sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
a418ebe2867256cffc7536098845b2e3fb0b1a2b802b81e6bc0829b2848eaca3 | Python | 634 | 22 | """Create individual experiment files for a parameter sweep."""
from pathlib import Path
import yaml
FNAME = Path("exp.yaml")
with open(FNAME, "r") as f:
data = yaml.safe_load(f)
NUM_SIMS = 20
for i in range(NUM_SIMS):
data["student_simulation_settings"]["weights_init_seed"] += 1
data["student_simulati... |
e83bee87ce812ac8b65f8291e03ec335c5fd5125bd06577ae3521ff3497a1063 | Python | 634 | 21 | from __future__ import annotations
from poetry.config.config import Config
from poetry.console.commands.command import Command
class CacheListCommand(Command):
name = "cache list"
description = "List Poetry's caches."
def handle(self) -> int:
config = Config.create()
if config.repository... |
38772dae00ff9484b5f32c492a268b4fae27084fe41379702ff1c2f84e0f4243 | Python | 635 | 24 | # encoding: utf-8
"""
@author: Jiayang Chen
@contact: yjcmydkzgj@gmail.com
"""
# import fm
# def choose_backbone(backbone_name):
# if backbone_name == 'rna-fm':
# backbone, backbone_alphabet = fm.pretrained.rna_fm_t12()
# else:
# raise Exception("Wrong Backbone Type! {}".format(backbone_name))... |
92f684855f57bc87e3bfd9cdbfe13d107034fad55a6cac040722257ed51cf3d4 | Python | 636 | 23 | # 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 tests.speech import TestFairseqSpeech
class TestS2TTransformer(TestFairseqSpeech):
def setUp(self):
self.se... |
0a17ab747d3cc252235b425a8dd150f7843b2b28dfd9761839aa0f455f8db0c7 | Python | 637 | 19 | #
# setup.py
# Copyright (c) 2020 Daisuke Endo
# This software is released under the MIT License.
# http://opensource.org/licenses/mit-license.php
#
#--------------------------------
# 作成者：Daisuke Endo
# 連絡先:daisuke.endo96@gmail.com
# 最終更新日 2020/5/17
#--------------------------------
from distutils.core import setup, E... |
1b64d3e180e9b83f9d8c109ba9e940f09831ede9229d139df353f0ff80f1fac4 | Python | 637 | 17 | from src.utils.eval_utils import Ontology
import pandas as pd
ont = Ontology('data/go-basic-2020-06-01.obo')
MF_terms = pd.read_csv('data/GeneOntology/MF_mapping.csv', header=None)
BP_terms = pd.read_csv('data/GeneOntology/BP_mapping.csv', header=None)
CC_terms = pd.read_csv('data/GeneOntology/CC_mapping.csv', heade... |
b2303cc517dbe727238d91aecde9047be04537226e9cb33197cb234e4ca83628 | Python | 637 | 20 | from mdt import CompartmentTemplate
__author__ = 'Robbert Harms'
__date__ = "2015-06-21"
__maintainer__ = "Robbert Harms"
__email__ = "robbert@xkls.nl"
class CylinderGPD(CompartmentTemplate):
parameters = ('g', 'b', 'G', 'Delta', 'delta', 'd', 'theta', 'phi', 'R')
dependencies = ('VanGelderenCylinder', 'Sph... |
265b903afe0795a800071d1e46513a2f595ea946ee950b534b85d8f00484af39 | Python | 639 | 23 | # 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 tests.speech import TestFairseqSpeech
class TestS2TConformer(TestFairseqSpeech):
def setUp(self):
self.set_... |
99b6dc388add0ed76fba35e40cf36a64f17e88f5b830dd7eaee48853c92f4c31 | Python | 639 | 14 | # Copyright 2021 DeepMind Technologies Limited
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agr... |
45de42d027d3accc847ef3a017485fc90ede4b337941b5bbd11f25f04d7180c2 | Python | 640 | 27 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import os
from tractseg.experiments.base_legacy.tract_seg_legacy import Config as TractSegConfig
class Config(TractSegConfig):
EXP_NAME = os.path.basename(__file__).split(".")[0]
NUM_EPOCHS = 250
DATA_AUGMENTATION = True
# DATA_AUGMENTATION = False
M... |
c9c4ab022bad39427765f8aa524382b1890df4682490e24f232c125eaf249aed | Python | 641 | 28 | #!/usr/bin/env python3
import math
import torch
from torch import Tensor
def batched_outer(a: Tensor, b: Tensor) -> Tensor:
return a.unsqueeze(2) * b.unsqueeze(1)
def asym_var(a: Tensor, b: Tensor) -> Tensor:
return (a - b).var()
def asym_angle(a: Tensor, b: Tensor) -> Tensor:
assert a.shape == b.s... |
db1ad3a42aecf597d9566eabb7b6394bb8b48aa8472cf98323057a9781ade6d2 | Python | 642 | 17 | from __future__ import annotations
from poetry.console.commands.lock import LockCommand
from poetry.console.commands.self.self_command import SelfCommand
class SelfLockCommand(SelfCommand, LockCommand):
name = "self lock"
description = "Lock the Poetry installation's system requirements."
