sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
dece06ab0a2e2f73d74c0d5c7f7dc468d9a046a6ff343dcf559d96f5b6e67f7c | Python | 3,850 | 126 | import argparse
import os
import pandas as pd
def get_args():
parser = argparse.ArgumentParser(description="Generate sample sheet to convert bcl files to fastq files")
parser.add_argument(
"-b",
"--barcodes",
required=True,
help="Tab separated file with a header of columns Sam... |
a25da3d651bd07d14b1c9cf7a866def33c90a532c6776102f8d3ce6c0885a0ba | Python | 3,851 | 118 | """alignments methods."""
import functools
import parasail
import pysam
import medaka.common
from medaka.tandem.record_name import RecordName
def align_chunk_to_ref(
chunk: pysam.FastxRecord, ref_fasta: pysam.FastaFile, aln_header=None
) -> pysam.AlignedSegment:
"""Align consensus chunk to reference using ... |
b478a1b3d3ecb10c6af990086ed6facd66da2b5d3990831f1aacee1528cf6e94 | Python | 3,854 | 91 | """Explicit demonstration of the KAN's advantages (Paper #2): a capability scorecard across all six
models and a parsimony/efficiency analysis (accuracy vs trainable parameters). These crystallise why
the KAN is the preferred model — competitive accuracy, fewest parameters, and the only learner that is
both intrinsical... |
960f2b79003f2095a93c934253cca1248ef7813b2806606654ae633307ac3e13 | Python | 3,855 | 127 | #!/usr/bin/env python
# Made by Paul Kiessling pakiessling@ukaachen.de
import urllib.request
from urllib.parse import urlparse
import os
import anndata
import argparse
import shutil
import pandas as pd
import scipy
import json
import tempfile
LINKS = [
"https://linnarssonlab.org/osmFISH/osmFISH_SScortex_mouse_all... |
2cbab51c597a90100f6351b61dc505590f9f0d998893dbd82b20180506af1a46 | Python | 3,856 | 92 | import torch
import torch.nn as nn
import torch.nn.functional as F
import config.cfg_lodet as cfg
from ..layers.convolutions import Convolutional, Deformable_Convolutional
from ..layers.msr_blocks import MSR_Convset_L, MSR_Convset_M, MSR_Convset_S, MSR_Convset_L_R, MSR_Convset_M_R, MSR_Convset_S_R
from ..head.mtr_head ... |
4d558ea36adcc6d5a3d8a214566b4f7130966b39aff2e5a1a8676a81ba6d76e4 | Python | 3,856 | 113 | # 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 Optional
import torch
from . import FairseqDataset
class TransformEosLangPairDataset(FairseqDataset):
"""A :class:... |
755105045322ee73902f3c75db8dbec921bb9929925179017b863ce580fe7f9b | Python | 3,856 | 110 | import numpy as np
import pandas as pd
from scipy import stats
from ._base import BaseCITest, _CITestResult
class Pearsonr(BaseCITest):
r"""
Partial Correlation test for conditional independence.
If :math:`Z = \emptyset`, compute Pearson's correlation coefficient :math:`r_{XY}` and its two-sided p-value... |
87528406b1a63e1a5c1d0dd55b47ea8cff7fe31210ed2aa6963fff5ff4d4eef0 | Python | 3,859 | 103 | import torch
from librosa.filters import mel as librosa_mel_fn
from .audio_processing import dynamic_range_compression
from .audio_processing import dynamic_range_decompression
from .stft import STFT
from .utils import get_mask_from_lengths
class LinearNorm(torch.nn.Module):
def __init__(self, in_dim, out_dim, bi... |
1a01387e7d33bce9086627248e62a3162b5ef0307b99539033fa650d3c6092fe | Python | 3,860 | 102 | import pickle as pkl
import scipy.sparse
import numpy as np
import pandas as pd
from scipy import sparse as sp
import networkx as nx
from collections import defaultdict
from scipy.stats import uniform
from data import *
def load_data(datadir):
input_data(datadir)
PIK = "{}/datasets.dat".format(datadir)
wit... |
3716b9c415666a44cf55e1ee0a904c87fcc6b0fffaf5ec8d64442b1daafad56b | Python | 3,860 | 87 | import anndata
import os
import sys
import pandas as pd
import scanpy as sc
from tqdm import tqdm
from nicheformer.data.constants import DefaultPaths, ObsConstants, UnsConstants, VarConstants, AssayOntologyTermId, SexOntologyTermId, OrganismOntologyTermId, TissueOntologyTermId, SuspensionTypeId
from nicheformer.data.... |
5e601c5a074166930f6fe19010af19fcfe856d1df3e01349af068e9ca32285ae | Python | 3,861 | 128 | #!/usr/bin/env python3
"""Generate a jobs.sh file for SLURM array job submission.
This is step 1 of the SLURM workflow for reproducing the SymmNet paper figure.
