sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
7ab46ca780c16cfb4bd10dc93a41a6f2a2256217fa03e9ebdb80b3786dfd6735 | Python | 10,296 | 224 | 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 > ... |
aca4555eb4d2ab1e81419068a9b97d68b53b02dce3a9a21eba7cc0c1b090b144 | Python | 10,301 | 268 | # coding=utf-8
# Copyright 2018 The Open AI 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/LICENSE-2.0
#
# ... |
c7d67098e600d901198067bf5752b990ff98e87fcd7c0b9685556b79fe0393e1 | Python | 10,307 | 288 | """
Copyright (c) Facebook, Inc. and its affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""
import numpy as np
import sympy as sym
from scipy import special as sp
from scipy.optimize import brentq
def Jn(r, n):
"""
numerica... |
da77173638952acd2d14d6d3bdd9bbd3f8d8bd1fe1922037d4636b104bd72784 | Python | 10,307 | 246 | """
This module runs sequence classification task.
Author: wangning(wangning.roci@gmail.com)
Date : 2022/12/7 7:41 PM
"""
import argparse
import os.path as osp
from functools import partial
import paddle
from paddlenlp.datasets import MapDataset
from paddlenlp.transformers import ErnieForSequenceClassification
from... |
0ee5a8cccea0b2b597cc166e14988ebb44a89b744e5c3f775afbd6589338dfcd | Python | 10,315 | 227 | """Plot a GoSubDag.
GO Terms in a plot contain text. The first two lines appear by default:
GO:0015618 L07 D13 p2 c2 d3
potassium-transporting ATPase activity
GO:0015618 => GO ID
First line:
LNN => The "level" of the go term.
The length of the shortest path(s) fr... |
b60da4d16300f4116c8e4027ae079f7b2fad2d0955a814d1323379b4f3a6bb2e | Python | 10,315 | 335 | # 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... |
10a22d4ee864243b6f19d7ad274bdafd04ba2615dbf54bd82fd55f0504c69b16 | Python | 10,316 | 219 | import numpy as np
from mdt.component_templates.base import ComponentBuilder, ComponentTemplate
from mdt.lib.components import has_component, get_component
from mdt.model_building.parameter_functions.numdiff_info import NumDiffInfo, SimpleNumDiffInfo
from mdt.model_building.parameters import ProtocolParameter, FreePara... |
610fa5a9dfae7405bc2e792543c5330891f096d6c8086f2cae9e2c99ab4ab456 | Python | 10,317 | 269 | """
Report Generation Pipeline for NeuroVFM
Loads a trained NeuroVFM model and provides a high-level interface for
generating radiology reports from medical imaging studies.
"""
import torch
import torch.nn as nn
from typing import Dict, List, Optional, Tuple, Union
from pathlib import Path
import logging
import json... |
dae6214b75fce9dfdd1f646d6b7871a306a6fab63668c83b664cee78f39cf178 | Python | 10,318 | 271 | # coding=utf-8
# Copyright 2018 The Open AI 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/LICENSE-2.0
#
# ... |
7647982f31cf74f12739e7971588810e7b7b4d96ce8c7a4a58466ea73f1b0da5 | Python | 10,321 | 277 | import argparse
import numpy as np
import os
import bigstream.io_utility as io_utility
from bigstream.align import alignment_pipeline
from bigstream.configure_bigstream import (configure_logging,
set_cpu_resources)
from bigstream.image_data import (ImageData, get_spatial_valu... |
ec90fc7176561c46a03d486179cf2655b49cda5a071ab8774bf8484d925f656c | Python | 10,323 | 264 | from __future__ import annotations
from typing import TYPE_CHECKING
from typing import Any
from typing import ClassVar
from cleo.helpers import argument
from cleo.helpers import option
from packaging.utils import canonicalize_name
from poetry.core.packages.dependency import Dependency
from poetry.core.packages.depend... |
2cd72de4bc401eabe18db7b064c15d8ab02131ef69f1494123916dd024558534 | Python | 10,324 | 281 | """Run some basic statistics on the VG + COCO overlap captions."""
