sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
8cdb43e3479d61ad64eed7254238a89098ba1b417da7f53436ad824f05c73e64 | Python | 9,713 | 216 | import os
import msvcrt # For Windows systems
'''
By properly implementing file locking mechanisms like using msvcrt for Windows systems,
one can ensure that the Optuna optimization process runs smoothly without encountering
race conditions or file locking issues, even when using multiple processes (n_jobs > 1).
'''... |
34d15b17afabffd82f724272764e02f309743553f36c14da8badb64cd97dc031 | Python | 9,714 | 256 | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICEN... |
1f8c539c3386226d0c9c1294c45641ff873d80095482db6adf2c16b34528a49c | Python | 9,715 | 203 | import torch
import numpy as np
import torch.nn.functional as F
import torch.nn as nn
from utils import *
from self_calibration import *
from torch.fft import fftshift, ifftshift, ifft2, fft2
from fft_conv_pytorch import fft_conv, FFTConv2d
dtype = torch.float32
class forward_model_lsm_variant(nn.Module):
def __i... |
7d0d87884393f5ba7e1e55309d13c4e19f5b41dfc075ab358c86a2383670747b | Python | 9,715 | 246 | """Class and functions for ``[vak.prep]`` table of configuration file."""
from __future__ import annotations
import inspect
import dask.bag
from attrs import converters, define, field, validators
from attrs.validators import instance_of
from .. import prep
from ..common.converters import expanded_user_path, labelse... |
9574849e2354a9190adafcbcf887835c1ba853bc81d9c556abf327f8929b1f2d | Python | 9,716 | 290 | import torch
import torch.nn.functional as F
import numpy as np
from math import log10
"""
At Pado, all measurements adhere to the International System of Units (SI).
"""
nm = 1e-9
um = 1e-6
mm = 1e-3
cm = 1e-2
m = 1
s = 1
ms = 1e-3
us = ms * 1e-3
ns = us * 1e-3
def wrap_phase(phase_u, stay_positive=False):
"""
... |
5b6883bb8d2db7b68c0cf400c7836f8a40299875732f76f425cdbbf106138d7e | Python | 9,717 | 215 | import os
import fcntl # For Unix-like systems (including Ubuntu)
'''
By properly implementing file locking mechanisms like using fcntl for Unix-like systems,
one can ensure that the Optuna optimization process runs smoothly without encountering
race conditions or file locking issues, even when using multiple proces... |
2f9b0ad6246bb9ef3fda5485b3f2409c26e58c5b0f53a5a12729847ffacff7c2 | Python | 9,718 | 217 | import os
import msvcrt # For Windows systems
'''
By properly implementing file locking mechanisms like using msvcrt for Windows systems,
one can ensure that the Optuna optimization process runs smoothly without encountering
race conditions or file locking issues, even when using multiple processes (n_jobs > 1).
'''... |
f2e13a5b67251162e5f5e568bb295aef75c7e9f5739501b8b3706a99acc39179 | Python | 9,718 | 368 | """Functions for input validation"""
from __future__ import annotations
import pathlib
import warnings
import numpy as np
import numpy.typing as npt
import torch
def column_or_1d(y: npt.NDArray, warn: bool = False) -> npt.NDArray:
"""ravel column or 1d numpy array, else raise an error
Parameters
------... |
091d341e84bf26065f9ee792989e488f86cc0b910c9c801e4396483361bfbd55 | Python | 9,719 | 297 | """
Unified compute-parity logging for HIPPIE / PhysMAP / NEMO benchmark runs.
The goal is a single CSV schema that every benchmark method appends to, so we
can build a per-method x per-dataset wall-clock and peak-memory table for the
Nature Comms supplement (the "compute parity" reviewers will look for).
Schema (one... |
885f649011db9546ac2e2998ffd10b33879bb705223d87ebf700c13e61c7c322 | Python | 9,720 | 217 | import os
import msvcrt # For Windows systems
'''
By properly implementing file locking mechanisms like using msvcrt for Windows systems,
one can ensure that the Optuna optimization process runs smoothly without encountering
race conditions or file locking issues, even when using multiple processes (n_jobs > 1).
'''... |
5c0873d05f7b2aa95ea319a41162ad92b41478c0c6d4aaee08b9423984118931 | Python | 9,724 | 253 | __author__ = "alvaro barbeira"
import numpy
import pandas
import copy
import math
from . import Utilities
from . import MultiPrediXcanAssociation, PrediXcanAssociation
from ..expression import HDF5Expression, Expression
#################################################################################################... |
22aa76225052d6c5f0ba91ee857300f797d27f7940d28cae4706e4e6af04e2a9 | Python | 9,726 | 268 | """
PyTorch Lightning Module for Garfield training.
This module wraps the GNN-VAE model for distributed training with PyTorch Lightning.