Each line of the output file contains one `python salnet_symm.py ...` command,
one per learning_rate × seed combination. Already-completed runs (those with a... |
372300303a0058064537c8192dc343a4728287944a5576e97d7c70bfdac241aa | Python | 3,865 | 79 | import traceback
from typing import Type
from batchgenerators.utilities.file_and_folder_operations import join
import nnunetv2
from nnunetv2.imageio.natural_image_reager_writer import NaturalImage2DIO
from nnunetv2.imageio.nibabel_reader_writer import NibabelIO, NibabelIOWithReorient
from nnunetv2.imageio.simpleitk_r... |
3b21e1aa5d20d73a92691f4ef111fca3dc5b0d95bc8f651ee91d6254ffdeb682 | Python | 3,865 | 79 | import traceback
from typing import Type
from batchgenerators.utilities.file_and_folder_operations import join
import nnunetv2
from nnunetv2.imageio.natural_image_reader_writer import NaturalImage2DIO
from nnunetv2.imageio.nibabel_reader_writer import NibabelIO, NibabelIOWithReorient
from nnunetv2.imageio.simpleitk_r... |
1823c734aa425536fc0c18f6b636581cdcb988c8e5208f9bcff47c640d4282e3 | Python | 3,866 | 79 | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'ScheduleUI/ValveMapUI.ui'
#
# Created by: PyQt5 UI code generator 5.9.2
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore, QtGui, QtWidgets
class Ui_Form(object):
def setupUi(self, Form):
Form.se... |
0b3fae81f845813308687f534af41f9e0c853d396962996165cad4753d283161 | Python | 3,868 | 108 | """Culture-collection accessions: the strain identifiers running text spells.
A strain deposited in a public collection is named by the collection's acronym
and a deposit number — `ATCC 6538`, `DSM 22228` — and BRENDA's `cultures` table
records that string verbatim, so a span carrying one reaches a strain with no
name... |
31209ba56a336112e3858310ccceafd2b8d530a0170ec4a2d1681a22bf9487bb | Python | 3,868 | 109 | """The release script refuses rather than half-releasing.
Every check here guards a step that cannot be undone once it is published: a
tag is immutable the moment anyone fetches it, and a changelog commit with no
tag beside it is a release that does not exist. The classification of a commit
subject is pinned too, beca... |
ef73aeba84f2d377eccc046f7be2f71e11672809a24b846b9cd0fa287cde33f7 | Python | 3,871 | 108 | """The package `__init__` must not make a leaf import pay for the model stack.
`d3text.models.__init__` used to re-export the three model classes eagerly, so
importing any submodule of the package ran `base` and everything behind it —
transformers, lmdb, sklearn, `d3text.utils` — whatever the importer actually
wanted.... |
b739266618a479ebe5fab4ff2b384470fe9e1196b5aed95bec9a0c243c4c9f5a | Python | 3,873 | 111 | # 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 collections import OrderedDict
from torch.utils.data import Dataset
from torch.utils.data.dataloader import default_collat... |
eab81e3421469b9d96f18fb1c35f798206eba75936b5eb7d6e810f3619134505 | Python | 3,873 | 104 | """Class representing the model table of a toml configuration file."""
from __future__ import annotations
from attrs import asdict, define, field
from attrs.validators import instance_of
from .. import models
MODEL_TABLES = [
"network",
"optimizer",
"loss",
"metrics",
]
@define
class ModelConfig:
... |
773787e5dfed95097de76904e5dbb586bfd30686d8ec98a2a08fd3af3a190b66 | Python | 3,877 | 114 | """Explicit registration of GPN model families with Transformers AutoClasses."""
from threading import Lock
from typing import Literal
ModelFamily = Literal["ss", "msa", "phylo", "star"]
_FAMILIES: tuple[ModelFamily, ...] = ("ss", "msa", "phylo", "star")
_registered_families: set[ModelFamily] = set()
_registration_l... |
d1a227880c95e8c195eac4f5a16e47b875d2ae00cf761894ebf6b8cc19a91072 | Python | 3,878 | 160 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""decorators for functions"""
from matplotlib.colors import LinearSegmentedColormap
transparent_binary_cmap = LinearSegmentedColormap(
name="transparent_binary",
segmentdata={
"red": [
(0, 0, 0),
(1, 1, 1),
],
"gr... |
0c855f48fc78f4e6d55f2683311d8c83874b2f6cb233250497888aff56015790 | Python | 3,882 | 107 | """
Positional Encoding Modules for Spatial Coordinates
Various positional encoding schemes for 2D and 3D spatial data, including
sinusoidal encodings and learnable Fourier features.
"""
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the license foun... |
c24529204f0c4b83a53f3bbd404f3d5e8a7facb48391d7d104959a3957113c51 | Python | 3,883 | 139 | """fixtures relating to annotation files"""
import crowsetta
import pytest
import tomlkit
from .config import GENERATED_TEST_CONFIGS_ROOT
from .test_data import SOURCE_TEST_DATA_ROOT
ANNOT_FILE_YARDEN = SOURCE_TEST_DATA_ROOT.joinpath(
"spect_mat_annot_yarden", "llb3", "llb3_annot_subset.mat"
)
@pytes... |
c4c76f0c99b13e04fcde55393647f9ca90fc5bcbc3bd00f1f292d30fcbfee68f | Python | 3,883 | 132 | #!/usr/bin/env python
# ENCODE DCC pseudo replicator wrapper
# Author: Jin Lee (leepc12@gmail.com)
import sys
import os
import argparse
import multiprocessing
from encode_common import *
def parse_arguments():
parser = argparse.ArgumentParser(prog='ENCODE DCC pseudo replicator.',
... |
08931ac67d76145a78a2cb2699e0ecb62ba2e85244f076c730806a4b7927c657 | Python | 3,884 | 109 | #!/usr/bin/env python
# ENCODE annot_enrich (fraction of reads in annotated regions) wrapper
# Author: Daniel Kim, Jin Lee (leepc12@gmail.com)
import sys
import os
import argparse
from encode_lib_common import (
run_shell_cmd, strip_ext_ta,
ls_l, get_num_lines, log)
import warnings
warnings.filterwarnings("ig... |
49e4da6ecdf286b5c1562cc745240360cca9e2c55079715b6c5acd5399f3dd28 | Python | 3,885 | 103 | from __future__ import annotations
from collections import defaultdict
from functools import cached_property
from html import unescape
from typing import TYPE_CHECKING
from poetry.core.packages.utils.link import Link
from poetry.repositories.link_sources.base import LinkSource
from poetry.repositories.link_sources.b... |
baf84042fd7be982b351bd523f0a44af21529ccc12673694cf5e19a3fcca1159 | Python | 3,885 | 103 | #!/usr/bin/env python
import unittest
import sys
import shutil
import os
import io
import re
import gzip
import numpy
if "DEBUG" in sys.argv:
sys.path.insert(0, "..")