# Imports
import os
from typing import List
import click
import datasets
import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
import spacy
from loguru import logger
from tqdm import tqdm
from compositionality_study.constants impo... |
b2018547ce5fb143e007ac30c211e91921a2b9a062d81715111ba80a47c13b33 | Python | 10,326 | 296 | # Simulations as a function of the source depth in the spherical conductor
import numpy as np
import matplotlib.pyplot as plt
from bfieldtools import sphtools as sph
import functions
font = { 'size' : 20}
plt.rc('font', **font)
#%% Plot parameters
legendfontsize = 15
linewidth = 2.5
#%% Define parameters
#... |
a39f10b2d63256edc7cc623229c9afc76cee7ede14790d1f6bd98ca4cf26fd71 | Python | 10,327 | 247 | #
# 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 .iadc import IADC
from .iadc import get_digit
from simulator.backend import ComputeB... |
076bebdfb03a81a56cc2212ed56c070f141d510e73dcb0bd6056633dcb938090 | Python | 10,329 | 257 | import numpy as np
import timeit as ti
from scipy import stats
from typing import Union
import os
def AMI_Thomas(x : np.ndarray, L : Union[int,np.ndarray,list]) -> Union[np.ndarray,float]:
"""
Usage: (tau,ami)=AMI_Thomas(x,L)
inputs: x - time series, vertically orientedtrc files selected by user
... |
1f817b0e7a9fdd6cfd9c4a54062a01cff46b0b8600ad687300e3bbe4f47a3dee | Python | 10,335 | 272 | #!/usr/bin/env python3
# MIT License
#
# Copyright 2022 Broad Institute
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use... |
311b6a9a25c6fd83903538b6e53c504045c9aa86b5fb0b8cc2a1eb83344f450f | Python | 10,335 | 290 | import math
from functools import partial
from typing import Callable, NamedTuple, Protocol
import jax
import jax.numpy as jnp
import jax.numpy.linalg as jnp_linalg
from jax.flatten_util import ravel_pytree
from jax.tree_util import tree_map
from .device_utils import DEVICE_AXIS, split_rng_key_to_devices
from .types ... |
4cadce9843f54427c3a5de1cc1ea55ff4233868af45441b2d1376e91a364e539 | Python | 10,346 | 262 | import sys, pysam, time, os, copy, argparse, subprocess, random, re, datetime
import numpy as np
from subprocess import Popen, PIPE, STDOUT
from argparse import ArgumentParser, SUPPRESS
from sys import exit, stderr
def subprocess_popen(args, stdin=None, stdout=PIPE, stderr=stderr, bufsize=8388608):
pr... |
5074175e91abd65d309e030025abc123395158b6f8580cb4b25f814753ccfbfe | Python | 10,348 | 257 | import torch
from torch import nn
import torch.nn.functional as F
from .modules import BaseClassifier, BaseClassifier_reg
# ---------------------------------------------------------------------------
# CNN-Transformer Hybrid baselines
# ---------------------------------------------------------------------------
cla... |
a1ffbf5de1d1e7a8016f4747509065925163e44212b9c9366e59c315b75178be | Python | 10,354 | 246 | """
run_spont_analysis.py
=====================
Analysis pipeline for the spontaneous Brunel sweep (bitrep_spont).
For every spikes_spont_s{seed}.npz file found under RESPATH, computes:
- Tier-1 regime metrics: mean_rate, chi, tau_net, cv_isi_mean, cv_isi_std,
f_peak, sigma
- Tier-2 dim... |
cf0340642e445a600fd673784fb1f80b9add98e842c81214d076576a33634f2e | Python | 10,360 | 244 | # -*- coding: utf-8 -*-
# Copyright (C) 2017-2023 Phillip Alday <me@phillipalday.com>
# License: BSD (3-clause)
"""File I/O utilities for EEG data."""
from __future__ import division, print_function
import codecs
import os
import mne
import numpy as np
from .. import __version__
# TODO: include boundaries in MNE ... |
edd5bf07f88065fd4abf97b4f0d08477a5b781029aaebbe34cb95e74f2c00479 | Python | 10,362 | 283 | import os
os.environ["CUDA_VISIBLE_DEVICES"] = "0"
from typing import Optional
from dataclasses import dataclass, field
from transformers import HfArgumentParser, TrainingArguments, BertTokenizerFast, set_seed, Trainer
import logging
from src.benchmark.models import model_mapping, load_adam_optimizer_and_scheduler
fr... |
e12281ca49da8aff4e08681fcdce14cb8fe645aefe21c4b0c9ee28ebf76be441 | Python | 10,363 | 300 | """Render evaluation figures from saved payload (six separate PNGs: eval_a–f)."""
from __future__ import annotations
import os
import matplotlib
import numpy as np
from matplotlib.colors import to_rgb
from tasks.dynamic_segmentation.simulation_eval_bars import SIMULATION_BAR_LEGEND_LINES
from tasks.dynam... |
2fbbf425370ee18f9d17c17c7dc4aedde3e8e2d6bbc90162e50679c2ad62466a | Python | 10,368 | 228 | import os
import numpy as np
import cv2
label_path = r'D:\FangX24\data\DOTA/labelTxt/'
store_path = r'D:\FangX24\code\LO-Det-main\mnt\Datasets\DIOR/Annotations/'
if not os.path.exists(store_path):
os.makedirs(store_path)
classes = ['plane', 'baseball-diamond', 'bridge', 'ground-track-field', 'small-vehicle', 'la... |
a664e2c14316010954e1fc3eac2c6c8b2836c62cf706185f6d3b52a00f826c12 | Python | 10,368 | 323 | import sys
import logging
import os
import tensorflow as tf
import tensorflow_addons as tfa
from tensorflow.keras.layers import Conv2D, MaxPooling2D, Layer, Flatten, Dense, Bidirectional, Dropout, LSTM, \
LayerNormalization, MultiHeadAttention, Concatenate
from tensorflow.keras.models import Model
from tens... |
518c76e0a35396c7499a0054b7ec296a36f82f2ca17222b97a6897bd90f776a5 | Python | 10,369 | 269 | #
# 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 ..idevice import EmptyDevice
import numpy as np
from scipy.interpolate import interp... |
7b689c7cbe4923c8c933348ffe89c3ee7e1dce134728803d3a829f1b85678160 | Python | 10,370 | 124 | import torch
import torch_geometric.nn as gnn
from Bio.PDB import PDBParser
import numpy as np
import pandas as pd
from torch_geometric.utils import remove_isolated_nodes
from matplotlib import pyplot as plt
import warnings
warnings.filterwarnings('ignore')
cn = {'P':0,'M':1,'A':2,'B':3}
cn_ = {0:'P',1:'M',2:'A',3... |
b07e5b92c75c98426ff011143abbd54dea79ea7dbddf5e15221e24d986f8486d | Python | 10,372 | 275 | from __future__ import annotations
import numpy as np
import pandas as pd
STRUCTURE_AXIS_WEIGHTS = {
"phi_local": 3.0,
"phi_uncertainty": 1.0,
"phi_stability": 0.0,
"phi_reference": 0.0,
}
REFERENCE_AXIS_WEIGHTS = {
"phi_local": 0.0,
"phi_uncertainty": 2.0,
"phi_stability": 1.0,
"phi_... |
0cd10d05960e94e700070da39d00522d1bb8f85af536ba48cd3447e8578a8605 | Python | 10,373 | 241 | """Publication-asset generator. Reads results_phase1/phase1_artifacts.npz + phase1_meta.json
(+ the CSV tables) and writes paper-ready figures and CSV/LaTeX tables to results_phase1/paper/.