help = f"""\
Th... |
ce142bcdf31cc519c552cd002bd74e8c054b3cd22b27e0f5f85c323ca3c77e46 | Python | 643 | 20 | import argparse
import neuroglancer
import neuroglancer.cli
from example import add_example_layers
if __name__ == "__main__":
ap = argparse.ArgumentParser()
neuroglancer.cli.add_server_arguments(ap)
args = ap.parse_args()
neuroglancer.cli.handle_server_arguments(args)
# Specifying a token disable... |
6631bfecb4c373262661c8956d514200fba66e15621ca47c3cb39333396f360d | Python | 647 | 20 | # 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 . import BaseWrapperDataset
class StripTokenDataset(BaseWrapperDataset):
def __init__(self, dataset, id_to_strip):
super().... |
71c65d0f62d514324d2224ca179ebb6f85afa1b291ceaefa84f089b9c18f8e76 | Python | 647 | 23 | """Register Simulation dataset (standalone Simulation + CID package)."""
from __future__ import annotations
from dlbase.registry import register_dataset
from datasets.Simulation.datamodule_setup import (
simulation_eval_split_note,
setup_simulation_datamodule,
)
from datasets.Simulation.dataset_tas... |
4eca160be556da2639ba9b6abd83208dddc6052cf23b4549e7eb6bf2a000c639 | Python | 648 | 21 | from ._attrdict import attrdict
from ._decorators import unsupported_if_adata_minified
from ._dependencies import dependencies, error_on_missing_dependencies, is_package_installed
from ._docstrings import de_dsp, setup_anndata_dsp
from ._mlflow import mlflow_log_artifact, mlflow_log_table, mlflow_log_text, mlflow_logge... |
9ce050b96db979e9955bb139ea136986780398dc3c4794227e59347f11e41255 | Python | 649 | 31 | """scvi-tools."""
# Set default logging handler to avoid logging with logging.lastResort logger.
import logging
from ._constants import REGISTRY_KEYS
from ._settings import settings
# this import needs to come after prior imports to prevent circular import
from . import data, model, external, utils, criticism
from ... |
22eb336c48259a2e16b22260a80469d708a86250af781126d933cadeb952b511 | Python | 652 | 23 | # 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 .processor import *
from .how2processor import *
from .how2retriprocessor import *
from .dsprocessor import *
try:
from .rawvideopr... |
ae33bd884435d83210ece0e3bdff1be3d068dd7c050aae92e8dcd918387ba11a | Python | 652 | 23 | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from dataclasses import dataclass, field
from hydra.core.config_store import ConfigStore
from hydra_plugins.hydra_submitit_launcher.config import SlurmQueueConf
@dataclass
class DependencySubmititConf(SlurmQueueConf):
"""Slurm configuration ... |
8b784a9fdcafcb6d0e35c8b164977edbe3ad700950d109ed9542b527706fbfa7 | Python | 653 | 24 | import os
import glob
root = r"D:\Projects\LFODet-main\mnt\Datasets\NWPU\ImageSets"
old_prefix = r"D:\FangX24\code\LO-Det-main\mnt\Datasets\NWPU"
new_prefix = r"D:\Projects\LFODet-main\mnt\Datasets\NWPU"
txt_files = glob.glob(os.path.join(root, "random*", "**", "*.txt"), recursive=True)
print("Found txt f... |
144c001f817a11c018cb618354e7fb67e52cd76d01b74667b02fc0657a5874e7 | Python | 655 | 14 | # Copyright 2021 DeepMind Technologies Limited
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agr... |
77f201aa00b9e435554c096a42406cfcbcfa40d9562ef763dd77f3ed0b4f6eea | Python | 656 | 22 | #
# 09/19 11:34 - {builders_utils.py:208} - n_genes, n_pathways 9229 1387
# 09/19 11:34 - {builders_utils.py:208} - n_genes, n_pathways 1387 1066
# 09/19 11:34 - {builders_utils.py:208} - n_genes, n_pathways 1066 447
# 09/19 11:34 - {builders_utils.py:208} - n_genes, n_pathways 447 147
# 09/19 11:34 - {builders_utils.p... |
b8a13f8b64dfdc5805f6e88c5db0fd50263ccef88266315607c8fed92ee6c38f | Python | 657 | 21 | import numpy as np
def calculateMeanCoefficients(trialCoefficients):
"""
calculate mean coefficients for each trial.
parameters:
- trialCoefficients: dictionary with trial coefficients
returns:
- dictionary with mean coefficients per trial
"""
meanCoefficients = {}
for tsN... |
a18f9f091ca3349f6326e7ca8dffeb41fa6c2c39810b6e3a912a80f5a5ff22ee | Python | 658 | 26 | from . import decorator, definition, factory, registry
from .convencoder_umap import ConvEncoderUMAP
from .decorator import model
from .ed_tcn import ED_TCN
from .factory import ModelFactory
from .frame_classification_model import FrameClassificationModel
from .get import get
from .parametric_umap_model import Parametr... |
bc6c5b54c01570b1437a110b752d03f579fc8300af1569ef7fe05a0cb42fbaf8 | Python | 658 | 19 | """Generic cfg-level assertions (no hard-coded dataset / model / task names)."""