sys.path.insert(0, "../../")
sys.path.insert(0, ".")
sys.argv.remove("DEBUG")
import metax.Formats as Formats
from M00_prerequisites i... |
32e21b912b9684a28bdc343886252ea20b76185eede138b987ee5d082322e0db | Python | 3,886 | 126 | """Utility functions for brenda_references"""
import string
from collections.abc import Iterable
import nltk
import pandas as pd
from aiotinydb.middleware import AIOMiddlewareMixin
from rapidfuzz import fuzz
from tinydb.middlewares import CachingMiddleware as SyncCachingMiddleware
class CachingMiddleware(SyncCachin... |
f5f568fe5957e48bd56247dea0f9cc942bf8883573a12acd9dc3506fa9156c56 | Python | 3,886 | 91 | #!/usr/bin/env python
import polars as pl
from src.utils import gtf_to_SJ, read_gtf
import argparse
def get_CSSs(predicted_cds_gtf, annotation_gtf, out, novel=True, feature="exon"):
"""
Get novel canonical splice sites present in the predicted GTF but not the GENCODE GTF.
A splice site is considered novel ... |
4790cd1e397d0d10efd95925316c702fd30e24a91ac33032e90751d3ea69add4 | Python | 3,889 | 119 | from __future__ import annotations
import pandas as pd
import pytest
from src.processing.cluster_detection import (
find_longest_cluster_times,
group_clusters_by_time_period,
identify_clusters,
process_cluster_window,
select_peak_clusters,
select_stim_clusters,
)
def test_identify_clusters_m... |
8c4a24c5d67ffe276be48819dcfd34c457532f6596ec50ddb53e842beac66aad | Python | 3,889 | 111 | import glob
import os
import subprocess
import sys
import time
import matplotlib
import numpy as np
import pandas as pd
import torch
from Bio.PDB.Polypeptide import index_to_one, one_to_index
from torch.utils.data import DataLoader, Dataset
from rasp_model import (
CavityModel,
DownstreamModel,
Residue... |
9c09873fb7023cd1e6f02a4ed23137a3e4cd495e3edcda6ddefefd82d2ae1e6b | Python | 3,890 | 71 | #!/usr/bin/env python3
"""TOC graphic -- exigencia 4 do escritorio da ACS (e-mail de 11/09/2026).
Quadro do achemso = 3.25 x 1.75 in. Gerado em 3.05 x 1.62 in SEM bbox_inches='tight'
(o tight distorce o aspecto; armadilha registrada no JPCL), incluido com
width=3.05in e centralizado com \\vspace*{\\fill} dentro do toc... |
24e424c7f9123e6ff3239297def62a67441518702ec01e7d902d1a3e01234302 | Python | 3,891 | 107 | """
This module inference sequences embeddings.
Author: wangning(wangning.roci@gmail.com)
Date : 2022/12/7 7:41 PM
"""
from Bio import SeqIO
import paddle
from paddlenlp.utils.log import logger
from paddlenlp.data import Stack
from paddlenlp.transformers import ErnieModel
from dataset_utils import seq2input_ids
fr... |
54dba78707e510b73a1488fdfcc4f69f3a3806d31f9ef35a6d4ffcb8ba470180 | Python | 3,894 | 73 | from dynamic_network_architectures.architectures.unet import ResidualEncoderUNet, PlainConvUNet
from dynamic_network_architectures.building_blocks.helper import convert_dim_to_conv_op, get_matching_batchnorm
from dynamic_network_architectures.initialization.weight_init import init_last_bn_before_add_to_0, InitWeights_H... |
a166464360c119202c78edaccfe3b4e23f912553863ef865f9ccc91fa909a70c | Python | 3,894 | 88 | #!/usr/bin/env python3
from collections.abc import Callable
from typing import Any
from bpreveal.internal import interpretUtils
from bpreveal import logUtils
from bpreveal import utils
from bpreveal.internal import interpreter
from bpreveal.internal.constants import ONEHOT_AR_T
import numpy as np
def minmaxMetric(hea... |
b2615655b9e938d60c1fbfbeb11f63790dc9062803a3857220407ffd6ea50dd7 | Python | 3,895 | 70 | import os
opdir='/Volumes/My_Passport/150423_journal_44/'
#noiselist = ['0.00' ,'0.02' ,'0.04' ,'0.06' ,'0.08' ,'0.10' ,'0.12' ,'0.14' ,'0.16' ,'0.18' ,'0.20' ,'0.22' ,'0.24' ,'0.26' ,'0.28' ,'0.30']
#noiselist = ['0.26' ,'0.28' ,'0.30']
#noiselist = ['0.00' ,'0.02' ,'0.04' ,'0.06' ,'0.08' ,'0.10','0.12' ,'0.14']
nois... |
953cfb4d33adec309f8c71c5c6290978f95d78d205c3ecebc5528dd9d21b4df5 | Python | 3,896 | 115 | import os
import mne
print('Starting now with preprocessing')
base_dir = './derivatives/'
directory_path = "./data/"
# Initialize a set to store unique participant identifiers
unique_participants = set()
# Iterate over the files in the directory
for filename in os.listdir(directory_path):
# Check... |
1d96d334412e704c8ebcb18f4db7a22e763952d99b39736f5dbe5ea5ea817ddf | Python | 3,897 | 122 | from __future__ import annotations
from pathlib import Path
from typing import TYPE_CHECKING
from typing import ClassVar
from cleo.helpers import option
from poetry.console.commands.command import Command
if TYPE_CHECKING:
from cleo.io.inputs.option import Option
class PublishCommand(Command):
name = "pu... |
524fb9816a7d5dc944da3e2708d2088affbe55c2f4718517f1239af51fe512b1 | Python | 3,898 | 97 | import ast
import sys
import tempfile
import unittest
from pathlib import Path
import numpy as np
import trimesh
MODULE_DIR = Path(__file__).resolve().parents[1]
if str(MODULE_DIR) not in sys.path:
sys.path.insert(0, str(MODULE_DIR))
from stl_mesh_pipeline import ( # noqa: E402
build_stl_meshes,
export... |
fcd7e3d67edb1e9ec3f9d90d66b8f788300892ea3f035a90f8c0f22e86729fa0 | Python | 3,900 | 105 | #!/usr/bin/env python3
"""Make a PISA plot or graph (depending on the input json).