"""
import torch
import pytorch_lightning as pl
from typing import Dict, Any
class GarfieldLightningModule(pl.LightningModule):
"""
Lightning wrapper for Garfield GNN-VAE m... |
baefc1e3ea8bab4dc2199a0189e5af3aee94b6136b024af5d7c246f735b94036 | Python | 9,727 | 151 | import os
def create_chanmap(kilosort_location, EndChan, StartChan = 1, probe_type = '3A', Nchannels = 384, MaskChannels = []):
mask_string = '['
for channel in MaskChannels:
mask_string += str(channel+1)
mask_string += ' '
mask_string += ']'
chanmap_string = make_chanmap_strin... |
81904bddc473ea7a9d171e3bf4e31da528f1537aab699d8cdaf173c95100a15b | Python | 9,729 | 239 | """
Turn a merged corpus into tfrecord files.
NOTE: You will want to do this using several processes. I did this on an AWS machine with 72 CPUs using GNU parallel
as that's where I had the deduplicated RealNews dataset.
"""
import argparse
import ujson as json
from sample.encoder import get_encoder, tokenize_for_grove... |
246a36e73f3931235ebe4aa1805c78113048be4f95aedefed7ce12da81af40a8 | Python | 9,739 | 158 | import torch
import torch.nn as nn
from dropblock import DropBlock2D, LinearScheduler
from ..layers.convolutions import *
class MSR_Convset_L(nn.Module):
def __init__(self, filters_in):
super(MSR_Convset_L, self).__init__()
self.__dw0 = Convolutional(filters_in=filters_in, filters_out=filters_in*2,... |
371b0507549e1259be12b1bf582eca054d1c9f61ee61cad59cd76e25fb0c9387 | Python | 9,740 | 245 | from sys import float_info
import numpy as np
from .cfmm import cFastMarcher
FAR, NARROW, FROZEN, MASK = 0, 1, 2, 3
DISTANCE, TRAVEL_TIME, EXTENSION_VELOCITY = 0, 1, 2
def pre_process_args(phi, dx, narrow, periodic, ext_mask=None):
"""
get input data into the correct form for calling the c extension module
... |
8cfe3fa8331b112625430a9df186b104dae186eeee8dc678fb454501f55561aa | Python | 9,740 | 251 | import os
import h5py
import warnings
import matplotlib
import numpy as np
from scipy import stats
from sklearn import mixture
from skimage import morphology
from types import SimpleNamespace
from scipy.ndimage import median_filter
with warnings.catch_warnings():
warnings.simplefilter("ignore")
matplotlib.us... |
6c0af4b88bdd688f77bfe321d25843b7d02f2ef4cfea33f8972ec28c3378c4a4 | Python | 9,744 | 257 | import numpy as np
import subprocess
import os
import json
import struct
import func.utility_func as uf
class MCX_adapter():
'''
invision source:
https://github.com/IMSY-DKFZ/simpa
==================================Workflow==================================
1. save simulation ... |
7c2286d9b29d59f628e7b4971b65f81045d1d789b1585c62ee8c1fa5973e2ea7 | Python | 9,749 | 245 | # _*_ coding: UTF-8 _*_
# Version information START --------------------------------------------------
VERSION_INFO = \
"""
Author: ZHANG YUBO
Version-01:
2026-01 Inferring evolutionary relationship from multiple sequence alignment for three population
"""
# Version information END ----------... |
809679e77303d5443924dff088635f9cfb286f99280809351ba3c3bc7570a0a9 | Python | 9,751 | 270 | from typing import Dict, Optional, Union, Sequence
import torch
import tape
import transformers
import numpy as np
import msm
from copy import copy
import logging
from utils.align import MSA
import itertools
logger = logging.getLogger(__name__)
class Vocab(object):
def __init__(
self,
tokens: Dic... |
383926bf043c85fa69a3ac8a54aaf05de662e4926090683c4f3280f3d4d35327 | Python | 9,752 | 303 | # 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 os
import contextlib
from dataclasses import dataclass, field
from typing import Optional
from omegaconf import MISSING... |
da00df9f341a0a4d120fed2a28f26558b5abcb4ac8c615dc507b3f1400ddb461 | Python | 9,758 | 256 | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
from collections import defaultdict
from typing import Iterable, List, Mapping
import numpy as np
from pymatgen.analysis.structure_matcher import StructureMatcher
from pymatgen.core.structure import Structure
from pymatgen.entries.computed_entri... |
66ad73676fe83a011ed88d9f716acb7387d5e7a8d87c6a5eb4ede65e51043bec | Python | 9,765 | 227 | #!/usr/bin/env python
"""Fetch a URL and save its raw response body to disk as a test fixture.
RNAlysis leans on external web services (UniProt, Ensembl, PANTHER, PhylomeDB, OrthoInspector,
KEGG, GO, ...) that change formats, rename fields, and go down without notice -- see CLAUDE.md:
"External web APIs are the most f... |
c0791504b229f14ef758805077f0deeb18bf59145527b26cc78fc9ae099ad174 | Python | 9,769 | 254 | import numpy as np
from mot.lib.cl_function import CLFunction, SimpleCLFunction
__author__ = 'Robbert Harms'
__date__ = "2014-06-19"
__license__ = "LGPL v3"
__maintainer__ = "Robbert Harms"
__email__ = "robbert@xkls.nl"
class ParameterPrior(CLFunction):
"""The priors are used during model sample, indicating the... |
8e1fad1ddde3a1025bc59a7066c65ba10a0ea372fb3493915d9c129847c7c2f5 | Python | 9,770 | 282 | """Modules used on the ProteinBERT model.
