib import Path
import re
import tempfile
INCLUDE_RE = re.compile(r'^(\s*#include\s+)([<"])([^>"]+)([>"])(.*)$')
def comment_gromacs_cmap(line, in_cmap=False):
stripped = line.lstrip()
active = bool(stripped) and not stripped.startswith(';')
section = re.match(r'\[\s*([^\]]+?)\s*\]', stripped) ... |
03cfc56af928a386489b75ce3a229c0598e9a85abac44ba87346afd7deb5043e | Python | 2,850 | 83 | import gzip
import io
import pandas
import logging
from .. import Utilities
def data_frame_streamer(path, sentinel_column, sentinel_white_list=None, sentinel_suffix=None, additional_skip_row_check=None):
_check_sentinel(sentinel_white_list, sentinel_suffix)
found = set()
def _ogz(p):
return io.T... |
d1851753b1c74bf0352ff5b6229ad559902b302e295bb41633142dafe9c03be2 | Python | 2,850 | 85 | # 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.nn as nn
from fairseq.models import FairseqEncoder
from fairseq.modules import LayerNorm, TransformerEncoderLayer
class Transf... |
6e76fc0a7a3831c01cfffd18c220d44438073a66338d91ca61fc84b924021e61 | Python | 2,851 | 78 | #!/usr/bin/env python
#
# Copyright 2009, Google Inc.
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met:
#
# * Redistributions of source code must retain the above copyright
# notice, this list... |
a799fd016d6fd35993da8510911ea87410ef1ca40e3dd7b9eeb9dd5b45da60e6 | Python | 2,853 | 98 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Copyright (c) 2017-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from __future__ import absolute_import
from __future__ import division
from _... |
e5ebe90066461ce4ecc555e64ecf60c5a41e65483448be53cd828ad8d077442e | Python | 2,856 | 75 | """Argparse `type=` callbacks and defaults shared by more than one CLI."""
import argparse
import pathlib
from collections.abc import Sequence
def non_negative_limit(value: str) -> int:
"""Reject a negative `--limit` before it reaches the corpus loaders.
`load_split` refuses one too, but a `ValueError` out ... |
04021f06d61a043f4fdac98ea3fd7c35c705ce0550f2fa0f52377ed8d2ecd032 | Python | 2,857 | 93 | # @license
# Copyright 2023 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... |
e333ee4ebd6ff4d4420cbcff6d52cf4a3118c6e1de3b55563cf6d637efce65cc | Python | 2,857 | 63 | import torch.nn as nn
import torch
import torch.nn.functional as F
import config.cfg_lodet as cfg
class MSigmoid_approx(nn.Module):
def __init__(self):
super(MSigmoid_approx, self).__init__()
def forward(self, input):
return (torch.clamp(torch.sigmoid(input),0.011,1)-0.01)/(1-0.01)
class DSC_H... |
a73b15a3803c12d078a1064710cd88b70f8d12330ef2cf7b6655c7b2d569bcd8 | Python | 2,858 | 65 | import torch
from batchgenerators.utilities.file_and_folder_operations import save_json, join, isfile, load_json
from nnunetv2.training.nnUNetTrainer.nnUNetTrainer import nnUNetTrainer
from torch import distributed as dist
class nnUNetTrainerBenchmark_5epochs(nnUNetTrainer):
def __init__(self, plans: dict, confi... |
da941fafe60a8037b3d8f963356635dcbe2f956224e18c2918cdcb5b3fc14179 | Python | 2,859 | 90 | import os
import unittest
from unittest.mock import patch
from pyecharts.datasets import (
EXTRA,
FuzzyDict,
register_url,
register_files,
register_coords,
)
class TestDatasets(unittest.TestCase):
@patch("pyecharts.datasets.urllib.request.urlopen")
def test_register_url(self, fake):
... |
e5d57dabdc08e5a576bbed7b23ef705669246ac0a764989a5bc939ad8963f6e9 | Python | 2,860 | 132 | import argparse
import csv
import os
import h5py
import numpy as np
import random
from process_pretrain_data import get_kmer_sequence
from multiprocessing import Pool
def generate_example(X, Y, kmer, index):
# assert X.shape[0] == Y.shape[0]
lines = []
for j in range(len(X)):
if j % 1000 == 0:
... |
511d10ad81998ce123213460dc08ab134d6ace7c5228568830e8c620eabdd00c | Python | 2,861 | 49 | from argschema import ArgSchema, ArgSchemaParser
from argschema.schemas import DefaultSchema
from argschema.fields import Nested, InputDir, String, Float, Dict, Int, NumpyArray
from ...common.schemas import EphysParams, Directories
class NoiseWaveformParams(DefaultSchema):
classifier_path = String(required=True, ... |
7ec554052ead2f6e9dd218b63e9a4c34209eeac523af7aad9325440f581eedcb | Python | 2,864 | 92 | from __future__ import annotations
from typing import TYPE_CHECKING
from typing import ClassVar
from cleo.helpers import argument
from cleo.helpers import option
from poetry.console.commands.init import InitCommand
if TYPE_CHECKING:
from cleo.io.inputs.argument import Argument
from cleo.io.inputs.option im... |
ff876a3d5f3e6349093293ab7b72000c34a6e024e86c4644408bb3409980a5f5 | Python | 2,866 | 84 | """`brenda_references` must declare no console script it cannot ship.