BNF
---
.. highlight:: none
.. literalinclude:: ../../doc/bnf/makePisaFigure.bnf
Parameter notes
---------------
``graph-configs``, ``plot-configs``
A list of configurations appropriate for the functions in
:py:mod:`plotting... |
21c42416a770727c6c9b0154c0945a040de18e2304d7101cc31f56f90c591ef8 | Python | 3,905 | 121 | # 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 logging
import torch.nn as nn
from fairseq.model_parallel.modules import (
ModelParallelTransformerDecoderLayer,
ModelParalle... |
b97a94bf1fd7db25b828a50d61efce5312a1d6ab083bf6c55f9cc01ffd6ff452 | Python | 3,905 | 148 | import argparse
import random
import numpy as np
def cut_no_overlap(length, kmer=1, max_prob=0.5):
cuts = []
while length:
if length <= 509+kmer:
cuts.append(length)
break
else:
if random.random() > max_prob:
cut = max(int(random.random(... |
8ed05b3145f817f882c1287249b8a7652141fe4498d5d034496b2cda9a776630 | Python | 3,906 | 98 | """Implementation of a bucketed data sampler from PyTorch-NLP.
Modified by Roshan Rao.
See https://github.com/PetrochukM/PyTorch-NLP/
"""
import typing
import math
import operator
from torch.utils.data.sampler import Sampler
from torch.utils.data.sampler import BatchSampler
from torch.utils.data.sampler import SubsetR... |
50d8aea510d76ceb74c6c14f32dfe5de5f485b853d2966c70a09fb3231246e32 | Python | 3,907 | 73 | import os
opdir='/Volumes/My_Passport/140423_journal_4/'
#noiselist = ['0.00' ,'0.02' ,'0.04' ,'0.06' ,'0.08' ,'0.10' ,'0.12' ,'0.14' ,'0.16' ,'0.18' ,'0.20' ,'0.22' ,'0.24' ,'0.26' ,'0.28' ,'0.30']
#noiselist = ['0.26' ,'0.28' ,'0.30']
#noiselist = ['0.00' ,'0.02' ,'0.04' ,'0.06' ,'0.08' ,'0.10','0.12' ,'0.14']
noise... |
c8184fd623a6bb89e08fa3a2905cf53ba36015526628b81a8c81421f670f9f3e | Python | 3,907 | 106 | #!/usr/bin/env python3
import os
import sys
import pickle
import argparse
import numpy as np
import pandas as pd
from tqdm import tqdm
from sklearn.metrics import roc_auc_score, f1_score, average_precision_score
import torch
import torch.nn.functional as F
from torch.utils.data import DataLoader
sys.path.append("../sc... |
6a94e8b62393af986fcc408e159aca88d2b0720a221ccc7c8b24d67031c43213 | Python | 3,909 | 121 | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import logging
import os
import subprocess
from pathlib import Path
from typing import Any, List, Sequence
from hydra.core.singleton import Singleton
from hydra.core.utils import JobReturn, filter_overrides
from omegaconf import OmegaConf
log = lo... |
078acc29cb26ef58d178a5d0111bb67fff210bc280f8c48c0ea43674881d2b53 | Python | 3,912 | 113 | """
Simple check list from AllenNLP repo: https://github.com/allenai/allennlp/blob/master/setup.py
To create the package for pypi.
1. Change the version in __init__.py, setup.py as well as docs/source/conf.py.
2. Commit these changes with the message: "Release: VERSION"
3. Add a tag in git to mark the release: "git... |
30d6ae143e81b6e0b411786c5d718db1e81896c93463baad6c030065df5e7dc5 | Python | 3,912 | 106 | import numpy as np
import pandas as pd
import pytest
from pgmpy.ci_tests import ChiSquare
@pytest.fixture
def test_chi_square():
df_adult = pd.read_csv("pgmpy/tests/test_estimators/testdata/adult.csv")
test = ChiSquare(data=df_adult)
return test
def test_chisquare_adult_dataset(test_chi_square):
#... |
85d515bb26ae5efc00c5e14fd42d1b5b0181caaaa070567f8db9ee433a7cd82c | Python | 3,912 | 72 | import numpy as np
import torch
import torchvision.transforms as transforms
from utils.PerlinBlob import *
def circle_grad(img_res_y, img_res_x):
center_x, center_y = img_res_x // 2, img_res_y // 2
circle_grad = np.zeros([img_res_y, img_res_x])
for y in range(img_res_y):
for x in range(img_res_x):... |
e7aed7afa27a33cb35258e06c8d92a93ba5743bb41948d7da520db98938d803b | Python | 3,912 | 93 | #!/usr/bin/env python3
"""Build and inspect wheel/sdist artifacts from an external checkout copy."""