This code has been modified from the original implementation
by Facebook Research, describing its ESM-1b paper."""
import math
from typing import Optional
import torch
import torch.nn as nn
import torch.nn.functional as F
from .multihead_attention import MultiheadAttention... |
827af9812451eed478567c13292dca0fedf4f6526919e0a2e0b980965fff8e7b | Python | 9,772 | 224 | # coding=utf-8
# Copyright 2018 Google AI, Google Brain and Carnegie Mellon University Authors and the HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://ww... |
0c2463010aa17b53434684b932ea4717bb5ae862ff8434dc2af61ed858c263ba | Python | 9,773 | 225 | # coding=utf-8
# Copyright 2018 Google AI, Google Brain and Carnegie Mellon University Authors and the HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://ww... |
335f82f437102408048db82277719b9f754168fb028a9194f7cd2cfc96b3728b | Python | 9,773 | 270 | from constructs import Construct
from aws_cdk import (
Stack,
Tags,
Size,
RemovalPolicy,
aws_iam as iam,
aws_ec2 as ec2,
aws_batch as batch,
aws_ecs as ecs,
aws_s3 as s3,
)
import boto3
class AwsBatchStack(Stack):
"""
References:
- https://constructs.dev/packages/@aws-c... |
d4a388cce9e4ff23d05e55f088c5cb18949ab49b913f86b2fbb54dba19b1d0ce | Python | 9,773 | 189 | 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_CSA_DRF_FPN
from mo... |
22b5278350958cad577a655c4c6408d4a9d6252dfb4ec457ef88b16ca62149d2 | Python | 9,776 | 213 | import os
'''
By properly implementing file locking mechanisms like using msvcrt for Windows systems (and fcntl for Unix-like systems), one can ensure that the Optuna optimization process runs smoothly without encountering race conditions or file locking issues, even when using multiple processes (n_jobs > 1).
'''
impo... |
918c46ca5f90bc9762536ad9206bb49f2dd3193751b0e14ef37f06c2543d23d5 | Python | 9,776 | 222 | #
# 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
#
from abc import ABC, abstractmethod
import warnings
from simulator.parameters.xbar_parame... |
dd64b0c7918ca6e75e6ff1ec8e2aeb02acf7017209f7a039fbbba99bc5f7e5d9 | Python | 9,779 | 262 | import torch
import sparse
import argparse
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from PIL import Image
from pathlib import Path
from einops import reduce, rearrange, repeat
from utils import MROI
# https://stackoverflow.com/questions/5543651/computing-standard-d... |
83215650338120d71be5d34b3784c8d9e1df35ffdb3f2e17ecae266dfe391bcb | Python | 9,780 | 262 | import numpy as np
import omegaconf
import pandas as pd
import torch
from torch_geometric.data import Data, InMemoryDataset
from utils.data.abstract_datatype import (
AbstractDataModule,
AbstractDatasetInfos,
Statistics,
)
from utils.data.load import (
character_to_int,
detect_nan_rows,
position... |
4ee47e6c3b478cf69c099ba759591af9de2a4a37ec6680d8d9235adb5ddfc905 | Python | 9,781 | 192 | #!/usr/bin/env python3
"""build_data_sources_table.py — comprehensive data-sources table for the manuscript.
Generates Supplementary Table S1 listing every contributing study with:
- GSE / PRIDE / cohort identifier
- Tissue + platform + MS / HC sample sizes
- PMID and citation anchor
- Stratum used in analysis... |
88d15db3c7fed1349e0e26b2604708df6d726415164dc37ed0674beb3201b015 | Python | 9,783 | 223 | # Copyright 2021 HIP Applied Computer Vision Lab, 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... |
faeffd0f5496de378fb036a4774c1c8d6851f98024d0eda75840b05ef9de0ed4 | Python | 9,785 | 206 | #!/usr/bin/env python3
"""A utility to calculate the input and output length of BPReveal models."""
# flake8: noqa: T201
import argparse
def getParser() -> argparse.ArgumentParser:
"""Command line arguments for the length_calc script.
:return: An ArgumentParser, ready to parse_args()
"""
parser = arg... |
fe65607b88e5e4083d1298997621b65e7ef5482cb8e3af6c29c820ba1d96739f | Python | 9,786 | 209 | from __future__ import annotations
import argparse
import json
from pathlib import Path
import numpy as np
import pandas as pd
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import average_precision_score, roc_auc_score
from st_risk.paths import current_results_dir, ensure_results_layout, project_r... |
ed8d4c48c0c7ebdf52ce32100ba672d3769996d6df5a46614b75b9b0d5e49e6f | Python | 9,787 | 213 | import os
'''
By properly implementing file locking mechanisms like using msvcrt for Windows systems (and fcntl for Unix-like systems), one can ensure that the Optuna optimization process runs smoothly without encountering race conditions or file locking issues, even when using multiple processes (n_jobs > 1).