from __future__ import annotations
from typing import FrozenSet
from omegaconf import DictConfig
def assert_task_in(cfg: DictConfig, allowed: FrozenSet[str], context: str) -> None:
t = str(cfg.task.name)
if t not in... |
2cb2ab98627b3e2b0c3ea9a10328ff36a55a614ea71c1eebd91f64befead05a1 | Python | 659 | 17 | from chanfig import Config, Variable
class BaseConfig(Config):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self.input_file = Variable(str, default="./tests/fasta/single_sequence.fasta")
self.save_path = Variable(str, default="../results")
self.auto_fix = ... |
5e0dbbdb89a7a61883dcf1f0147c52e11aabb9b79e552567170ce6a3ff1e9a68 | Python | 659 | 19 | import shutil
from batchgenerators.utilities.file_and_folder_operations import isdir, join
from nnunetv2.paths import nnUNet_raw, nnUNet_results, nnUNet_preprocessed
if __name__ == '__main__':
# deletes everything!
dataset_names = [
'Dataset996_IntegrationTest_Hippocampus_regions_ignore',
'Da... |
948faf9ef59dc9adb2ac758bbf76a69e8f0a8c99dd668b821fe35e553bca4f16 | Python | 659 | 17 | """Filtro das copias por simetria (543 das 1784). SEM_COPIAS=0 desliga (controle)."""
import json, os
from pathlib import Path
_G = json.loads((Path("/home/david/atual/new-methods/submissions/oce-jpcc-perovskites/REVISAO_R1/calculos/eos_cenapad") /
"duplicatas_simetria_1784.json").read_text())
COPIAS =... |
9c5a3818939c8cc44afd5e02dbe8c1b23990ff073877a5de2dfad6bd43834e08 | Python | 659 | 22 | # 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 __future__ import print_function
from __future__ ... |
4b2a472f1a4b4b11f97dd79ed7b7aae7760d81e97e9b46a136009d4cf9eae224 | Python | 660 | 22 | import qrcode
# URL var: enter link/url for the pdf
pdf_url = "https://drive.google.com/u/0/uc?id=1Uvs7RSEbtPUsUvyRcrEEizRhAgqhlElH&export=download"
# QR code instance
qr = qrcode.QRCode(
version=1, # QR code version (adjust as needed)
error_correction=qrcode.constants.ERROR_CORRECT_L, # Error correction le... |
51dc0519ffd7c1adc2aa46bf39f7df4521beb07a14ef1f888db821454c8f3b77 | Python | 660 | 35 | from .utils import (
WINDOW_LENGTH,
WINDOW_STRIDE,
Pointer,
Token,
aggregate_embeddings,
embed_document,
load_fast_tokenizer,
log_config,
merge_off_tokens,
merge_predictions,
merge_tokens,
repr_sequence,
split_and_tokenize,
token_merge,
tokenize_and_align,
)
... |
b1b1ee3a3d6868e108ccca1c9503d5a7824c1997d4bb239999f1a6241f37e16b | Python | 660 | 29 | from dataclasses import dataclass, field
from typing import Any, Optional
@dataclass
class DatasetParams:
loader: str
image_dir: str
image_size: int
channels: list[str]
batch_size: int
val_split: float
test_split: float
keys: list[str]
name: Optional[str] = None
labels: Optiona... |
5f7244d77ef3fee41dd8078507ed87f3317ea9109a937674fc8dd26cf466540d | Python | 661 | 20 | import numpy as np
class CrossSessionLeaveOneOut:
"""
K-Fold by held-out sessions.
Provides train/test indeces stratified by session.
Useful for Allen dataset
"""
def __init__(self, session_labels: np.ndarray):
self.session_labels = session_labels
self.unique_sessions = np.uni... |
81d285f77e444308aaf387bf06ecbbf7ccca4461d62db3e9ad9fe462393e5d82 | Python | 663 | 14 | # Copyright 2021 DeepMind Technologies Limited
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agr... |
72df66c996cd559fa6a67b909de787123fea2f816173d2e3f9cb0a9cc9dc0f68 | Python | 664 | 31 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import os
import shutil
from glob import glob
from vlpp.utils import gzipd, run_shell, run_matlab, TPL_PATH
def main():
niigz = "${petInputNii}"
nii = gzipd(niigz)
dst = nii.replace("_input_", "_").replace("_copy", "")
shutil.move(nii, dst)
tags = ... |
90bfadedc63b26b61934964dfb27156269a8eab52ab9293c591cc651736baa9b | Python | 664 | 26 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import os
from tractseg.data import dataset_specific_utils
from tractseg.experiments.base_legacy.tract_seg_legacy import Config as TractSegConfig
class Config(TractSegConfig):
EXP_NAME = os.path.basename(__file__).split(".")[0]
DATASET_FOLDER = "HCP_preproc_all"... |
c0a0c60e671d2b2a433f06d61778a966c87d94493059e6550222bdce3af2c566 | Python | 665 | 23 | # 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 os
import importlib
from fairseq import registry
(
build_monotonic_attention,
register_monotonic_attention,
MONOTONIC_ATT... |
dd785f4231bb626af74669c13b67fbc8e277a0b5637de6bc38926b7656522c93 | Python | 666 | 20 | from rnalysis.utils.feature_counting import *
def test_create_featurecounts_script():
expected_path = 'tests/test_files/featurecounts_tests/expected_featurecounts_script.R'
output_dir = Path('tests/test_files/featurecounts_tests/outdir')
kwargs = {'arg': True, 'arg2': None, 'arg3': 'string', 'arg4': ['str... |
2d7f7a8faf41e26d05eb16f82fe843a4a180497565dd6841f644891dc7a3b383 | Python | 668 | 27 | from __future__ import annotations
from poetry.console.commands.command import Command
class AboutCommand(Command):
name = "about"
description = "Shows information about Poetry."