from __future__ import annotations
import argparse
import json
import shutil
import subprocess
import tempfile
from pathlib import Path
def validate(source: Path, python: Path, results_root: Path) -> dict:
root ... |
ea695120874fdbb658e2b8849e433f8021a3ee775e61db2906b5cdc2ffa9ee48 | Python | 3,912 | 100 | from typing import Tuple
import jax
import jax.numpy as jnp
import jax_dataclasses as jdc
from ...utils import factorial2, zero_embed
def get_cartesian_angulars(l):
r"""List x, y and z angular momenta for a given total angular momentum."""
return [(lx, ly, l - lx - ly) for lx in range(l, -1, -1) for ly in r... |
16ce8644dbdff9d139fbd75a0e514b8e24489e6df437f20f75af312e2a3d807f | Python | 3,913 | 96 | import numpy as np
import matplotlib.pyplot as plt
import matplotlib
matplotlib.use("TkAgg")
import pandas as pd
from cal_KL_div import calculate_kl_divergence
min_n = 100
max_n = 0
def get_model_bit_scores(model_name, min_n, max_n):
all_seq_score_list = []
f = open("./outputs/" + model_name, 'r')... |
e06baf5c14a2984cee6fa6076cd71e92b0755ca0fee5767780afd3b46495bf4f | Python | 3,914 | 124 | import os
import pickle
from typing import Any
import pandas as pd
import torch
from lightning.pytorch.loggers.logger import Logger, rank_zero_experiment
from lightning.pytorch.utilities import rank_zero_only
class SimpleExperiment:
"""Simple experiment class."""
def __init__(self):
self.data = {}
... |
fc5f8654c79d2378da9e47225631bb4fa6861163ceeeca4726f663a08b274374 | Python | 3,915 | 114 | """
This script is a modified version of the code in the following link to support
the current requirements of this repository.
source: https://github.com/zbmed-semtec/medline-preprocessing/tree/main/code/Cosine_Similarity
author: Vishnu Vardhan Dadi
credits: [Rohitha Ravinder, Leyla Jael Castro, Dietrich Rebholz-Schu... |
49142594578a543ccef349d44d320dca4ca8a4a051c39019e6bb31fccd3c5144 | Python | 3,916 | 96 | """Fixture-based GB energy parse golden (kcal/mol component means).
This is not a full AmberTools end-to-end regression. It locks the
mdout → EnergyVector → BindingStatistics path so GB totals cannot drift
silently. See scripts/validation/README.md for adding Amber binaries goldens.
"""
import tempfile
import unittes... |
a1cbdaf11a9e885bb2515bfc46921bc940c8796dd0318e0fde2da89bde1da77e | Python | 3,918 | 94 | def validate_split_durations(train_dur, val_dur, test_dur, dataset_dur):
"""helper function to validate durations specified for splits,
so other functions can do the actual splitting.
First the functions checks for invalid conditions:
+ If train_dur, val_dur, and test_dur are all None, a ValueError... |
c3629ec79c428bb458498d0386c564acd6c6c606bbc8645e40824b4fed569e3d | Python | 3,919 | 89 | # scSGL - a python package for fene regulatory network inference using graph signal processing based
# signed graph learning
# Copyright (C) 2021 Abdullah Karaaslanli <evdilak@gmail.com>
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as pu... |
a0ceb34319994f9fdb57f85907adfdddbe3abaf784cf4de58d5b7d5ffd9d035d | Python | 3,921 | 98 | import pandas as pd
import gc
from preprocessor.utils.preprocess_intrinsic import preprocess_intrinsic
from preprocessor.utils.preprocess_synaptic import preprocess_synaptic
class MembraneCurrentPreprocessor:
"""
Preprocesses intrinsic and synaptic currents and combines them into membrane currents.
"""
... |
cdd9ddbab7128a6d48b2fa4da906622665a93dc43d182bbcf48e837e85e5583b | Python | 3,923 | 116 | import pandas as pd
import logging
import gzip
import shutil
import requests
from pathlib import Path
from typing import List
from src.data.manager import DatasetManager
log = logging.getLogger(__name__)
class ECODManager(DatasetManager):
def __init__(self, filepath_dir: str="data/", version=292):
"""
... |
8c073b1adeac21b71b572db7cba7f20fc97c8d7308c9698fe1f5934934e195ec | Python | 3,924 | 109 | # 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... |
2ef62f02c3027e95370f81dd1c0a0b0b4515b51efb05f0d1a68b6eeb367e91ff | Python | 3,925 | 74 | # Copyright 2020 Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://w... |
46bf84258fdb9f094fbc694dd77a43a75c3f7629f0a80c4b97cebd5c961003d4 | Python | 3,925 | 108 | #!/usr/bin/env python
"""Neural pattern similarity across participants — single-condition (R4) and
triple / across-condition (R5).