'''
impo... |
6ceb7fa2164338af248708796056c79a2975e58f4d7c9007e004aa7acdd27a2f | Python | 9,790 | 213 | import os
'''
By properly implementing file locking mechanisms like using msvcrt for Windows systems (and fcntl for Unix-like systems), one can ensure that the Optuna optimization process runs smoothly without encountering race conditions or file locking issues, even when using multiple processes (n_jobs > 1).
'''
impo... |
97b77911439c1a82834a0d898d58f1d8cbe1d336603406f7057599d9e1148bd0 | Python | 9,792 | 203 | #!/usr/bin/env python3
"""Figura do mecanismo: o haleto domina, e o efeito do cátion B é condicional.
VERSÃO CORRIGIDA. A primeira tentativa afirmava "dois eixos de controle
ortogonais -- o haleto move a valência, o cátion B move o gap". **Os dados
contradizem isso** e a própria figura mostrava: o painel do desacoplam... |
3beb468ac783721595884a5b9d19544679d3c0ce87008834432a12bd3a7351e4 | Python | 9,793 | 216 | from torch import nn
import torch
import torch.nn.functional as F
class ConvolutionalVAE(nn.Module):
def __init__(self, latent_dim=20, n_cls=10, img_size=28, n_convs=None, in_ch=[1,32,64,128], conditional=False,
kernel_size=3, stride=2, padding=1, h_dim=2048, relu=False, req_flatten_size=None, la... |
2b686a1bedf6180f3959f837e7cfc9ad2a13e1d44b23055f3d50f67a08dd17e3 | Python | 9,797 | 253 | from dataclasses import dataclass
from typing import TYPE_CHECKING, Any, Callable, Dict, List, Optional, Tuple, Union
import inspect
import math
from loguru import logger
import os
import torch
import torch.nn as nn
from torch.nn import functional as F
from transformers.generation.utils import SampleDecoderOnlyOutput
... |
913175846469318eaae98cabaff9a4a79115061810cf8f8924e209296e321359 | Python | 9,798 | 244 | # Copyright 2019 The TensorFlow 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 applica... |
1999cfb823d9067454c2112c4bd2dcee281490ccd2b75be76eeafd79d72cb79c | Python | 9,799 | 341 | """
Wrappers for VTK algorithms and mappers.
"""
# Author: Oualid Benkarim <oualid.benkarim@mcgill.ca>
# License: BSD 3 clause
from vtk.util.vtkConstants import VTK_DOUBLE
from .base import BSVTKObjectWrapper, wrap_vtk
from .property import BSTextProperty
from .lookup_table import (BSLookupTable, BSLookupTableWithE... |
429fd45b7c5553f8f6b9ed0b4fc520ccb23efdbe949bd0a6526aece4338d17d8 | Python | 9,805 | 290 | #!/usr/bin/env python2
"""Tool for extending via equivalences a set of segments."""
import argparse
import copy
import os
import webbrowser
import neuroglancer
from neuroglancer.json_utils import decode_json, encode_json
neuroglancer.set_static_content_source(url="http://localhost:8080")
def get_segmentation_layer... |
623988e6122a758c2dca8524803523578da11b3be4da6506e2e9c35f078df465 | Python | 9,810 | 181 | """End-to-end mango DMC benchmark (the large, nonlinear NIR case; complements linear tahini).
Leakage-free interseason external validation: train = Seasons 1-3 (Set Cal+Tuning), test = Season 4
(Set 'Val Ext', zero Pop overlap). SG1 preprocessing; equal light tuning (inner GroupKFold by Pop);
single continuous target (... |
983af1991ee2e18fc0fa5a24f5210209af7a1af70d965243a68b320b31557eea | Python | 9,813 | 212 | """Given user GO ids and parent terms, group user GO ids under one parent term.
/ Given a group of GO ids with one or more higher-level grouping terms, group
each user GO id under the most descriptive parent GO term.
Each GO id may have more than one parent. One of the parent(s) is chosen
to best represen... |
23ca3265df954ba80a4ef87d5c757d27893c0bc3cd568169c85cf6633a92c743 | Python | 9,816 | 226 | from os.path import join, dirname, realpath
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
from matplotlib import gridspec
from mpl_toolkits.axes_grid1 import make_axes_locatable
from analysis.data_extraction_utils import get_pathway_names
from setup import saving_dir
d... |
6070b61750ac7608093fc4500d968a5b688a587ef6cdd263d33caa7bb728dcd7 | Python | 9,817 | 164 | """
Copyright 2020 Binxu Wang
Use GAN as prior to do feature visualization.
This method is inspired by the work
Nguyen, A., Dosovitskiy, A., Yosinski, J., Brox, T., & Clune, J.
Synthesizing the preferred inputs for neurons in neural networks via deep generator networks.(2016) NIPS
The GAN model is imported fro... |
9538f7b83c5476671e06a10a5951d86ae7aeb347bbc468f45616fe35b9a0ec02 | Python | 9,821 | 214 | import os
'''
By properly implementing file locking mechanisms like using fcntl for Unix-like systems ( and msvcrt for Windows systems), one can ensure that the Optuna optimization process runs smoothly without encountering race conditions or file locking issues, even when using multiple processes (n_jobs > 1).