The shim runs with the venv's `bin/` as `sys.path[0]`, so the module has to be
part of the installed distribution. This package is src-layout: its editable
install puts `brenda_references/src` on `sys.path`, which leaves the sibling
`scripts/` reach... |
5482a875a65cb985b7e93cd1f3685e0cdc5a1819e711518e137695e71a3c07eb | Python | 2,867 | 68 | # -*- coding: UTF-8 -*-
"""
@Project: iDCF
@File : main.py
@IDE : PyCharm
@Author : hjguo
@Date : 2025/7/9 11:35
@Doc : Main function
"""
import os
import torch
import pandas as pd
from iDCF.utils import load_data, load_data_from_path, load_knowledge
from iDCF.train import train, prediction
def main(data_na... |
188077e0f50222357dcc9cf27b1ff44f41267d030e6ba68c67beb525cb48a74d | Python | 2,868 | 82 | import itertools
import pandas as pd
def load_TREC_data(input_path: str) -> pd.DataFrame:
trec_df = pd.read_csv(input_path, delimiter="\t", names = ["Topic", "Zeros", "PMID", "Relevance"], usecols=["Topic", "PMID", "Relevance"])
return trec_df
def get_unique_topics(trec_df: pd.DataFrame) -> list:
# Get u... |
d203dd1a01dfd118517d0a9c6cdd9387a9a86b70df44daf9e80009da8fc5b28d | Python | 2,868 | 86 | import numpy as np
from typing import Union
def grid_xyz(dx, grid_size):
return np.meshgrid(
np.arange(grid_size[0], dtype=np.float32) * dx,
np.arange(grid_size[1], dtype=np.float32) * dx,
np.arange(grid_size[2], dtype=np.float32) * dx,
indexing='ij'
)
def sphere_m... |
9b6cb457df87a154f306057a80a4223a6a20e918397a56239398c43eca1a1a67 | Python | 2,869 | 99 | # 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 collections import defaultdict
import numpy as np
from misc.bleu_utils import sentence_bleu
import json
import warnings
def get_args()... |
fd417fef562019a14335a8c7b850912c54e6ebd34cb8c2f7e52e22d667f8d190 | Python | 2,869 | 90 | #!/usr/bin/env python
# Written by Senthilkumar Panneerselvam and released under the MIT license.
import argparse
import logging
import os
# Create a logger
logging.basicConfig(format="%(name)s - %(asctime)s %(levelname)s: %(message)s")
logger = logging.getLogger(__file__)
logger.setLevel(logging.INFO)
mqc_main = "... |
904a80a46a577b93d47c15406b5e994423dcfe132bdd8ab51f22f180188ff3e2 | Python | 2,872 | 79 | #!/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 use... |
0b8968547d53b008b0f331068706e410eebf9731faf7cf8f8d01dc370b3cd0b7 | Python | 2,873 | 65 | # Copyright 2020 The Lucent Authors. All Rights Reserved.