Per parcel: mean the BOLD over each excerpt's 60 s window -> spatial pattern;
correlate each participant's pattern with the leave-one-out group mean (single),
or take the sign-consistent a... |
928cb60e76c940be697d1760e09eb60260e5e437d3ef1e78b2a9c0fe93b4dbc6 | Python | 3,925 | 121 | from math import isclose
from skbase.utils.dependencies import _safe_import
from sklearn.exceptions import ConvergenceWarning
from pgmpy import logger
from pgmpy.utils._warnings import _warn_external
torch = _safe_import("torch")
optim = _safe_import("torch.optim")
def pinverse(t):
"""
Computes the pseudo-... |
6729d0a1924a2547b6c9af610b087a43c0d45a599c4ac26b23719d8e715eb2f6 | Python | 3,926 | 99 | from typing import List
import numpy as np
import pandas as pd
from harmony import harmonize
from scipy.stats import ks_2samp
from sklearn.decomposition import IncrementalPCA
import loompy
from cytograph.preprocessing import Normalizer
import logging
class PCA:
"""
Project a dataset into a reduced feature space u... |
62f94c578cff83f0dc81af983665da9d6722f12085181fd833cddb5f40147937 | Python | 3,927 | 83 | from pathlib import Path
import re
import unittest
ROOT = Path(__file__).resolve().parents[1]
class BuildEditionTests(unittest.TestCase):
def test_version_is_single_source_for_both_builds(self):
source = (ROOT / "SegRef3D.py").read_text(encoding="utf-8")
version = re.search(r'^__version__\s*=\s*... |
ec8d3ea793ba11500db04d3b84673880400ececc40a48503305bf090e0c3c902 | Python | 3,927 | 94 | import torch
import torch.nn as nn
import torch.nn.functional as F
# source: https://github.com/kaijieshi7/Dynamic-convolution-Pytorch/blob/master/dynamic_conv.py
# zhihu: https://zhuanlan.zhihu.com/p/142381725
# zhihu: https://zhuanlan.zhihu.com/p/208519425
class attention2d(nn.Module):
def __init__(self, in_plan... |
6db82c1aa1d8cd745f2557dec7eb864bbe6d1c9f70936962af5a0365cbc7bb3f | Python | 3,928 | 108 | """
03_celltype_deconvolution.py
NNLS cell-type deconvolution and adjusted enrichment analysis.
Estimates cell-type proportions, then recomputes PCDH coordination
scores using partial correlations controlling for cell-type fractions.
Harbert D. (2026) BMC Genomics
"""
import sys, os
sys.path.insert(0, os.path.dirnam... |
fd675534fc54b761c9d6a7735b9f4bac0f33e51a2121206218aa69fb85a2f6c9 | Python | 3,929 | 121 | #!/usr/bin/env python3
"""
Author: Ken Chen
Email: chenkenbio@gmail.com
Date: 2022-11-24
"""
import os
import sys
import pickle
from tqdm import tqdm
import argparse
import numpy as np
import matplotlib.pyplot as plt
new_rc_params = {'text.usetex': False, 'svg.fonttype': 'none' }
plt.rcParams.update(new_rc_params)
im... |
2f3a24121915b9223b0d5ac4c8018cc9b3fc5b58877ff37ff88e976024744502 | Python | 3,932 | 98 | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import torch
from mattergen.common.diffusion import corruption as sde_lib
from mattergen.common.utils.data_utils import compute_lattice_polar_decomposition
from mattergen.diffusion.corruption.corruption import Corruption, maybe_expand
from matte... |
34f4be7963b44aa9b8a58408e4c40e4fe087e99bb81e5977427cb4e1034c6d6b | Python | 3,936 | 153 | #
# Copyright 2017-2023 Sandia Corporation. Under the terms of Contract DE-AC04-94AL85000 with
# Sandia Corporation, the U.S. Government retains certain rights in this software.
#
# See LICENSE for full license details
#
import numpy as np
from ...backend import ComputeBackend
xp = ComputeBackend()
STYLES = (
"S... |
7e8ead3ccac38b8d1f818b7b6d19e43548c3cb8f196e70104f13792a32d01512 | Python | 3,936 | 133 | import pytest
from apiadapters.ncbi import AsyncNCBIAdapter
from apiadapters.straininfo import StrainInfoAdapter
from brenda_references import expand_doc
from d3types import Bacteria, Document, Organism, Strain
from lpsn_interface import get_lpsn, lpsn_id, lpsn_synonyms, name_parts
get_lpsn()
straininfo = StrainInfoAd... |
291243717b999671db6fd2e11e9661a87f18bdd1f0eef061f2e3eed95d4091e4 | Python | 3,937 | 113 | # 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 glob
import argparse
import pprint
import omegaconf
from omegaconf import OmegaConf
from torch.utils.data import DataLoader
... |
849b6703ad14112a7df5a167ecf4a7cad25025d33367cc4b372c7f0f74147496 | Python | 3,937 | 96 | """Orchestrate ``summary.log`` for dynamic segmentation (aligned with DLBase ``tasks/classification/run.py``)."""
from __future__ import annotations
import os
from datetime import datetime
from typing import Any
import torch
from omegaconf import DictConfig
from pytorch_lightning.utilities.rank_zero import... |
4c0e8509bcca1055dc16396676900c6d4a019cda71815f87be36e7846dc715d8 | Python | 3,940 | 115 | """
Model class
"""
import warnings
warnings.filterwarnings("ignore")
import math
from torch import nn, Tensor
from torch.nn import TransformerEncoder, TransformerEncoderLayer
import sys
sys.path.append('../')
from typing import Any
import torch
def full_block(in_features, out_features, p_drop=0.1):
return nn.... |
548554bdb1f9958cd3d272397d1d2202a66c26ce1a11bd52cda1255dd5733715 | Python | 3,940 | 103 | """Pure unit tests for the vocabulary-independent helpers in data/data.py.