Decoupled from training -> rerun anytime to restyle. Run: python -m kanfood.report"""
import sys
import json
from pathlib import P... |
3da5310f5438aa0225a0e2d88a0569328cca2e4e1084051c91d14d303ec3cd04 | Python | 10,376 | 231 | import io
import logging
import os
import re
import tempfile
import unittest
from pathlib import Path
from unittest.mock import patch
from GMXMMPBSA.progress import MAX_RICH_WIDTH, FrameCounter, _StallNotifier, monitor_progress, resolve_progress_style
class _Stream(io.StringIO):
def __init__(self, is_terminal):
... |
05164a8d25cc014462d77ef995b6b1cf046d01f57e00e7cf49e6a861b2ae6a22 | Python | 10,377 | 249 | # _*_ coding: UTF-8 _*_
# Version information START --------------------------------------------------
VERSION_INFO = \
"""
Author: ZHANG YUBO
Version-01:
2020-01 Converting VCF format to multiple sequence alignment
"""
# Version information END ------------------------------------------------... |
53ed02567bbf4da96a6a094ec86e0ae959e0e274fe5a3cc705483e949f92614d | Python | 10,377 | 261 | #!/usr/bin/env python3
import argparse
import shutil
import os
import sys
import numpy as np
import pandas as pd
from tqdm import tqdm
from sklearn.metrics import roc_auc_score, f1_score
import torch
from torch import Tensor
import torch.nn as nn
import torch.nn.functional as F
from torch.utils.data import DataLoader,... |
586da7735d5b706788429024a2d3028e378b0946a41ff171a70fdbcf7e861595 | Python | 10,378 | 315 | import logging
import os
import sqlite3
import re
import pandas
from . import Exceptions
from . import NamingConventions
class WDBQF(object):
"Weight DB weight Query Format"
RSID=0
GENE=1
WEIGHT=2
REF_ALLELE=3
EFF_ALLELE=4
K_RSID="rsid"
K_GENE="gene"
K_WEIGHT="weight"
K_EFFEC... |
81cb9b2221c16b21e1ba6737bcf6fbb5d398784101584a972d75d2a6d5d413e8 | Python | 10,378 | 343 | from __future__ import annotations
import dataclasses
import hashlib
import json
import logging
import shutil
import threading
import time
from collections import defaultdict
from pathlib import Path
from typing import TYPE_CHECKING
from typing import Any
from typing import Generic
from typing import TypeVar
from typ... |
a6ff789b736a6825acb96b6e3cf2908b4ecf08ae1793ef4f9d99db713168d754 | Python | 10,379 | 232 | import numpy as np
import pandas as pd
import matplotlib
from matplotlib import pyplot as plt
import scipy
import pynumdiff
import cvxpy
class compute:
def angular_acceleration(fly_df: pd.DataFrame, name_of_heading_field:str, name_of_time_field: str):
params = [2, 10, 10]
dt = np.median(... |
4cfb3ea1e8ad24c87b113c5da27fbfb2ed33a3ca7e0ee7d1ec182ee39662fd19 | Python | 10,382 | 232 | import numpy as np
import scipy.io as si
import os
import h5py
from sklearn.model_selection import KFold
from imblearn.over_sampling import RandomOverSampler
from imblearn.under_sampling import RandomUnderSampler
from sklearn.svm import SVC
import sklearn.pipeline as skp
from sklearn.preprocessing import StandardScale... |
cae3ca9c87147643bbf0eef321378b9b2ea79c9a791be10e7b61727a01228c8f | Python | 10,385 | 300 |
import os
import matplotlib.pyplot as plt
import skimage.io as skio
import torch
import torch.fft
import torch.nn.functional as F
import numpy as np
import scipy as sp
from math import factorial
import numbers
from scipy import ndimage
import scipy.fft as fft
defaultTFDataType="float32"
defaultTFCpxData... |
6b6b76f9c9ac3452143985a5b3b6e2b4190deebfe18286896041ea083d765f33 | Python | 10,388 | 307 | # Authors: Christian O'Reilly <christian.oreilly@sc.edu>
# Scott Huberty <seh33@uw.edu>
# License: MIT
"""class to wrap mne.annotations in dash shapes/annotations."""