def handle(self) -> int:
from importlib import metadata
self.line(
f"""\
<info>Poetry - Package... |
e1d6bf30574f4e9b17aef158d9bd5c31ff2d61d495d43b5989cfa54e50d7751a | Python | 668 | 24 | import setuptools
with open("README.md", "r") as fh:
long_description = fh.read()
setuptools.setup(
name="mmpt",
version="0.0.1",
author="Hu Xu, Po-yao Huang",
author_email="huxu@fb.com",
description="A package for multimodal pretraining.",
long_description=long_description,
long_descr... |
5742888af6570c79b1af7e46fe5e846f373c22f70522f8961bdd665e15e378e3 | Python | 669 | 27 | #!/usr/bin/env python
import re
import requests
from packaging import version
def get_most_recent_version(name):
request = requests.get(
"https://api.anaconda.org/package/conda-forge/" + name
)
request.raise_for_status()
pkg = max(
request.json()["files"], key=lambda x: version.parse(... |
f39ec4a065bbde7f867e683ba490a7e3019248d6c85744e8be5febbcb15ee9c9 | Python | 669 | 19 | # 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 importlib
import os
# automatically import any Python files in the current directory
cur_dir = os.path.dirname(__file__)
for file in o... |
cd7929ec8ecb5cdfd97814a4cc19ec60a3f7843a934df819d47fe80dbe3314f6 | Python | 670 | 24 | from msi_visual.base_dim_reduction import BaseDimReduction
import pacmap
import numpy as np
import joblib
from msi_visual.utils import normalize
class PACMAC3D():
def __init__(self):
self.model = pacmap.PaCMAP(n_components=3)
def __repr__(self):
return f"PACMAC-3D"
... |
cda8fe5886fc44e41e6469d802be15bc436ff03586b00173bd99044e909d9acf | Python | 670 | 30 | from __future__ import annotations
from typing import TYPE_CHECKING
import pytest
from cleo.io.buffered_io import BufferedIO
from poetry.utils.env import EnvManager
if TYPE_CHECKING:
from poetry.poetry import Poetry
from tests.types import FixtureDirGetter
from tests.types import ProjectFactory
@pyt... |
aee147dfa11a620fee2a4171c38a77fe7ab0f2d06b37c7278b1b8c6dce98c759 | Python | 671 | 22 | from typing import NamedTuple
class _CYTOVI_REGISTRY_KEYS_NT(NamedTuple):
X_KEY: str = "X"
BATCH_KEY: str = "batch"
LABELS_KEY: str = "labels"
SAMPLE_KEY: str = "sample_id"
CAT_COVS_KEY: str = "extra_categorical_covs"
CONT_COVS_KEY: str = "extra_continuous_covs"
INDICES_KEY: str = "ind_x"
... |
15d13418b0ede38ed80ba91f62d635c2ddf0cf22039eb6de19b7b0287693cb8b | Python | 672 | 22 | from gtfparse import read_gtf
from transcript_transformer.data import parse_transcriptome, save_transcriptome_to_h5
import h5py
import time
data_dict = parse_transcriptome("export/final_transcripts_RiboTIE.gtf", "/Users/xunuo/Genomic_references/GENCODE/GRCh38.primary_assembly.genome.fa")
no_handle = True
max_wait = 90... |
5f2a31195f51e2195f60cc9893a887beb81f08b563b47b9f753715e90d57c745 | Python | 673 | 28 |
import torch
import msprime
import stdpopsim
import os
import numpy as np
import pickle
from dadi_simulators import *
datadir = snakemake.params.datadir
posteriordir = snakemake.params.posteriordir
num_simulations = snakemake.params.num_simulations
if not os.path.isdir(f"{datadir}"):
os.mkdir(f"{datadir}")
dem... |
f8fc4f9241043358aa81fd7f09643321e6343860eb33e93670c809a549a564eb | Python | 673 | 23 | import ctypes
from functools import partial
from typing import Tuple
import jax
import jax.numpy as jnp
import numpy as np
from pyscf import lib
from pyscf.dft import gen_grid
@partial(jax.jit, static_argnums=0)
def spherical_grid(lebedev_order=7) -> Tuple[jax.Array, jax.Array]:
r"""Return the spherical Lebedev ... |
5270f7b19e889251e36b24bc488b5e03ee9f2bff6de64f157bc08447021a20c8 | Python | 674 | 23 | import soundfile as sf
import argparse
if __name__ == "__main__":
parser = argparse.ArgumentParser(description='Example argument parser')
parser.add_argument('--src', type=str)
parser.add_argument('--dst', type=str)
args = parser.parse_args()
wavs = [x.strip() for x in open(args.src, "r").readline... |
dff7a4c0cf5347a5c402595b4cbcf97bc7d8ab7f7dd71b68a7dbdd62ab9d75de | Python | 674 | 21 | # -*- coding: utf-8 -*-
import setuptools
with open("README.md", "r", encoding="utf-8") as fh:
long_description = fh.read()
setuptools.setup(
name="working-memory-eeg-analysis",
version="0.0.1",
author="Marius Keute and Silvana Miranda Montenegro",
description="Analysis functions for working-memo... |
23833682bef7db82e711f99f106717dfecd42aa6bbfb17ac55220ee729139e19 | Python | 676 | 28 | from __future__ import annotations
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from poetry.core.packages.package import Package
from poetry.core.packages.project_package import ProjectPackage
class SolverResult:
def __init__(
self,
root: ProjectPackage,
packages: list[Pac... |
05ce2b15899ccd353a35b38d93869591b5dd1937ca782d2d5650ec0b52e87991 | Python | 677 | 31 | import os
def get_volume_name(
fullname_volume: str,
dir_prefix: str = None,
) -> str:
"""
Get name of volume (with directory prefix and plane suffix).