None of these touch HDF5 or the BRENDA files (see tests/data/test_dataset.py
for the fixture-backed dataset tests).
"""
import numpy
import pandas as pd
import pytest
import torch
from d3text.data.data import BrendaDataset, compute_frequencie... |
e3c6f136d5e1801c5067f7e02dd8d0f3cf532fb7bcd0223500189c8149785ef3 | Python | 3,940 | 104 | # encoding: utf-8
"""
@author: Jiayang Chen
@contact: yjcmydkzgj@gmail.com
CATH 20201021 database
"""
import os
import pandas as pd
from redevelop.data.datasets.utils import *
from redevelop.data.datasets.bio_seq import BIO_SEQ
from Bio import SeqIO
class Custom(BIO_SEQ):
def __init__(self, root, data_type="se... |
ef1aafda7c337c1567a442dad1a0a7a142228062042b2d312b776ed36403b54c | Python | 3,940 | 133 | import pytest
from apiadapters.ncbi import AsyncNCBIAdapter
from apiadapters.straininfo import StrainInfoAdapter
from brenda_references import expand_doc
from d3types import Bacteria, Document, Organism, Strain
from lpsn_interface import lpsn_id, lpsn_synonyms, name_parts
straininfo = StrainInfoAdapter()
caldanaerobac... |
044bff7f04bb21570da24e92d5728131dc54c3b15d4ed4c97d036f8b33c2d523 | Python | 3,941 | 103 | import numpy as np
from pgmpy.base import DAG, PDAG
from pgmpy.metrics import BaseSupervisedMetric
class SHD(BaseSupervisedMetric):
r"""
Computes the Structural Hamming Distance (SHD) between two graphs.
Given two graphs (DAGs or PDAGs) :math:`G_1` and :math:`G_2` over the same vertex set, let :math:`S(... |
57fea405991a43a677a3d0bb87219394437a09d3197092fbd291350df9d663eb | Python | 3,941 | 99 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""The setup script."""
from setuptools import find_packages, setup
def get_extra_requires(path, add_all=True):
"""Parse an optional-dependencies file into a setuptools ``extras_require`` mapping.
``path`` is a *standard* pip requirements file: one requirement ... |
9f856c8f38471deb16ea543bd51eadbb54f7a221d76f421d5d55817d0e1fd866 | Python | 3,941 | 110 | """
Some sanity checking of polarisation/phasing options for different processors
"""
import numpy as np
import sys
import os
import pytest
sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", "workflow", "scripts"))
import ts_simulators
import ts_processors
def test_genotypes_and_distances():
one_po... |
f39261d6e16eab48ebdd7eb7d1b68a4cfef84e496f2f40cd8bc07c77cfbcca3b | Python | 3,941 | 88 | # Copyright (C) 2025 ETH Zurich, Moritz Thürlemann, and other AMP contributors
import json
import os
import numpy as np
from pathlib import Path
def write_qm_mm_json(path:str):
parameters = {}
parameters["qm_zone_resnames"] = ["UNL"]
parameters["mm_zone_resnames"] = ["HOH"]
with open(path, "w") as ... |
a893ae8c3f6e0f6feab6ac3365ba1009580de49f80578b6c65c4ce9a6862f33e | Python | 3,943 | 93 | #!/usr/bin/env python3
# Florian Bénitière 16/03/2025
# Script to generate a .parquet file by merging all TSV gVCF files from a directory
import os
import shutil
import sys
import pandas as pd
import subprocess
import psutil # System and process utilities
from math import floor # For rounding down numbers
from col... |
dfa7a07afda12c5aa896b1b0b538b2f79709dca5d8b2a3b9db279723bae69a17 | Python | 3,943 | 99 | import os
import pandas as pd
import numpy as np
from neuron import h
# Dictionary mapping current types to their corresponding NEURON attributes
# current_types = {
# 'nax': '_ref_ina_nax',
# 'nad': '_ref_ina_nad',
# 'car': '_ref_ica_car',
# 'kdr': '_ref_ik_kdr',
# 'kap': '_ref... |
7ede8a62a11758835a5a06adf4dd4f73284051716af0746fa23d4a7559bc6b9e | Python | 3,944 | 112 | import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from scipy.stats import shapiro, ttest_rel, ttest_ind, wilcoxon, mannwhitneyu
# Set font to Times New Roman
plt.rcParams["font.family"] = "Times New Roman"
# Load the Excel file
file_path = "path_to/Database_comparison.xlsx"
df = pd.r... |
ee7b25dcf7d61d5f8b07e2371549ec19f080115137a285f6e220b7af4a19a29e | Python | 3,945 | 127 | """Build Wave-1.5 feature matrix for perovskite candidate pool (n=1784).
Mirrors data/mofs_qmof/build_wave15.py: adaptive CT2F + Madelung-CT2F + CT3F
on each perovskite supercell, with charges taken from `formal_charges`
(ionic Cs+/K+, Pb+2/Sn+2/Ge+2, I-/Br-/Cl-/F-).
"""
from __future__ import annotations
import json... |
fedae29612be4d8436ff449b5aab8fe38836f6cbc1e6360f0d4d5d0925135c1b | Python | 3,946 | 124 | import typing
import os
import logging
from abc import ABC, abstractmethod
from pathlib import Path
import torch.nn as nn
from tensorboardX import SummaryWriter
try:
import wandb
WANDB_FOUND = True
except ImportError:
WANDB_FOUND = False
logger = logging.getLogger(__name__)
class TAPEVisualizer(ABC):
... |
48ee7cd04bba1593f6158b677c588f1064d87e2c5f6fdd83f0bad1306d50616d | Python | 3,949 | 137 | # 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 ast
import argparse
import json
import logging
from pathlib import Path
import soundfile as sf
import torch
from tqdm import tqdm
fro... |
944bae494e9abc9d76f9dc79628fab86a525abcb0ae55773088ecf8a21f1664d | Python | 3,950 | 107 | """What an evaluation logs when sklearn cannot score the class head.