import mne
import numpy as np
import pandas as pd
from uuid import uuid1
class EEGAnnotation:
"""Store mne.annotation info as plotly sha... |
92369153f772afb086d02fca18db5598c17fd4f7655d7a1a7d35d432dbee8eaa | Python | 10,396 | 252 | from typing import Optional
import numpy as np
import torch
import torch.nn.functional as F
from .tensor import coerce_numpy
from sklearn.metrics import auc
@coerce_numpy
def rna_compute_precisions(
validation_step_outputs: torch.Tensor,
minsep: int = 0,
step: int = 0.001,
):
T = np.arange(0, 1 + step,... |
184c933fae56fd12c9d076487b88ea2f6bfe7750170d65c500eb34d3227cd187 | Python | 10,398 | 272 | import os
from scripts import pdb_utils
import pandas as pd
from Bio import pairwise2
from Bio.pairwise2 import format_alignment
from Bio import Align
from Bio.Align import substitution_matrices
from datetime import datetime
aligner = Align.PairwiseAligner()
aligner.substitution_matrix = substitution_matrices.load("B... |
3aa3837b60d87e93065b4e0e6326ee89c3766ae756f445f63d71026e3341d957 | Python | 10,405 | 273 | """CPU-only mask cleanup and frame interpolation shared by all builds."""
from __future__ import annotations
from collections.abc import Mapping, Sequence
import numpy as np
from scipy import ndimage
CLEANUP_OPERATIONS = {
"fill-holes": "Fill Holes",
"remove-islands": "Remove Small Islands",
"largest":... |
645a5bcb054a4b4620980951031cc5d89f02abd5e05838cc3abf4d55d44a023a | Python | 10,408 | 270 | from __future__ import division
import torch
import numpy as np
import cv2
def nms(bbox, thresh, score=None, limit=None):
"""Suppress bounding boxes according to their IoUs and confidence scores.
Args:
bbox (array): Bounding boxes to be transformed. The shape is
:math:`(R, 4)`. :math:`R` is... |
03fc8f7c6f711d2102a8b14127c12a485ab071d9a182a2ac6df4c416d3a546ea | Python | 10,411 | 246 | import logging
import math
from typing import Optional
import anndata
import matplotlib.pyplot as plt
import numpy as np
import squidpy as sq
from scipy.spatial.distance import cdist
from sklearn.metrics.cluster import adjusted_rand_score
from sklearn.neighbors import NearestCentroid
from aestetik.AESTETIK import AES... |
4472c9539f0ce86c599c64b20bafd9472e11244e0351fb2f61fa8b4110783a5d | Python | 10,413 | 244 | """Run the Phase 1 reference-equivalence test with a real SAM2 predictor."""
from __future__ import annotations
import argparse
from pathlib import Path
import shutil
import sys
import tempfile
import zipfile
import numpy as np
from PIL import Image, ImageDraw
def parse_args():
parser = argparse.ArgumentParser... |
f6127b91f1ee03e01e6c58a573569a694ca06e175805ebb1097c594fd88d0e59 | Python | 10,419 | 283 | import copy
import threading
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.colors import to_rgb
from matplotlib.widgets import Button, Slider
from skimage.segmentation import find_boundaries
from .motion_marker_utils import compute_stats, stats2mms
mpl.rcParams['axes.spi... |
5057cf87e7092d8657f150ab0da6c8f4968a8220642ef3add053cb40ef424579 | Python | 10,420 | 201 | """Page 6: DA Analysis."""
import streamlit as st
import plotly.express as px
import plotly.graph_objects as go
import pandas as pd
import numpy as np
from utils import PIPE_ORDER, PIPE_COLORS, style_figure
def render(store, dataset):
st.header("Adaptation Effects")
st.markdown(
"Does domain adaptati... |
816c1dfeaad125db4dd2a5ed8aea1fb9b69d8072c8debd1b28ed1398f208a64b | Python | 10,421 | 298 | # 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 copy
import logging
from fairseq.models import (
FairseqEncoder,
FairseqEncoderModel,
FairseqLanguageModel,
register_m... |
285079398212c0be2d3ffd7ee57d799a023baf336134311980f7c1e417d1544e | Python | 10,426 | 283 | from __future__ import annotations
import logging
import traceback
import pandas as pd
from scvi import settings
from scvi.dataloaders import DataSplitter
from scvi.model._utils import get_max_epochs_heuristic
from scvi.train import MlxTrainingPlan, TrainRunner
from scvi.utils import is_package_installed, mlflow_log... |
5117103fee2e78bcd515a618dcb1721b4434069f9cea70ad47af979e073cbc19 | Python | 10,432 | 293 | import tensorflow as tf
from tensorflow import keras
from tensorflow.keras.models import Model
from tensorflow.keras.layers import Conv2D, MaxPool2D, Reshape, RepeatVector
from tensorflow.keras.layers import Dense, Input, Flatten, Dropout, concatenate
from tensorflow.keras.layers import BatchNormalization, Lambda, Mult... |
da41a3b1f498b1a0485e0b4781a88fab425009dc10a0eeb763bb0f0397f8c8cb | Python | 10,434 | 338 | """
This module contains all loss functions used by the Garfield module.
"""
from typing import List, Literal, Optional
import math
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
def compute_omics_recon_mse_loss(recon_x, x):
"""Computes ... |
7ad69022d34a00b4d393842cf2afb7bc38f61263ca74fba841e5a40768bc02d0 | Python | 10,435 | 206 | #!/usr/bin/env python3
"""figure2_rna_volcanoes.py — per-stratum RNA volcanoes with INV-only Tier-1 highlighting.
Updates the prior per_celltype_volcanoes_v3.png by:
• Re-colouring labels into the current evidence groups
• Inverse-concordant Tier-1 (2 genes: ITGB2, IKZF1) get RED bold * + thick ring
• Tier-2 aux... |
e8e9d5901d9ccf7c9492bdcaa2e33ec3b39b66c7bb5f7c37cba8c7fda841902d | Python | 10,442 | 259 | """Slater-Koster directional 2-centre integrals + Born-Mayer repulsion.