Parameters
----------
fullname_volume : str
Full name of volume.
dir_prefix : str (optional)
Prefix for directory. De... |
5e47ec9ddb1f0c3a959cad122f423a50c93d029bad66c6fa5084b254daac0f01 | Python | 677 | 17 | OrderList = ['1234', '1324', '2134', '2314', '3124', '3214']
for i in range(6):
for j in range(2):
with open('Training_dataset_R%s.txt' % (i*2 + j +1), 'r') as fin:
lines = fin.readlines()
with open('Training_dataset_R%s_%s.txt' % ((i*2 + j +1), OrderList[i]), 'w') as fout:
for m in OrderList[i]:
for k i... |
3da520b5ee83b1b048241d819c6b99ac73e302b177b80664d8084f0667f234de | Python | 679 | 24 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Outputs analysis results"""
try:
import numpy as _ # noqa F401 F811
import matplotlib as _ # noqa F401 F811
import nd2 as _ # noqa F401 F811
except ImportError:
raise ImportError("Must install numpy, matplotlib, and nd2")
from . import basic_analyse... |
0c76ee07509d4e5d2f03d5ab71fbf9b57dac3f437d1a79a655c94b071614203f | Python | 680 | 21 | # 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.functional as F
def pad_to_multiple(x, multiple, dim=-1, value=0):
# Inspired from https://github.com/lucidr... |
8c9e457307bab5b5f1a92b94c513b7b9e978e2d1cfe77bd549ca2396eb347013 | Python | 680 | 18 | # Copyright 2015 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... |
a87a738b55afac2fe2e93ad5aefb92e78ebc8d62859fe3755ff68cf8577df902 | Python | 681 | 26 | import math
import numpy as np
def point_to_line_distance(x1, y1, x2, y2, xp, yp):
# 计算斜率
if x2 - x1 == 0: # 防止除以零的情况（垂直线）
m = float('inf')
distance = abs(xp - x1)
else:
m = (y2 - y1) / (x2 - x1)
# 计算点P到直线的垂直距离
distance = abs(m * xp - yp + y1 - m * x1) /... |
d5f34a1c73f4ae59dcac69aa478a9c0bcffef42c1a6f882c0e86603101ed6a5f | Python | 681 | 31 | #!/usr/bin/env python3
import os
import numpy as np
import tensorstore as ts
example_dir = os.path.abspath(os.path.dirname(__file__))
def write_single_res():
store = ts.open(
{
"driver": "zarr3",
"kvstore": {
"driver": "file",
"path": os.path.join... |
18c59276f5d4e3bc805f0adc3206e95b5424639021480e168188e1ce25b345ec | Python | 684 | 23 | """assertions common to cli functions"""
import vak
def toml_config_file_copied_to_results_path(results_path, toml_path):
assert results_path.joinpath(toml_path.name).exists()
return True
def log_file_created(command, output_path):
log_file = sorted(output_path.glob(f"{command}*.log"))
assert len(lo... |
8fa8dfd201c15fc0f799bd9a3b47d53bc03d68058c52cde63989800fdf8357eb | Python | 684 | 30 | # 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.data.encoders import register_bpe
SPACE = chr(32)
SPACE_ESCAPE = chr(9601)
@register_bpe("characters")
class Characters(obje... |
28a1e8e5f7446c0bc8ca48be844781daae625ab0eb0045108c9d8ae4a6040f3e | Python | 685 | 24 | from mdt.component_templates.compartment_models import CompartmentTemplate
__author__ = 'Robbert Harms'
__date__ = "2018-08-28"
__maintainer__ = "Robbert Harms"
__email__ = "robbert@xkls.nl"
class AstroCylinders(CompartmentTemplate):
parameters = ('b', 'G', 'Delta', 'delta', 'd', 'R')
dependencies = ['VanGe... |
45718ac64a5eeb5fa67236791753a69604e3526c82c8acabc8c39fdff063edb2 | Python | 685 | 25 | import torch
def test_model(model, dataloader, device, log_dir):
test_log = open(f'{log_dir}/test_log.csv', 'w')
test_log.write("Label,Probability\n")
model.eval()
with torch.no_grad():
for i_batch, sample_batched in enumerate(dataloader):
inputs, labels = sample_batched['mat... |
ee1c191ea80110b22c49cb6f0c153052b86cc7d6296870d1c6394565e698be1c | Python | 685 | 16 | from transformers.models.bert.configuration_bert import BertConfig
config = BertConfig.from_pretrained("zhihan1996/DNABERT-2-117M")
model = AutoModel.from_pretrained("zhihan1996/DNABERT-2-117M", trust_remote_code=True, config=config)
dna = "ACGTAGCATCGGATCTATCTATCGACACTTGGTTATCGATCTACGAGCATCTCGTTAGC"
inputs = tokeniz... |
835d09eca984d34a6ea3e061ecd54c0a09d73c97a5ecc1db2dc45a351bf6b83a | Python | 687 | 27 | from __future__ import annotations
from typing import TYPE_CHECKING
from poetry.plugins.base_plugin import BasePlugin
if TYPE_CHECKING:
from poetry.console.application import Application
from poetry.console.commands.command import Command
class ApplicationPlugin(BasePlugin):
"""
Base class for app... |
a41bce0b15f50e5bff70ce8b3c2b7aeb504b7bc018e8c1a7c5a3050e574aeab5 | Python | 687 | 26 | # kNN with neighbors=4 benchmark for Kuzushiji-MNIST
# Acheives 92.10% test accuracy
from sklearn.neighbors import KNeighborsClassifier
import numpy as np
def load(f):
return np.load(f)['arr_0']
# Load the data
x_train = load('kmnist-train-imgs.npz')
x_test = load('kmnist-test-imgs.npz')
y_train = load('kmnist-t... |
4f93076c72ed10def3657f2fc37e928f22552af33b55723616dc0b2e4c18de73 | Python | 689 | 25 | from __future__ import annotations
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from torch import Tensor
def rowwise_max_excluding_diagonal(matrix: Tensor) -> Tensor:
"""Get the rowwise maximum of a matrix excluding the diagonal."""