A diverged head scores NaN, which `average_precision_score` refuses outright.
`evaluate_model` hands its dict to tracking in a single call at the end, so a
raise there cost the whole pass — every count already measured included —
rather than one numb... |
c20013d5cbad134f3df88b82fc905eb939f38f9d6500af8ce7a9004abffd7f56 | Python | 3,950 | 114 | # /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(gpu_index=0):
'''
This function is to im... |
8895b62e97190adcd9feeb46cbc20eb7079d9377db4da2209eceb875ed0bf23d | Python | 3,952 | 76 | #!/usr/bin/env python3
# MIT License
#
# Copyright 2024 Broad Institute
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to u... |
adbeba6fe3f9fbef2baf096cc0582a3528bbbd8c26d72124865735d7cb8c1da9 | Python | 3,952 | 114 | # /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 scipy.io as sio
import CBIG_pMFM_basic_functions as fc
import warnings
def CBIG_pMFM_generate_simualted_fc_fcd(gpu_index=0):
... |
fbc8b385b227f70fa2a74d3952ab88336bd6d9af5a7cc72981f4ce3068c36522 | Python | 3,953 | 107 | import torch
import numpy as np
from typing import List, Callable
from pytorch_grad_cam.base_cam import BaseCAM
from pytorch_grad_cam.metrics.road import ROADCombined
def batch_pearson_coherency(A: np.ndarray, B: np.ndarray) -> np.ndarray:
"""
Computes Pearson correlation for a batch of matrices.
"""
... |
87d8a1325d39ec288155179847691567b68b49c0e15c873c8f6537f9cc939658 | Python | 3,954 | 77 | #04 3
"old DET"
import sys
sys.path.append("..")
from modelR.backbones.mobilenetv3 import MobileNetV3
from modelR.backbones.mobilenetv2 import MobilenetV2
# from modelR.necks.conv_csa_drf_fpn_hbb import Conv_CSA_DRF_FPN,FC2_CSA_DRF_FPN,Cat_Conv_CSA_DRF_FPN,M_CSA_DRF_FPN
from modelR.necks.Three_Head import FC2_CS... |
ba23e883d5b04bab18bad3599c67e4d501ea6555d4e7f0ff5f27069fa2238583 | Python | 3,954 | 149 | import numpy as np
def affine_transform(
coords: np.ndarray, matrix: np.ndarray, inverse: bool = False
) -> np.ndarray:
"""Perform an affine transform of coordinates.
Args:
coords: array of points with shape (3, ...)
matrix: the transformation matrix
inverse: do an inverse transfo... |
5440264a60dcffe8dea07dd3e2dde399888ca7a2b154832f52071962eb3e7e30 | Python | 3,955 | 98 | #!/usr/bin/env python3
"""SUPERSEDED by build_rna_sex_persample.py, which is what produced the reported numbers.
This earlier implementation uses a 1.0-SD gap threshold and a single inference route; the
shipped analysis uses 0.85 SD and three per-series routes. Retained for provenance only.
Its output paths pointed at ... |
812bccb8e66fee814967a54f18622ab8be5ee98d17075fb49be0fc0fcef098fa | Python | 3,955 | 100 | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
from typing import Callable
import torch
from mattergen.diffusion.sampling.pc_sampler import Diffusable, PredictorCorrector
from mattergen.common.data.collate import collate
BatchTransform = Callable[[Diffusable], Diffusable]
def identity(x:... |
a8bc7653c76def4293726858a7cd223bec91a550356b275f4b6bbaf6d6a7eeb7 | Python | 3,955 | 122 | # 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 numpy as np
from fairseq.data import FairseqDataset
from . import data_utils
from .collaters import Seq2SeqCollater
class... |
b9ab4747c983c2d373dccc02f551b498877d70c8a215d0736e9fc23b6bcfda32 | Python | 3,955 | 113 | #!/usr/bin/env python3
#########################################
# Author: [DonFreed](https://github.com/DonFreed)
# File: license_message.py
# Source: https://github.com/DonFreed/docker-actions-test/blob/main/.github/scripts/license_message.py
# Source+commit: https://github.com/DonFreed/docker-actions-test/blob/aa10... |
0168ab050cab05a9db7bb41ce7c171f04317234769bd15a932ef1b11695f596c | Python | 3,956 | 99 | import os
import numpy as np
import matplotlib.pyplot as plt
def scatterPlot(X_f,figHeight,figWidth,filename):
Yaxis = np.zeros((X_f.shape[0],1),dtype = np.float64)
plt.figure(figsize=(figWidth,figHeight))
plt.scatter(X_f[:,0:1], Yaxis[:,0:1], marker='o', color='black', s= 0.15)
plt.tight_layout()
... |
4da03dfe6063e574ed1a67d7e3ecc7866f263355b54dd9e6894866f246069cd2 | Python | 3,956 | 119 | import argparse
import torch
import torch.nn.functional as F
import numpy as np
import cv2
def gaussian_blur(x, k=31, sigma=7):
"""Simplified separable Gaussian kernel."""
coords = torch.arange(k, device=x.device, dtype=x.dtype) - (k // 2)
g1 = torch.exp(-(coords ** 2) / (2 * sigma ** 2))
g1 /= g1.sum... |
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