Wave-2 OCE extension. Provides the *machinery* (SK integrals + Born-Mayer)
and the *feature representation* needed to upgrade OCE 2F.
ARCHITECTURE OVERVIEW (essential):
In v1.1.x, 2F is shell-only Wolfsberg-Helmholz:
h_2F^WH(i,j) = sum_{... |
2932ad8c09e527d4556940fd69788cb0537bb6f644a17fad0d54fb2c927e4c98 | Python | 10,444 | 168 | # Copyright (c) 2019, Adobe Inc. All rights reserved.
#
# This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike
# 4.0 International Public License. To view a copy of this license, visit
# https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode.
"""
自定义pytorch函数，实现一维、二维、三维张量的DWT和IDWT... |
a4b8d410b1eb9aa5f6f7640f365be4d2649f8fee8cbd0850317090dbbdd02919 | Python | 10,444 | 253 | import argparse
import json
import os
import re
from tempfile import TemporaryFile, NamedTemporaryFile
from urllib.parse import urlparse
import boto3
import newspaper
import tldextract
from tqdm import tqdm
from warcio import ArchiveIterator
with open(os.path.join(os.path.dirname(__file__), 'domain_to_allowed_subdoma... |
56bd9ddcf1947b89bf90acd3c062305d0b867e39ce2add05b5bb8d4c4375bf96 | Python | 10,445 | 261 | """Function that converts a set of array files (.npz, .mat) containing spectrograms
into a pandas DataFrame that represents a dataset used by ``vak``.
The columns of the dataframe are specified by
:const:`vak.prep.spectrogram_dataset.spect_helper.DF_COLUMNS`.
"""
from __future__ import annotations
import logging
im... |
3153a8362c19a9977ee4ae10e60915362afd4c40538bbb4a2d4047ad8c5ea568 | Python | 10,448 | 301 | """Pin `fix_taxonomy` rewriting HasEnzyme/HasSpecies arguments it orphans.
`fix_taxonomy` used to delete a reclassified `other_organisms` id without
ever touching `doc["relations"]`, so a HasEnzyme subject or HasSpecies
object naming that id was silently dropped by `preprocess_relations`. These
tests exercise the rema... |
2443998d68a6db696b7e37e6c85f9c9f46a0e79d5db305a79899249242c69a16 | Python | 10,455 | 340 | import torch
import torch.nn as nn
__all__ = ["ResNet", "resnet18", "resnet34", "resnet50", "resnet101", "resnet152"]
def conv3x3(in_planes, out_planes, stride=1, groups=1, dilation=1):
"""3x3 convolution with padding"""
return nn.Conv2d(
in_planes,
out_planes,
kernel_size=3,
... |
9fd142b69bde71087856441600f3acef5f344702c26eecdc137926704772e3f3 | Python | 10,457 | 311 | """Parse behaviour CSV schemas and build extraction parameters.
All functions in this module operate on plain Python values or pandas
objects. They intentionally contain no UI-framework dependencies.
"""
from __future__ import annotations
import pandas as pd
DEFAULT_BEHAVIOUR_COLUMN_CANDIDATES = {
"Behaviours/... |
4ed08c9594f3d10834e3043725fe00af5fc8acf5639a31ac1af75b4730cc4046 | Python | 10,458 | 231 | from PyQt5.QtWidgets import *
from PyQt5.QtCore import *
from PyQt5.QtGui import *
import sys
class ChannelparametersSet(QWidget):
def __init__(self):
super(ChannelparametersSet, self).__init__()
self.setWindowTitle("通道参数设置")
self.setFixedSize(900,400)
self.setWindowIcon(Q... |
8b97b1d4289fb28a07c67ffbb5e8560fb657344ccf14af0d67d5123a746be312 | Python | 10,458 | 266 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Nov 17 21:07:57 2025
@author: vbp
Trial-history effect of outcome on anticipatory licking, for Figure 2B and
Figure S2D.
Fig S2D - delta anticipatory lick rate relative to baseline, across
trials before/after cued reward, omission, a... |
f2355336594e8de7b189dd0e5b7cb6a9f91e9ba4bee087b768e5c1894375f279 | Python | 10,458 | 287 | import zarr
import torch
import random
import sparse
import pickle
import itertools
import numpy as np
import pandas as pd
import torchvision.transforms.functional as F
from utils import MOUSE
from random import shuffle
from einops import rearrange
from torch.utils.data import Dataset
class MBADataset(Dataset):
... |
dae2114a90396c4b54f516e4314efb87551345723af179b7692e93e4e6ee16c5 | Python | 10,460 | 280 | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import numpy as np
import torch
import torch.nn.functional as F
from fairseq.models import register_model, register_model_architecture
from fa... |
a07b74047ae2eb3f68f100ad5639344333595242942821ac6af9b31c2a3d3dfa | Python | 10,463 | 295 | import pandas
def _dataframe(names, data):
columns = list(zip(*data))
d = {names[i]:columns[i] for i in range(0,len(names))}
d = pandas.DataFrame(d)
d = d[names]
return d
def sample_dosage_data_1():
#chromosome, rsid, position, non_effect_allele, effect_allele, frequency, allele_dosage
s =... |
6e28dbba5a1ce192ea719b9c06e684e3f22801bbf511b06dca3b80f60f9e0411 | Python | 10,468 | 212 | #!/usr/bin/env python3
"""DOS das perovskitas SIESTA: pipeline, validado antes de qualquer conclusão.