import torch
assert matrix.ndim == 2
num_cols = matrix.s... |
b70884b86b2ef284fc527f1e25981aee0eaad509d75b24337be3f9d47782ea13 | Python | 689 | 29 | project = "Moove"
copyright = "2025, Nils Riekers, Franziska Heubach, Jacqueline Laura Goebl, Lena Veit"
author = "Nils Riekers, Franziska Heubach, Jacqueline Laura Goebl, Lena Veit"
release = "1.1.0"
extensions = [
"sphinx.ext.autodoc",
"sphinx.ext.viewcode",
"sphinx.ext.intersphinx",
]
templates_path = ... |
4ed0eb8ed6c57e13f770958c956ac2c19c89b829988ad0f341e54a73e1cfed0e | Python | 691 | 26 | """Feature-local view state for behaviour alignment."""
from __future__ import annotations
from dataclasses import dataclass
@dataclass
class BehaviourViewState:
file_path: str = ""
pre_behaviour_time: str = ""
post_behaviour_time: str = ""
synchronize_start_time: str = ""
duration_box_placement... |
7bec4a1b73cb98692f8662c59d0f790f10f2ee2dd24875ac5825318d10f8b36c | Python | 691 | 29 | from apiadapters.straininfo import normalize_strain_names
def test_parse_standard() -> None:
standard_names = ("Delft L 40", "STAFF 1027", "DSMZ 2213")
assert normalize_strain_names(standard_names) == set(standard_names)
def test_parse_non_standard() -> None:
names = (
"544 / ATCC 23448",
... |
d87f1ab847b18d43c042f124ec0e614d7fb24faf4538282493da9f0531f0636f | Python | 695 | 29 | import torch
from torch.utils.data import Dataset
import pandas as pd
from typing import Union
from pathlib import Path
from rinalmo.data.alphabet import Alphabet
class TranslationEffDataset(Dataset):
def __init__(
self,
csv_path: Union[Path, str],
alphabet: Alphabet
):
self... |
043d100fe5016302eada1f9515763fee5228ca26c30763fd272a540507a787a2 | Python | 696 | 17 | import torch
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("zhihan1996/DNABERT-2-117M", trust_remote_code=True)
model = AutoModel.from_pretrained("zhihan1996/DNABERT-2-117M", trust_remote_code=True)
dna = "ACGTAGCATCGGATCTATCTATCGACACTTGGTTATCGATCTACGAGCATCTCGTTAGC"
input... |
8f3f394ef74987cf0302dc62e08c10808ab5b20aa96db4cf441cda1f323199a6 | Python | 696 | 30 | from __future__ import annotations
import ast
import os
from setuptools import setup
def read_version():
with open(os.path.join(os.path.dirname(__file__), "demo", "__init__.py")) as f:
for line in f:
if line.startswith("__version__ = "):
return ast.literal_eval(line[len("__ve... |
7010e87b8781f7f55ca8aa381675c8f857cce6e6519332db329993f61865968f | Python | 697 | 21 | """Regression test for the deadline profile `tests/conftest.py` loads.
None of the suite's property tests measure timing, so a slow machine
tripping Hypothesis's 200ms default deadline is a flake, not a signal.