'''
#im... |
96ffe59b3b1bc2cdbe055c6426ef5d8e8fabb32bfabde57d7eca4d4898d5a8d9 | Python | 9,823 | 304 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Matches cells and regions"""
from typing import Dict, List, Literal, Optional, Tuple, Union
import numpy as np
# import matplotlib.pyplot as plt
from scipy import ndimage as ndi
from skimage.segmentation import watershed # , find_boundaries
from sklearn.linear_model... |
50eaf4f7b8e8964dc3b099ffa7d3f3cd7fe42c826f5e53e0b6b2c76d82a09185 | Python | 9,826 | 293 | """
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 torch_scatter import scatter
from ..initializers import he_orthogonal_init
from .base_layers import Dense, ResidualLayer
f... |
0c9227a95fe1f40c273800ba04a58f8aabd455c91c51dc1d7254f31c69a5556a | Python | 9,828 | 246 | # Copyright 2019 The TensorFlow 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 applica... |
e175d94750c9484c560be82123ade138c5da7041cab2863203f32b4b05459118 | Python | 9,830 | 214 | import os
'''
By properly implementing file locking mechanisms like using fcntl for Unix-like systems ( and msvcrt for Windows systems), one can ensure that the Optuna optimization process runs smoothly without encountering race conditions or file locking issues, even when using multiple processes (n_jobs > 1).
'''
#im... |
618d49a01c84409568b1fe9da4710428547616430d89b535678b9ecf85d58721 | Python | 9,831 | 214 | import os
'''
By properly implementing file locking mechanisms like using fcntl for Unix-like systems ( and msvcrt for Windows systems), one can ensure that the Optuna optimization process runs smoothly without encountering race conditions or file locking issues, even when using multiple processes (n_jobs > 1).
'''
#im... |
f54da7149aac56facd8779cd6ec8d8a767fa9b57394b5ef19942afc33f255be0 | Python | 9,832 | 214 | import os
'''
By properly implementing file locking mechanisms like using fcntl for Unix-like systems ( and msvcrt for Windows systems), one can ensure that the Optuna optimization process runs smoothly without encountering race conditions or file locking issues, even when using multiple processes (n_jobs > 1).
'''
#im... |
085757e3833b675a5c5f08868f2a6d7bb0b67364a7a38bd7f3eafe7270911658 | Python | 9,835 | 321 | import torch
import torch.nn.functional as F
from einops import einsum, rearrange, repeat
from mamba_ssm.ops.triton.layernorm_gated import (
_layer_norm_fwd,
_layer_norm_bwd,
)
from mamba_ssm.ops.triton.ssd_combined import (
_mamba_chunk_scan_combined_bwd,
_mamba_chunk_scan_combined_fwd,
)
def flip(in... |
a4ba1814ff5c8e298214c4262d25739c6d135cefa99a4e3d4512de57039e94d4 | Python | 9,839 | 215 | import os
'''
By properly implementing file locking mechanisms like using fcntl for Unix-like systems ( and msvcrt for Windows systems), one can ensure that the Optuna optimization process runs smoothly without encountering race conditions or file locking issues, even when using multiple processes (n_jobs > 1).
'''
#im... |
c4399c0891f001187667ee888df4dbc021249c4fa7b20ec8c6f103e4b44d8078 | Python | 9,839 | 253 | import functools
import os
import tempfile
import unittest
import numpy as np
import torch
import medaka.datastore
import medaka.training
import medaka.torch_ext
import medaka.models
from medaka.test.test_sample import get_test_samples
class TestNamespace:
class ModelAndData:
CheckpointType = medaka.to... |
e65e2aab0f9e5cdab71acefb76fc1b8f7359f65c1c1fc37f606397133514a4d5 | Python | 9,839 | 250 | """
DWP Pipeline — Distance-Weighted Pooling
Phase 1: MAP-identical CV to select best feature/DA/classifier
Phase 2: Compute source-to-target distances in best feature space
Phase 3: All-source continuous inverse-distance weighting
Phase 4: Deterministic weighted merge (replication)
Phase 5: DA once on merge... |
4881c9d870fe145359d2614c98cb526de43177b8c42a611317aded1a2395da3e | Python | 9,847 | 345 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# SHAP documentation build configuration file, created by
# sphinx-quickstart on Tue May 22 10:44:55 2018.
#
# This file is execfile()d with the current directory set to its
# containing dir.
#
# Note that not all possible configuration values are present in this
# autog... |
4fe76cfc6d3929aa78fed3ca86287cae566cc382ba0dee550177f717110df62b | Python | 9,850 | 237 | """module to plot sensornode measurements using pyqtgraph
"""
import pyqtgraph as pg
from Sensors import constants
import numpy as np
from datetime import datetime
from queue import Queue
class plotter:
"""Class that contains methods to setup a pyqt plot grid and plot measurement curves
Attributes
... |
2a8cde23116272a965507eb47c660bfa968e76f3ba4682f8fd6bfc0bf4e70446 | Python | 9,851 | 163 | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'optimization_options_dialog.ui'
#
# Created by: PyQt5 UI code generator 5.10.1
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore, QtGui, QtWidgets
class Ui_OptimizationOptionsDialog(object):
def setupUi(... |
f4505b52d411fe3317066ec091212d56775e9b27a27e161bb4d60f5924fa6118 | Python | 9,851 | 187 | import gzip
import sys
import argparse
SHOW_WARNINGS = False
def parseArgs(args):
parser = argparse.ArgumentParser(
description="Create annotation file from UCSC knownGene file.")