#
# 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 ... |
3ef99390f61409e932993586eccd7296755e313a005bf1eb0a17f48d8feb3e3c | Python | 2,873 | 93 | # This script reformats the output of IUPred2A to be compatible with IsoformAnalyzeR
from src.utils import read_gtf
from io import StringIO
import polars as pl
def split_and_insert(list_A, list_B):
result = []
header_index = 0
if header_index < len(list_B):
result.append(">" + list_B[header_index])... |
9f73a504c76cf1d1070da1c9bbee0e847784ab66bf79eca0b85ac8d7069c2d7a | Python | 2,873 | 82 | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
from typing import Optional, Tuple, Union
import torch
from mattergen.diffusion.corruption.sde_lib import SDE, VESDE, VPSDE
from mattergen.diffusion.data.batched_data import BatchedData
B = Optional[torch.LongTensor]
def wrap_at_boundary(x: ... |
cd79a1d5b8c7714638cdf63fc65e587aef3009f34dc2e133bac3f2c440515878 | Python | 2,874 | 100 | import torch
import torch.nn as nn
def conv3x3(in_planes, out_planes, stride=1):
"3x3 convolution with padding"
return nn.Conv2d(in_planes,
out_planes,
kernel_size=3,
stride=stride,
padding=1,
bias=False)
... |
74047b15536e9af31e97dce1037f8c386a927fb6f4761e5e5df5a0d123e0aea7 | Python | 2,877 | 67 | import importlib.util
import os
from pathlib import Path
import struct
import subprocess
import sys
import tempfile
import unittest
ROOT = Path(__file__).resolve().parents[1]
spec = importlib.util.spec_from_file_location('windows_pe', ROOT / 'tools/windows_pe.py')
windows_pe = importlib.util.module_from_spec(spec)
spe... |
5319cc584c34a6a19bb9b4d67c26b036407e927b560ccb42c3f8f700dfb16bd8 | Python | 2,878 | 68 | # -*- coding: utf-8 -*-
"""
.. _tutorial02_ref:
Tutorial 2: Types of Surfaces
=============================
This tutorial covers what types of surfaces that can be plotted with
``surfplot``.
Types of surfaces
-----------------
Put briefly, ``surfplot`` can take file paths to any valid surface file(s)
with geomet... |
98f5c06c20e0b55562a1e69a3fefbb2307d4145ae2353cae2ac0c4cd352402b6 | Python | 2,878 | 70 | #!/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 use... |
30756ffbd318aebdf7aaf7d069f5f14f4d433d830141d92a620a2f8d51aa939a | Python | 2,881 | 100 | import torch
import wandb
from metrics.evaluation_statistics import compute_RSSD
from utils.data.dataholder import DataHolder
from utils.data.misc import to_batch
def on_validation_epoch_start_func(self) -> None:
"""
Callback function called at the start of each validation epoch.
Returns:
- None
... |
6a49123b80ee112b33f9c2a24639ab0cd08c38a8a35ac3c0b162c92a4cec5891 | Python | 2,881 | 96 | import time
import RPi.GPIO as GPIO
class mainprogram:
#Main while loop condition
keepalive = True
# DEFINE NUMBER OF BUTTONS AND ORDER IN ARRAY
buttonarray = ['movefast', 'bregmahome', 'relativeML', 'relativeAP', 'moveslow',
'HomeToABSzero', 'recalibrate', 'miscbuttonA', 'presetwor... |
b48de242514095d5e593c718a212f68024f647af4223feb431e9dece66d1c158 | Python | 2,881 | 88 | #!/usr/bin/env python
# Author: Jin Lee (leepc12@gmail.com)
import sys
import os
import argparse
from encode_lib_common import (
mkdir_p, log, ls_l, rm_f, strip_ext_fastq)
from encode_lib_genomic import (
get_read_length, remove_chrs_from_bam, samstat, samtools_index)
def parse_arguments():
parser = arg... |
6d6c7eccce21ca33757752b21a363722cd68093fdb5aa1d40ac47a37678640b4 | Python | 2,882 | 58 | import torch
from torch.optim import Adam, AdamW
from nnunetv2.training.lr_scheduler.polylr import PolyLRScheduler
from nnunetv2.training.nnUNetTrainer.nnUNetTrainer import nnUNetTrainer