"""
import time
from hypothesis import given, settings
from hypothesis import strategies as st
@given(st... |
a4197c7c5c026be4f92b255c066e1fde3a27e954739f9a0fe3bb24f624291603 | Python | 697 | 22 | import glob
import os
import pickle
from sbi.utils.posterior_ensemble import NeuralPosteriorEnsemble
import torch
import numpy as np
posteriordir = snakemake.params.posteriordir
n_train = snakemake.params.n_train
posterior_files = glob.glob(f"{posteriordir}/n_train_{n_train}/posterior_rep_*.pkl")
posteriors = []
for ... |
1a643a8da2d1b5e284b654ba7270f5e577eae78725ae2c631776f20326517612 | Python | 698 | 27 | #!/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.
import sys
from sacremoses.normalize import MosesPunctNormalizer
def main(args):
normalizer = MosesPunctNormal... |
7034b2c057e017f47a2296e430634ad5bdd290cddf5de31111d5e940f8c084ca | Python | 698 | 24 | import lmdb
from tqdm import tqdm
import pickle as pkl
from pathlib import Path
from tape.data_utils import PFAM_VOCAB
import numpy as np
vocab = {v: k for k, v in PFAM_VOCAB.items()}
files = Path('data').rglob('*.lmdb')
for lmdbfile in files:
print(lmdbfile)
env = lmdb.open(str(lmdbfile), map_size=50e9)
... |
322e8dfc8e2c8392466a7d2cff42df7bc4eb8e55ed6253d62bb161f24a865c8f | Python | 701 | 31 | from __future__ import annotations
from typing import TYPE_CHECKING
import pytest
if TYPE_CHECKING:
from tests.types import HTMLPageGetter
@pytest.fixture
def html_page_content() -> HTMLPageGetter:
def _fixture(content: str, base_url: str | None = None) -> str:
base = f'<base href="{base_url}"' if... |
5a93138b4ca174c53ac781d91d3988d5b139239570754cd0dc0a4233954bd9bb | Python | 701 | 20 | # 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 typing import List, Tuple
def get_audio_files(manifest_path: str) -> Tuple[str, List[str], List[int]]:
fnames, sizes = [], []
w... |
ac4fb8554c0df22670fa8e3c403a40a20109bb5a49f3c2a640b5f20d0289cb1e | Python | 701 | 20 | # 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 importlib
import os
# automatically import any Python files in the models/ directory
models_dir = os.path.dirname(__file__)
for file ... |
bc77cdf0f5c07d4a466ee832f312b9ea42d9c3a3503e13516a5a2a829078da41 | Python | 701 | 33 | import numpy as np
from pyfaidx import Fasta
import logging
# Setup logging
logging.basicConfig(
format="%(asctime)s - %(levelname)s - %(name)s - %(message)s",
datefmt="%m/%d/%Y %H:%M:%S",
level=logging.INFO
)
logger = logging.getLogger(__name__)
def fasta2list(fasta_file):
data = Fasta(fasta_file... |
49ce0bf57161f87d00f011f56c3919dd09f769c932f8432e18da2b4fb66eff0d | Python | 704 | 23 | import setuptools
with open("README.md", "r") as fh:
long_description = fh.read()
setuptools.setup(
name="DSTG",
version="0.0.1",
author="QSong",
author_email="wasqqdyx@gmail.com",
description=
"Deconvoluting Spatial Transcriptomics data through Graph-based convolutional networks (DSTG)",
... |
c7d32482bc1cb6cebce9457900701282aff91ed7b701971a010cb4e813f20983 | Python | 704 | 34 | # adopted from attrs library
# https://github.com/python-attrs/attrs/blob/master/tests/utils.py
from attr import Attribute
from attr._make import NOTHING
def simple_attr(
name,
default=NOTHING,
validator=None,
repr=True,
eq=True,
hash=None,
init=True,
converter=None,
kw_only=False,... |
b3f446baa962c3764ab8865bfeeaa0d06c48f100e02a11a200c51e8bd74799fe | Python | 705 | 24 | #!/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.
import torch
from typing import List, Dict
from .base_decoder import BaseDecoder
class ViterbiDecoder(BaseDecoder)... |
b1e8efc40d2c5aefaa49ac72cb2c169c172539085570005ffc98f3029333d763 | Python | 706 | 25 | # 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.
"""
See "Gaussian Error Linear Units (GELUs)" by Dan Hendrycks and Kevin Gimpel with
the corresponding GitHub repo: https://github.com/hendryck... |
edcd129ff6966605bdff7baa493630c1704951f567208f81a19c0b453f85136b | Python | 706 | 17 | from brenda_references.collection_numbers import is_collection_number
def test_admits_real_collection_numbers() -> None:
for designation in ("ATCC 9202", "DSM 4252", "NCTC8511", "CBS 111.30"):
assert is_collection_number(designation), designation
def test_rejects_generic_designations() -> None:
for ... |
eef46a006a786a3452c54f86a013a1281beb1585a816f2ca79d478a0a56ca077 | Python | 706 | 29 | import torch
from torch.utils.data import Dataset
import pandas as pd
from typing import Union
from pathlib import Path
from rinalmo.data.alphabet import Alphabet
class ExpressionLevelDataset(Dataset):
def __init__(
self,
csv_path: Union[Path, str],
alphabet: Alphabet
):
sel... |
623f97e7d40dbbeb7a1c0b4fad0664d119ab1e9ec8e942e7fde91e9090e6bffb | Python | 707 | 23 | try:
from d3text.excepthook import install as _install_excepthook
_install_excepthook(style="darkbg2")
except ModuleNotFoundError:
print(
"pip install stackprinter if you want stackprinter's exception messages."