parser.add_argument("known_gene_file", help="UCSC knownGene file")
parser.add_argument("out_file", help="Output file n... |
70ae5e50b04e631836b729d7cf1c60d7fcd459409af6e2211ca5caaaa2f30933 | Python | 9,857 | 151 | # coding=utf-8
# Copyright 2019-present CNRS, Facebook Inc. and the HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#... |
c98cc741be5f8fe753ab269aff5eb7656742b1881c6b2c69c9103fb4d9462b16 | Python | 9,858 | 152 | # coding=utf-8
# Copyright 2019-present CNRS, Facebook Inc. and the HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#... |
1da4d7c30f6ae09bad9de39922fb88ba57d4443621271acf9b86cbd3f2df7459 | Python | 9,859 | 189 | #!/usr/bin/env python3
r"""Rebuild Supplementary Table S2 for the current 94-gene inverse-concordant pool.
WHY THIS EXISTS. S2 was last written for the 82-gene pool, before the expression-matrix repair
raised the pool to 94, and its tier column still placed CD79B in Tier-1. Two scripts had since
bolted columns onto th... |
a41121ce55f6a3af4be42bf414197f19f251f9e2bc9050a0079afce148d3ab06 | Python | 9,860 | 316 | from pathlib import Path
from types import SimpleNamespace
import numpy as np
import pytest
import torch
import yaml
from gpn.data import Tokenizer as StarTokenizer
from gpn.ss.model import GPNConfig, GPNForMaskedLM
from gpn.ss.train import (
DataTrainingArguments as GPNDataTrainingArguments,
)
from gpn.ss.train ... |
0a15731dbc9b72b40bfdca935d9c58d32a72e6ddb7c0850f14bf27df61d61cfa | Python | 9,861 | 301 | from __future__ import annotations
import abc
from abc import abstractmethod
from typing import TYPE_CHECKING
import torch
from torch.distributions import (
Categorical,
Independent,
MixtureSameFamily,
Normal,
kl_divergence,
)
from scvi.module._constants import MODULE_KEYS
if TYPE_CHECKING:
... |
804be03a36d6da1a391f96c6a532abc1b059708c56346715176f921ba0b70290 | Python | 9,864 | 244 | #!/usr/bin/env python
# coding: utf-8
"""
Temporopolar blurring in HS: ipsilateral / contralateral surface t-maps + raincloud plot.
Produces three figures:
1. ipsi_supp.png - ipsilateral HS vs controls, vertex-wise t-map
2. supp_contra.png - contralateral HS vs controls, v... |
150ed2c1585e15fb54cf6ab6e374d5667220d8b3754c66589540cbfb952c3dfd | Python | 9,865 | 294 | """No module invents a field on the base model's `transformers` config.
A `PretrainedConfig` is a plain object: assigning an attribute it does not
define stores it and nothing ever reads it back, so the failure is silent by
construction and this is a source-level check. The scan follows a local alias,
`setattr`, `.upd... |
86f9012b845dea6fbfff6f6ed37fdff06f224aa4006f6722c8f901517211bc20 | Python | 9,865 | 260 | import numpy as np
from pathlib import Path
import pickle
import argparse
from datetime import datetime
from deploy.iblsdsc import OneSdsc as ONE
from brainbox.io.one import SpikeSortingLoader
from iblatlas.regions import BrainRegions
from iblatlas.atlas import AllenAtlas
import gc
import pdb
from celltype_ibl.params.c... |
08ddc2001c53919c4a8492de6d94310e134dabfddd1eb490fd7ffa1f720c8aef | Python | 9,887 | 250 | from __future__ import annotations
import logging
import os
from pathlib import Path
import dask.bag as db
import numpy as np
from dask.diagnostics import ProgressBar
from ... import config
from ...common import constants, files
from ...common.annotation import map_annotated_to_annot
from ...common.converters import... |
51c6bbb0adb7d36b7791fd9191d25e2fa00b92dbe6b6011897b4bc151db31b89 | Python | 9,890 | 230 | #!/usr/bin/env python
from itertools import combinations
import networkx as nx
from pgmpy.base import DAG
from pgmpy.estimators import StructureEstimator
from pgmpy.structure_score import get_scoring_method
from pgmpy.utils._warnings import _warn_external
from pgmpy.utils.mathext import powerset
class ExhaustiveSe... |
280bce795134329112657ded6eef9aa765d54ee0ebbc123161deb1e1c15f7d21 | Python | 9,892 | 222 | from .utils import IntermediateLayerGetter
from ._deeplab import DeepLabHead, DeepLabHeadV3Plus, DeepLabV3
from .backbone import (
resnet,
mobilenetv2,
hrnetv2,
xception
)
def _segm_hrnet(name, backbone_name, num_classes, pretrained_backbone):
backbone = hrnetv2.__dict__[backbone_name](pretrained_... |
c915e537868f62c02dccf843dba2a323f256bfc7266a17158caffd033eb82aad | Python | 9,893 | 291 | # Copyright (C) 2025 ETH Zurich, Moritz Thürlemann, and other AMP contributors
from torch import Tensor
from typing import Final
from utilities.Scatter import scatter_sum as scatter
import torch
import numpy as np
from datastructures.Graphs import Graph
from utilities.Utilities import ff_module, scalar_product
cla... |
bb3601dda77979052d836101e95f227fb1a5c831dd4420ced0e98e6c6da37559 | Python | 9,903 | 255 | # This is the class for Physics informed neural network for phase field modeling in 2D
#文件2 PINN2D_PF
import tensorflow as tf
import numpy as np
import time
class CalculateUPhi:
# Initialize the class
def __init__(self, model, NN_param):
# Elasticity parameters
self.E = model['E']
... |
becfbd030ee266b0a53aba6f3cea815f0fa91207e3560eb90293c25267f92d9c | Python | 9,912 | 247 | """Facade for telemetry workbook export orchestration."""