class nnUNetTrainerAdam(nnUNetTrainer):
def configure_optimizers(self):
optimizer = AdamW(self.network.parameters(),
... |
ba32e856d48f04d29f3bbaf4ab10e07094b364e6e85477c18d3fb68ee0466b14 | Python | 2,882 | 75 | from sklearn.neighbors import NearestNeighbors
import numpy as np
import pandas as pd
def calc_neighbor_prop(
adata,
batch_key='replicates',
celltype_key='Cluster',
n_neighbors=25,
spatial_key='spatial',
output_key=None
):
"""
Normalize the cell ty... |
5b8241fed91ef64a696503dcff8d083d873b5916d38ca8c30214bf6245465b4f | Python | 2,883 | 89 | # encoding: utf-8
"""
@author: Jiayang Chen
@contact: yjcmydkzgj@gmail.com
"""
from .datasets import build_dataset
from .transforms import build_transforms
from .samplers import build_sampler
from .collate_function import build_collate_fn
from torch.utils.data import DataLoader
def find_dataset_type(dataset_name):... |
dc3fc6f71be5d9ded39a408822b591ba3cf57f696e7d4651bc40e97710b4ee2a | Python | 2,884 | 74 | import numpy as np
import pandas as pd
from sklearn import metrics
import scanpy as sc
import ot
from sklearn.decomposition import PCA
def mclust_R(adata, num_cluster, modelNames='EEE', used_obsm='emb_pca', random_seed=12345):
"""
Performs clustering using the Mclust algorithm in R.
Thi... |
89d13e41635524edc7776802b83998ee39d73ee8c120cbe276a10084024b6fa4 | Python | 2,893 | 85 | """
01_pcdh_coexpression.py
Within-region protocadherin co-expression analysis (Table 1).
Computes Pearson and Spearman correlations between all PCDH gene pairs
within each of 13 GTEx brain regions.
Harbert D. (2026) BMC Genomics
"""
import sys, os
sys.path.insert(0, os.path.dirname(__file__))
from utils import *
d... |
01ff7098c342fda86a1eeaeb414be414c438d4bb937c348f07b49b99daffc706 | Python | 2,894 | 118 | """FISSA functions to handle image and roi objects and return the right format.
If a custom version of this file is used (which can be defined at the
declaration of the core FISSA Experiment class), it should have the same
functions as here, with the same inputs and outputs.
Authors:
Sander W Keemink <swkeemink@s... |
0b03c299122823d95b59ce9d925bde5b03da617e790a9337437a443ffa620fd4 | Python | 2,894 | 107 | import torch.nn as nn
import torch.nn.functional as F
from .resnet3d import BasicBlock3D, Bottleneck3D, ResNet3D
__all__ = ["FastNet", "resnet18_fast", "resnet50_fast"]
class FastNet(ResNet3D):
def __init__(
self,
block,
layers,
fusion_kernel_size=(5, 1, 1),
fusion_stride... |
3554a1b830b0211a271294b4669513b1e057b76e2de8fbe5d1ca48ea5605ccea | Python | 2,894 | 98 | # -*- coding: utf-8 -*-
"""
@Time:Created on 2019/9/25 10:03
@author: LiFan Chen
@Filename: main.py
@Software: PyCharm
"""
import torch
import numpy as np
import random
import os
import time
from model import *
import timeit
import pickle
def shuffle_dataset(dataset, seed):
np.random.seed(seed)
np.random.shuf... |
3ac0952292d835ebd356011143ab4916c5160af13e182eefeb327361ff28df1b | Python | 2,894 | 74 |
import numpy as np
from spacestream.core.constants import ROI_NAMES
STREAM_NAMES = ROI_NAMES[-3:]
def prep_smoothness(
mapping, scaled_target_distances, scaled_source_distances, HVA_idx, by_stream
):
if HVA_idx is None:
unit_idx = np.arange(0, len(mapping["winning_idx"]))
else: # voxel2voxel H... |
0c95772341a0b1781505a8cf5d5d15e61b5232cb0a9e7bec1da3f873d3a5b1d6 | Python | 2,895 | 69 | from src.utils import read_gtf
import polars as pl
def main():
annot_peptides_hybrid = read_gtf("nextflow_results/V47/orfanage/annot_peptides_hybrid.gtf", attributes=["gene_name", "transcript_id", "detected", "type", "novelty"])