MOTIVO. O registro do projeto tem uma pendência declarada: nenhuma densidade de
estados foi jamais ajustada com OCE em conjunto algum. Para o artigo do gap das
perovskitas (RMSE/sigma 0,178, faixa forte), a DOS fecha ... |
435e6e41e61e42858af198e79084e523a1c650226bc9fec60e9346171bc7ff19 | Python | 10,477 | 302 | import argparse
import os
import random
from concurrent.futures import ProcessPoolExecutor
from copy import deepcopy
import h5py
import numpy as np
import torch
import torch.optim as optim
from sklearn.model_selection import KFold
from torch.utils.data import DataLoader, Dataset
from torchdiffeq import odeint
learnin... |
80ca02a38819be86ebab291d823ce3292f2cfe22d9c7bba7bbe11038d3f1f2a4 | Python | 10,481 | 299 | """
Copyright (c) Facebook, Inc. and its affiliates.
Copyright (c) Microsoft Corporation.
Licensed under the MIT License.
Adapted from https://github.com/FAIR-Chem/fairchem/blob/main/src/fairchem/core/models/gemnet/utils.py.
"""
import json
from typing import Any, Dict, Optional, Tuple
import torch
from torch_scatter... |
89ebe5c8b535c86e52cea95371d4f2064497f6eeaaa63c379ba23f57fcc03bfd | Python | 10,486 | 280 | import importlib
import logging
import os
import pickle
import re
import numpy as np
from collections import OrderedDict
from copy import deepcopy
from dataclasses import asdict, dataclass
from enum import Enum
from typing import Any
from .performer_module import PerformerModule
from .transformer import pytorchTransfor... |
c03e303b4b130a4396a6c999a72b04b8798870d59dfb46bdfc5ae15ff4dfd35e | Python | 10,490 | 316 | import os
import pickle
import hydra
import lightning as L
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
import torch
from captum.attr import IntegratedGradients
from lightning.pytorch.callbacks import ModelCheckpoint
from lightning.pytorch.loggers import WandbLogger
from... |
21010203ccb5a16de848d1e983805ddf3c4fba5f6dd0fa17d938033f53e11d2b | Python | 10,492 | 268 | # Copyright (c) Facebook, Inc. and its affiliates.
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
# Adapted from https://github.com/FAIR-Chem/fairchem/blob/main/src/fairchem/core/models/gemnet/gemnet.py.
from typing import Dict, List, Optional
# import numpy as np
import torch
import torch.... |
0cc3949c82660db6d415bbfd5147acbca37c59a270fa151ace3a642f06c55e7b | Python | 10,498 | 271 | # -*- coding: utf-8 -*-
import os
import gc
import argparse
import json
import random
import math
import random
from functools import reduce
import numpy as np
import pandas as pd
from scipy import sparse
from sklearn.model_selection import train_test_split, ShuffleSplit, StratifiedShuffleSplit, StratifiedKFold
from sk... |
cda44e38ad47eb12e5d71c93ce5e11807c736cc719a9d16a3b9df1a31bf648ea | Python | 10,508 | 302 | # Copyright 2020 The HuggingFace Team. 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 applicabl... |
4d59b82da07e487e9202ef86046734d2130d629c76553b6dbb8fe9e12a697fd1 | Python | 10,510 | 205 | import os
import math
import argparse
import numpy as np
from pathlib import Path
def parse_arguments():
parser = argparse.ArgumentParser()
# experiment
parser.add_argument("--random_seed", type=int, default=0, help="random seed for rng")
parser.add_argument("--epoch", type=int, default=0, help="epoch ... |
61e3f31a8bd249539064d7b7bc1f45a46ffbd3f9606bc2adad256f28e45a3421 | Python | 10,512 | 327 | import numpy as np
import pandas as pd
import statsmodels.formula.api as smf
from .paper_ANOVA import ANOVAModel
# Colours and types
Types = np.array(["T4", "T5"])
Type_colours = np.array(["#17becf", "#ff7f0e"])
Subtypes = np.array(["T4a", "T4b", "T4c", "T4d", "T5a", "T5b", "T5c", "T5d"])
Subtype_colours = np.array(
... |
d3374b16645168ce8c6eaeeb6b694337a39d28e967bebb7b968cf87556972a9a | Python | 10,513 | 254 | """Function that evaluates trained models in the frame classification family."""
from __future__ import annotations
import json
import logging
import pathlib
from collections import OrderedDict
from datetime import datetime
import joblib
import lightning
import pandas as pd
import torch.utils.data
from .. import dat... |
46c301b41634c9e92ae68e09ef2861f1daaa4c58001fe2790bc72e382115d34c | Python | 10,520 | 268 | from transformers import (
AutoModelForCausalLM, GPT2Config,
get_scheduler,
PreTrainedTokenizerFast,
DataCollatorForLanguageModeling
)
import numpy as np
import datetime
import random
import math
import time
import gzip
import os
from torch.optim import AdamW
import torch.utils.data
import torch.nn as... |
99120325f04f53429da2108e70b27834b6c12283a41c9c1c5f7e8d12cde8075c | Python | 10,521 | 292 | import os
os.environ["OMP_NUM_THREADS"] = "4" # export OMP_NUM_THREADS=4
os.environ["OPENBLAS_NUM_THREADS"] = "4" # export OPENBLAS_NUM_THREADS=4
os.environ["MKL_NUM_THREADS"] = "4" # export MKL_NUM_THREADS=6
os.environ["VECLIB_MAXIMUM_THREADS"] = "4" # export VECLIB_MAXIMUM_THREADS=4
os.environ["NUMEXPR_NUM_THREADS"]... |
f0b3004753d0bcf8c443af6613e86919eccd9419917eb88ca3c67acbac1539de | Python | 10,522 | 287 | """
Shared utility functions for epigenetic-protocadherin coordination analysis.