from __future__ import annotations
from pathlib import Path
import pandas as pd
from src.features.telemetry_alignment.exporters.cluster_sheet_exporter import (
populate_cluster_sheet as export_cluster_sheet,
)
from src.features.telemetry_alignment.export... |
59e1d94f953ae38d9ec7292b4be5619933508306db1dbe3ddda468d268207f3c | Python | 9,913 | 256 | # coding=utf-8
# Copyright 2018 Google AI, Google Brain and the HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# U... |
999be6e2bde1d6eef4b989d8e525c5050a23e24e33c625800d7e8c73fd712d3a | Python | 9,914 | 257 | # coding=utf-8
# Copyright 2018 Google AI, Google Brain and the HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# U... |
e6f3a24622b3b8b066677b14c60cdd904b5b0cedcfcb3cf8600d23ec2a12aeb2 | Python | 9,922 | 264 | # Source code:
# https://github.com/zbmed-semtec/doc2vec-doc-relevance-training/blob/main/code/train_model/utilities.py
# This file includes the modifications to the source codes according to this project!
import tqdm
import gensim
import logging
import numpy as np
import pandas as pd
from scipy.spatial.distance impo... |
2d517d16bd4b5c5934af52b25f4f468524ae2437cbfe0ad4a11557254ff88f29 | Python | 9,935 | 332 | """
Utility constants and helper functions for the EEG Streamlit dashboard.
"""
import numpy as np
import pandas as pd
import plotly.graph_objects as go
# ---------------------------------------------------------------------------
# Pipeline name mappings
# ------------------------------------------------------------... |
7614e0d9ab21e0e228a367a614f381e4d9eb8a31d748897d04cc0481f72b11e1 | Python | 9,936 | 218 | import os
import msvcrt # For Windows systems
'''
By properly implementing file locking mechanisms like using msvcrt for Windows systems,
one can ensure that the Optuna optimization process runs smoothly without encountering
race conditions or file locking issues, even when using multiple processes (n_jobs > 1... |
aa72f0ccb67fb79daad6b7afec39ea638db0e14131a5033a36513a1ea4313b62 | Python | 9,937 | 213 | # This script takes gff3 made by TransDecoder and shapes it into a format
# that can be used to construct Annotation by GenomeKit
from src.utils import read_gff, read_gtf
import polars as pl
from src.single_cell import SingleCell
# Read TD_gff and clean
TD_gff_path = "full_nt.fasta.transdecoder.genome_remove_spaces.... |
a5334f2dbb44351b7720e1ca4229453783d27d583eab4e05f95138b35ffaebd7 | Python | 9,938 | 319 | import numpy as np
import torch
from scipy.sparse import csr_matrix
from scipy.sparse import diags
from scipy.sparse.linalg import eigsh
from sklearn.cluster import KMeans
from sklearn.neighbors import NearestNeighbors
from typing import Tuple
from typing import List
def rbf_neighbor_graph(
X: np.ndarray,
a... |
e54aae4fd5a985a28dac5f8a988b54fe7b85f1f29598be873dd9e755ddc0bade | Python | 9,939 | 457 | import numpy as np
#Functions that are shared across the scripts used in the spatial-jitter simulations
def BSph(r, rq, Q):
"""
Calculate magnetic field due to a current dipole in a spherical conductor.
Sarvas' formula is used'
Parameters
----------
r: array (1, 3)
the posit... |
b5a62362c10d391c7a0435b166ba921f8b7fd17c2e25e38152979b144a999d63 | Python | 9,946 | 271 | """Function that trains models in the Parametric UMAP family."""
from __future__ import annotations
import datetime
import logging
import pathlib
import lightning
import pandas as pd
import torch.utils.data
from .. import datapipes, models
from ..common import validators
from ..common.paths import generate_results_... |
b911cf2d04792eb0ad2c267493d669281b4fcf6d8d6577fc7ad8a3f868d234cf | Python | 9,952 | 264 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sun Jan 25 21:27:06 2026
@author: vbp
Peak-aligned GRAB-DA kinetics for uncued reward, for Figure S2E/F.