)
try:
from beartype.claw import beartype_this_package
beartype_this_pack... |
d4bf22f3ffec8578bd0051c04b5b04d2e35997c041d601a1e8ce4936a3060f85 | Python | 708 | 18 | from batchgenerators.utilities.file_and_folder_operations import *
from nnunetv2.batch_running.collect_results_custom_Decathlon import collect_results, summarize
from nnunetv2.paths import nnUNet_results
if __name__ == '__main__':
use_these_trainers = {
'nnUNetTrainer': ('nnUNetPlans', ),
}
all_re... |
b64a9368daf430d6632a6a688e0f07620194555a5fafac827a61ee64b66ffd26 | Python | 709 | 21 | """Regression test for the shared NCBI merged-taxid forwarding helper."""
import pandas as pd
import pytest
from taxonomy.ncbitax import ncbitax
from d3text.taxonomy import merged_taxids
def test_merged_taxids_maps_a_retired_id_to_its_current_one(
monkeypatch: pytest.MonkeyPatch,
) -> None:
"""A caller impo... |
7059e9ca7471b693f9271f777cd411cfbb5d05b81e1e58d093ff9ca9d3b04599 | Python | 710 | 20 | # 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 importlib
import os
# automatically import any Python files in the models/huggingface/ directory
models_dir = os.path.dirname(__file_... |
9af73c32a31be54829eb9ae93ef64cba03fce207a6a6d08e6c0a39c5db1dc1d5 | Python | 710 | 28 |
def seq2kmer(seq, k_mer, max_length=None):
kmer_text = ""
i = 0
upper = len(seq) - k_mer + 1
if max_length:
upper = min(upper, max_length)
while i < upper:
kmer_text += (seq[i: i + k_mer] + " ")
i += 1
kmer_text = kmer_text.strip()
return kmer_text
def seq2input_id... |
00852a1fcf3d86ce84cdf3e8db889fd9acec533777bb560988ec24317a2614a0 | Python | 711 | 26 | import pytest
import numpy as np
import os
#from ecephys_spike_sorting.modules.automerging.automerging import automerging
#import ecephys_spike_sorting.common.utils as utils
#DATA_DIR = os.environ.get('ECEPHYS_SPIKE_SORTING_DATA', False)
def test_automerging():
sample_rate = 30000.0
params = {}
params['merge_th... |
49624487b3bac7cfe2974436d19e7ef04a11d04746a93235e4c9105507298d98 | Python | 711 | 23 | """
PyTorch Dataset and Batch Sampler
ImageDataset: Loads individual images with augmentation and tokenization
StudyAwareBatchSampler: Groups images from same study into batches
MultiViewCollator: Collates batches with background filtering
MultiBlockCollator: JEPA-style mask generation collator
ImageDataModule: PyTorc... |
397454407043ebd0962e07ff33c1f399855b84fcd7aa5a24deffbc2406147576 | Python | 713 | 24 | import argparse
import webbrowser
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.tx... |
c7094eab27073cf33d352a5b0a5960bd2fd06f1fb1c69dad4b4082522e33f1f9 | Python | 714 | 23 | import gradio as gr
import subprocess
def run_command(cmd: str) -> str:
p = subprocess.Popen(cmd, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
stdout, stderr = p.communicate()
if stdout:
return f"[Output]\n{stdout.decode()}"
if stderr:
return f"[Error]\n{stderr.decode()... |
f5e0024bd0baee8713c3480fb849751c0416c27f8d344265c7c12361d96ccd54 | Python | 714 | 31 | import numpy as np
from skfmm import distance
import time
import pylab as pl
def p(m): pl.matshow(m); pl.colorbar(); pl.show()
def c(m): pl.contour(m); pl.colorbar(); pl.show()
def cf(m): pl.contourf(m); pl.colorbar(); pl.show()
def test0():
"circular level"
N = 1500
X, Y = np.meshgrid(np.linspace(-1,1,N... |
14d7b8f24bfb2f2e2b7d19714880c4f3a8e7b2c61858224ea035847f59b29602 | Python | 716 | 19 | # python setup_cmmcost_omp.py build_ext --inplace
# export OMP_NUM_THREADS=6
from distutils.core import setup
from Cython.Build import cythonize
from distutils.extension import Extension
import numpy
srcfiles = ["cmmcost_omp.pyx", "_cmmcost_omp.c"]
includedirs = ["/mnt/seagate10/gsl/include", numpy.get_include()] # pa... |
d1a1bc68ff130b94230a607405744d50ea0ce0fb64511a4e31d6a0578d46d0b3 | Python | 716 | 23 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""utils"""
from . import color_maps # noqa F401
from . import types # noqa F401
from .decorators import timer_s # noqa F401
from .filter import ( # noqa F401
filter_edge,
filter_no_eccentricity,
filter_tile_scan,
filter_low_pixels,
filter_cells_ge... |
31114f08e3d6c08da15345d60014a86cbcdf9115b343f399ac25d20887454975 | Python | 717 | 21 | """Build ``torch.nn.Module`` from Hydra config (plugins registered in ``models.plugins``)."""
from __future__ import annotations
from omegaconf import DictConfig
def construct_model(cfg: DictConfig):
"""Construct weights only (call :func:`build_model` for compatibility checks)."""
from dlbase.regis... |
afe7a0545016d0d338d76f6ebb022208d16bec5ca87385cfd063f9b991f0bbb5 | Python | 718 | 18 | """ from https://github.com/keithito/tacotron """
'''
Defines the set of symbols used in text input to the model.
The default is a set of ASCII characters that works well for English or text that has been run through Unidecode. For other data, you can modify _characters. See TRAINING_DATA.md for details. '''
from . i... |
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