Harbert D. (2026) BMC Genomics
Inner Architecture LLC
"""
import os
import gzip
import subprocess
import pandas as pd
import numpy as np
from scipy.stats import pearsonr, spearmanr, fisher_exact
from scipy.stats import norm as sp_norm
fr... |
1097b9bfa69f51b146f0736165e56ec6469e837a626c00636d9e08d1be07273d | Python | 10,523 | 330 | import argparse
from pathlib import Path
import matplotlib.pyplot as plt
import numpy as np
from pewlib import Laser, io
from pewlib.config import SpotConfig
from pewlib.process.filters import rolling_median
import register
#Script to combine TIFF and LA-ICP-MS files for image fusion by cumilative density function a... |
bcdc93d68645c853688478f6ab24057e0a51f92cbc3a1a76d9d54fe7446de098 | Python | 10,523 | 213 | import sys
sys.path.append("../utils")
import torch
import torch.nn as nn
from utils import utils_basic
import config.cfg_lodet as cfg
#处理类别不平衡问题，使得模型更关注难分类的样本，从而提高性能
class FocalLoss(nn.Module):
def __init__(self, gamma=2.0, alpha=1.0, reduction="mean"):
super(FocalLoss, self).__init__()
self.__gamm... |
dc2e38bae7056f9149d262d12b506a78833dfe6c102a61eac3d85f62868aed9c | Python | 10,539 | 288 | import argparse
import hashlib
import importlib.util
import json
import shlex
from pathlib import Path
import numpy as np
import pytest
import torch
from gpn.scoring import log_likelihood_ratio, nucleotide_probabilities
FIXTURE_DIR = Path(__file__).parent / "fixtures"
BASELINE_PATH = FIXTURE_DIR / "published_model_b... |
765e53cd7806446235f7042638ce548c9e7e87a63ce3982d06f5d09dc25084ca | Python | 10,551 | 246 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Calculate the eigenmodes of a cortical surface
Updated to lapy 1.0.1
Original authors: James Pang and Kevin Aquino, Monash University, 2022
@author: James Pang, Monash University, 2025
"""
# Import all the libraries
from lapy import Solver, TriaMesh
import numpy as n... |
6979ad8befb2a0446085ae321c69789a94ab6bbf75e591c6bf61f64a6517fbbd | Python | 10,553 | 314 | """SIESTA DFT-PBE single-point runner for free C / Si clusters.
Strategy: spin-polarised DZP basis with PBE GGA on a non-periodic
simulation cell. The cell is set with ≥ 12 Å vacuum on all sides so that
the cluster does not interact with its periodic images.
Pseudopotentials (PSF / PSML) live in `pseudos/`.
Net cha... |
2f9cd7e26051657d9322694820f0ab578d31fdf9b44ef5772a872b35de980359 | Python | 10,554 | 187 | from .activations import *
from ..layers.convolutions import Convolutional, Cond_Convolutional
import math
import numpy as np
class Shuffle_new(nn.Module):
def __init__(self, filters_in, filters_out, kernel_size=3 ,c_tag=0.5, groups=3, dila=1):
super(Shuffle_new, self).__init__()
self.left_part = ro... |
c55fce650b47b4b5d353987d6bbc57d0b48976a10abea374049c0d13481828a1 | Python | 10,556 | 295 | __author__ = 'Robbert Harms'
__date__ = "2015-10-27"
__maintainer__ = "Robbert Harms"
__email__ = "robbert@xkls.nl"
class EstimableModel:
def __init__(self, *args, **kwargs):
"""This is an interface for all methods needed to be able to optimize and sample a model.
"""
super().__init__()
... |
3823a4c0d8fbbc3a5dd06309a73b88228f474d50501fe1e24cf389a270c83682 | Python | 10,560 | 301 | from os import makedirs
from os.path import join, exists
import numpy as np
import pandas as pd
import seaborn as sns
from matplotlib import pyplot as plt, gridspec
from matplotlib.ticker import FormatStrFormatter, NullFormatter
from scipy import stats
from sklearn import metrics
from config_path import PROSTATE_LOG_... |
593232d601fe8e5ee8d4dbabcd37d795c82ea256cfe45ad0152255baa4d99fe0 | Python | 10,563 | 236 | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn import Sequential, Linear, ReLU
from torch_geometric.nn import SGConv
class MLP(torch.nn.Module):
def __init__(self, sizes, batch_norm=True, last_layer_act="linear"):
super(MLP, self).__init__()
layers = []
f... |
86e64124aa468974546662f6afa9f5f42929c47a2dbe365d3b1cb5d31a61f38b | Python | 10,564 | 173 | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'generate_protocol_tab.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_GenerateProtocolTabContent(object):
def setupUi(self,... |
b9f5335bdb0e64227b4fb58b1431f5b74be79f5513b0c044b1a834a804b19be2 | Python | 10,564 | 361 | # -*- coding: utf-8 -*-