Fig S2E - peak-normalized GRAB-DA traces aligned to each session's own
response peak, per region
Fig S2F - full width at half ma... |
349e02a2d657ad1598990c0048f9a2488b5a448833857c479622922b9d5f1f4c | Python | 9,953 | 295 | from collections.abc import Mapping, Sequence
__author__ = 'Robbert Harms'
__date__ = "2016-09-03"
__maintainer__ = "Robbert Harms"
__email__ = "robbert@xkls.nl"
class ConversionSpecification:
def __init__(self):
"""Specifies how the content of an object is to be converted from and to a dictionary."""
... |
f21af4073a2b35d40436d4b5a7ad28d7eadb3a3040a817a9c8a7173097993c54 | Python | 9,953 | 280 | import json
import os
from pathlib import Path
from typing import Optional, Union
import numpy as np
import scanpy as sc
import torch
from anndata import AnnData
from torch.utils.data import DataLoader, SequentialSampler
from tqdm import tqdm
from .. import logger
from ..data_collator import DataCollator
from ..model... |
7c54f8a337ebb0a5a3765f77179b7d86c71ec89d9153272320cd9384b1c66916 | Python | 9,959 | 278 | # 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... |
c5ca65f6f116e02573d2302e03177a69838a4895ff6053bd6025c4638121898d | Python | 9,964 | 296 | # 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 os
from dataclasses import dataclass, field
from typing import Any, Optional
import numpy as np
from omegaconf import I... |
406deb5242862d1b2e416aa492cd5b6fdd7898c3b25731795887e8d54e090e4b | Python | 9,965 | 262 | from __future__ import annotations
import logging
from collections.abc import Callable
from PySide6.QtWidgets import (
QDialog,
QFrame,
QGridLayout,
QHBoxLayout,
QLabel,
QPlainTextEdit,
QPushButton,
QVBoxLayout,
QWidget,
)
from src.gui.framework.qt_log_handler import QtTextHandler... |
48de8448031a55cb327e102e26e857da43da5e8c4852b66625ec2ff57d0e3b86 | Python | 9,978 | 321 | import json
from typing import Literal
import numpy as np
import pydicom
import nibabel as nib
import torch
from pathlib import Path
from monai.transforms import Resize, ResizeWithPadOrCrop
from models import FE_Additional
def load_nifti_volume(path: str) -> np.ndarray:
"""
Load a NIfTI CT volume as a numpy ... |
8126c0f185d917c7257bb59b9a80ac62570555c26cec47d8aa7799586ba24853 | Python | 9,978 | 219 | import os
import fcntl # For Unix-like systems (including Ubuntu)
'''
By properly implementing file locking mechanisms like using fcntl for Unix-like systems,
one can ensure that the Optuna optimization process runs smoothly without encountering
race conditions or file locking issues, even when using multiple... |
5e7cfe21b26925c7034fc4c198241278de0ec2f7d7545a74c9f1f615a7bc85bc | Python | 9,979 | 226 | ## run ROI-based RSA
#
# written by S-C. Baek
# update: 16.12.2024
#
'''
The following code is to run representational similarity analysis (RSA) on 10 predefined ROIs or a subset of them.
Here, RSA basically measures the similarity between each or time-resolved neural RDMs at a given ROI and time point,
and two model ... |
ca6cde0e30cddb7952c201d21741aded9d8f21885b35b940acd7f1a59e435418 | Python | 9,981 | 286 | """Class forms of transformations
related to frame labels,
i.e., vectors where each element represents
a label for a frame, either a single sample in audio
or a single time bin from a spectrogram.
These classes call functions from
``vak.transforms.frame_labels.functional``.
Not all functions in that module
have a corr... |
dd79c955ff9c18e30fd7cb6e80768cd5c236db82cc4cb2065c105eaab981cbcb | Python | 9,982 | 325 | import torch
import torch.nn.functional as F
import numpy as np
import nibabel as nib
from torch.utils.data import Dataset
from collections import defaultdict
def load_mindboggle(path, normalization=True):
'''
Description:
Load mindboggle data -> crop -> scale -> return image and rois
... |
83fdd3b4bc40d98ff036194e09f7d4644ddee45aba8a52e39bfa00ab8491e845 | Python | 9,985 | 267 | # Source code:
# https://github.com/zbmed-semtec/doc2vec-doc-relevance-training/blob/main/code/train_model/utilities.py
# This file includes the modifications to the source codes according to this project!
import tqdm
import gensim
import logging
import numpy as np
import pandas as pd
from scipy.spatial.distance impo... |
0e209f5d3e1dbc347b52c0c2ec02cfe5f8c9f3a759e1777d3c72f6cda655c104 | Python | 9,994 | 221 | import os
import fcntl # For Unix-like systems (including Ubuntu)
'''
By properly implementing file locking mechanisms like using fcntl for Unix-like systems,
one can ensure that the Optuna optimization process runs smoothly without encountering
race conditions or file locking issues, even when using multiple ... |
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