gencode = read_gtf("/Users/xunuo/Genomic_references/GENCODE/gencode.v47.annotation... |
32b5976263d948fc2c4c8f7b137c45a6ec7e2350d331c57c2997e4ba6fefb0bb | Python | 2,895 | 76 | from mdt import CompartmentTemplate, FreeParameterTemplate, LibraryFunctionTemplate
__author__ = 'Robbert Harms'
__date__ = '2019-11-14'
__maintainer__ = 'Robbert Harms'
__email__ = 'robbert@xkls.nl'
__licence__ = 'LGPL v3'
class CylindersPoissonDistr(CompartmentTemplate):
"""Poisson Distributed Radii cylinders,... |
c36fa09cc4b8f21d337edd934b5e1931072ed81ec07766af79cfd2d7db343eb3 | Python | 2,895 | 65 | from functools import lru_cache
import numpy as np
import torch
from typing import Union, Tuple, List
from acvl_utils.cropping_and_padding.padding import pad_nd_image
from scipy.ndimage import gaussian_filter
@lru_cache(maxsize=2)
def compute_gaussian(tile_size: Union[Tuple[int, ...], List[int]], sigma_scale: float ... |
fc6e1f097b1d9d41fce8665496ef4c45fec51198b57428ed71033633ce6f76ab | Python | 2,895 | 71 | # 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 fairseq.search import Search
class NoisyChannelBeamSearch(Search):
def __init__(self, tgt_dict):
super().__in... |
3e2136f95c97996101692cb1069d5a99105bb5d1aee2a207b560a355247a7618 | Python | 2,896 | 54 | #!/usr/bin/env python3
"""Build figure-adapter tables from the complete-case (no-imputation) proteomic re-analysis.
Rationale: MinProb imputation assumes missingness is left-censored (MNAR) and fills absent
values with low intensities. Where missingness differs between groups this manufactures an
effect. ITGB2 in the ... |
69a225470dd7292b1fe5e0ce9c49b35f58119c574111dd835bee8027f0949e44 | Python | 2,896 | 87 | # 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 unittest
from argparse import ArgumentParser
from dataclasses import dataclass, field
from fairseq.dataclass import FairseqDataclass
f... |
9748f8ab029f7407427b9223a6360e82b0b211209c9f3cda6d96ba54d705dec0 | Python | 2,896 | 73 | import numpy
import pandas
import logging
from bgen import BgenReader
from ..misc import Genomics
def bgen_file_geno_lines(file, variant_mapping = None, force_colon = False, use_rsid=False, whitelist=None, skip_palindromic=False, liftover_conversion=None):
logging.log(9, "Processing bgen %s", file)
bfile = Bg... |
c542f1401aa7025e160da3901f916b94c84f9d2ffaa403c59e652d273875b7e0 | Python | 2,897 | 90 | '''
Tests for datahandler_framebyframe.py
'''
import os
import numpy as np
import imageio
from PIL import Image
from .base_test import BaseTestCase
from .. import datahandler_framebyframe as datahandler
from .. import roitools
class TestImage2Array(BaseTestCase):
''' Tests for image2array.'''
def setup_clas... |
da06d5e403d930abf9958f2504482ea25eda167ba73dec506546096b5638179f | Python | 2,897 | 58 | import numpy as np
import torch
from nnunetv2.training.loss.compound_losses import DC_and_BCE_loss, DC_and_CE_loss
from nnunetv2.training.loss.deep_supervision import DeepSupervisionWrapper
from nnunetv2.training.loss.dice import MemoryEfficientSoftDiceLoss
from nnunetv2.training.nnUNetTrainer.nnUNetTrainer import nnU... |
420138b2820c0cd4a4560bb33b93d5418bcaa832d31164f4020527994f3b3da9 | Python | 2,898 | 102 | """fixtures relating to audio files"""
import pytest
from .annot import LABELSET_NOTMAT, ANNOT_LIST_NOTMAT
from .test_data import SOURCE_TEST_DATA_ROOT
@pytest.fixture
def default_spect_params():
return dict(
fft_size=512,
step_size=64,
freq_cutoffs=(500, 10000),
thresh=6.25,
... |
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