#
# Documentation build configuration file, created by
# sphinx-quickstart on Fri Nov 18 11:12:41 2016.
#
# 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
# autogenerated file.
#
# All confi... |
e56357d0e796efdac40e66599e36ab2aa5dfeefbd6bce080de265c0c77cd465d | Python | 10,565 | 269 | from __future__ import annotations
import gc
import logging
import os
import pickle
import traceback
import warnings
from typing import TYPE_CHECKING
import numpy as np
import pandas as pd
import torch
from scvi import settings
from scvi.model._utils import parse_device_args
from scvi.train import Trainer
from scvi.... |
a0f7c5e7a25d1140caf9bd280156eb9ab820674733f828567183f2dcdf3f1dcb | Python | 10,578 | 304 | import argparse
from pathlib import Path
import deepdish as dd
import h5py
import nibabel.freesurfer.mghformat as mgh
import numpy as np
from scipy import stats
from scipy.spatial import distance_matrix
from spacestream.analyses.smoothness import prep_smoothness
from spacestream.core.constants import ROI_NAMES
from s... |
b6c69dccca0525917a6b4190541b92991143907ace0c9244eacbe581041ab6de | Python | 10,588 | 312 | # -*- coding: utf-8 -*-
"""
@Time:Created on 2019/5/20 19:40
@author: LiFan Chen
@Filename: model_glu.py
@Software: PyCharm
"""
# -*- coding: utf-8 -*-
"""
@Time:Created on 2019/5/7 13:40
@author: LiFan Chen
@Filename: model.py
@Software: PyCharm
"""
import torch
import torch.nn as nn
import torch.optim as optim
import... |
d3576eefb5e5bb29f19a4996d607836dd32a26b2f4a1a936f3149abf32423344 | Python | 10,592 | 336 | # 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.
"""
A standalone module for aggregating metrics.
Metrics can be logged from anywhere using the `log_*` functions defined
in this module. The l... |
4a18d602dc6928e17f5e3ca89621fef7afa3b6a1c588053cd0960a990157525f | Python | 10,593 | 342 | """
Training Script for Vision Models
Supports both self-supervised pretraining and supervised classification.
Uses PyTorch Lightning for distributed training with DDP.
"""
import warnings
warnings.simplefilter(action='ignore', category=FutureWarning)
import os
import logging
import argparse
import torch
import pyto... |
c4c4af7ea19625d4ffec9fa88516290e6876ff2844ae616896f1c2535a45bf03 | Python | 10,596 | 346 | from pathlib import Path
from types import SimpleNamespace
import numpy as np
import pytest
import torch
from gpn.star import inference as inference_module
from gpn.star import model as model_module
from gpn.star import utils as utils_module
def make_phylo_dist(path: Path) -> Path:
path.mkdir(parents=True)
... |
279559af57f1106e02aedf545aabf3763d15b480bb382b6d3de0b950a7b2f03d | Python | 10,601 | 264 | import os
import time
import math
import random
import numpy as np
import argparse
import torch
import torch.nn as nn
from yaml import parse
from gnn_data import GNN_DATA
from gnn_model import GIN_Net2, GIN_Net3
from utils import Metrictor_PPI, print_file
from tensorboardX import SummaryWriter
def boolean_string(s):... |
3999f5b06c09f87ca6d8a096639bec5f98bc9b48e377f5008b71ddb5e28a3117 | Python | 10,604 | 259 | from collections import deque
from collections.abc import Hashable
import networkx as nx
import pandas as pd
from sklearn.base import clone
from tqdm.auto import trange
from pgmpy import config
from pgmpy.base import DAG
from pgmpy.causal_discovery import ExpertKnowledge
from pgmpy.causal_discovery._base import BaseC... |
93f05a77f7bdb7899450231a2031c13dbcc416d53ad1b0a5a220701f563539ba | Python | 10,608 | 320 | """
Adapted from https://github.com/neuroailab/TDANN/blob/main/spacetorch/swapopt.py
"""
import copy
import sys
from dataclasses import dataclass, field
from datetime import date
from pathlib import Path
from typing import Any, Dict, List, Optional
import numpy as np
from numpy.random.mtrand import RandomState
from tq... |
75fce7ad168fd000ac700d67af3a243df0ab225971d5bdcae84761e1427cb6f3 | Python | 10,612 | 275 | # 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 typing import List
import torch
from fairseq.token_generation_constraints import (
ConstraintNode,
OrderedConst... |
f51adae74bfe0e9ece4b800bc2c4e903106743c7f77704b865da21a27edfbb13 | Python | 10,615 | 344 | #!/usr/bin/env python3
"""Generate benchmark charts from hyperfine JSON outputs.
Reads `<data>/{rust-beta5,rust-beta7,perl-0.6.11}_cN.json` (the per-condition
hyperfine outputs from `scripts/benchmark.sh`), produces three PNGs into
`<out>/`:
benchmark_wall_time.png — wall time vs cores, three engines
bench... |
da31abe72bcda76e1d1b0fc877ebde8ab6367bbffdff38cc90dd6b24d0a90915 | Python | 10,617 | 322 | from itertools import chain
import anndata
import numpy as np
import pandas as pd
import pytest
from anndata import AnnData
from scipy.sparse import csr_matrix
from scipy.spatial import Delaunay
from sklearn.metrics import euclidean_distances
import novae
from novae._constants import Keys
from novae.data.dataset impo... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.