sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
8c1cddd31b76fa8a8c8906aa6ea611b3698357652c96bb53cf42e67570462229 | Python | 18,277 | 416 | # SOURCE: vendored from Dr-Patient/pytorch_NeoDTI @ main
# https://raw.githubusercontent.com/Dr-Patient/pytorch_NeoDTI/main/src/model.py
# https://raw.githubusercontent.com/Dr-Patient/pytorch_NeoDTI/main/src/pytorch_NeoDTI_cv.py
#
# Wan, Zeng, Liao, Zhang 2019 (Bioinformatics) "NeoDTI: Neural integration of neighbor
# ... |
f7f9d4252bc7b92d11ed5faccbd490b6b036a75ffd8049f5285130642581e190 | Python | 18,287 | 577 | #!/usr/bin/env python3
import multiprocessing
import regex as re
import logging
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
import numpy as np
from MarkovModels import common
from MarkovModels.BeattieModel import BeattieModel
from MarkovModels.ClosedOpenModel import ClosedOpenModel
from M... |
c6d0a0761eae24f07d83535d081dd264f5758f2f050d47bf593223336694d118 | Python | 18,290 | 434 | '''
Copyright 2021 Twente Medical Systems international B.V., Oldenzaal The Netherlands
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 requir... |
1d6b52859aa3e75a423f368e80a1572eef0ca44288e6b5ef65ee756c07a0b9ff | Python | 18,294 | 503 | import matplotlib.pyplot as plt
import re
import os
from scipy.spatial import distance
import numpy as np
import seaborn as sns
from os import listdir
from os.path import isfile, join
from utils import permute_l
import h5py
import pandas as pd
from constants import *
import logomaker
def read_roc(path):
acc_di... |
592bdc2714c4b6193b404bbc5ec5047714688c9a9aeb23380db67b6c0ea285df | Python | 18,295 | 452 | # Copyright 2025 Google.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, soft... |
3ccf501108d4c50c42b6bc464ff4466a3429d28adb7540589f14d0ad4b5b9360 | Python | 18,298 | 393 | # ---
# jupyter:
# jupytext:
# formats: ipynb,py:percent
# text_representation:
# extension: .py
# format_name: percent
# format_version: '1.3'
# jupytext_version: 1.11.5
# kernelspec:
# display_name: brainpy
# language: python
# name: brainpy
# ---
# %% [markdown]
# # *... |
248c11bd6ed2f80baca42b753ac794377ccac59e423937c1780786a02da31cad | Python | 18,300 | 429 | #!/usr/bin/env python3
import unittest
"""
compare.py - versatile benchmark output compare tool
"""
import argparse
from argparse import ArgumentParser
import json
import sys
import gbench
from gbench import util, report
from gbench.util import *
def check_inputs(in1, in2, flags):
"""
Perform checking on th... |
832cef7659e2db733111fabc54bf7e20efecf5fb9df21e15a582168fcba153d5 | Python | 18,301 | 533 | """
Bug Report API Module
Generates comprehensive bug reports for debugging by collecting system
information from the node and all connected ethoscope devices.
"""
import datetime
import platform
import shutil
import socket
import subprocess
import sys
from typing import Any
import bottle
import netifaces
from .bas... |
93e3262eeb6bddf3d56e692f2c064899f9fcad7158ef9b1d289ca08f8e84593a | Python | 18,303 | 444 | import torch
import torch.nn as nn
import torch.nn.functional as F
from ..base import _layers as layers
from ..base import _blocks as blocks
from ..base import _towers as towers
class DeepSEA(nn.Module):
"""DeepSEA model implementation from Zhou et al 2015 in PyTorch
This is a flexible implementation of the ... |
30a3c579474810a4210d2106300f7d33db4f1cd2fb8ec61f6a4320fd840bff9c | Python | 18,307 | 446 | import numpy as np
from scipy.spatial.distance import *
import pandas as pd
from sklearn.model_selection import train_test_split
from nilearn.surface import load_surf_data
import bct
from netneurotools import networks as nets
from netneurotools import metrics, datasets
from strength_preserving_rand import strength_pr... |
97be54ac817357f065ef6a41b7109df096471d23253067b27769efa772e886d2 | Python | 18,307 | 466 | #!/usr/bin/env python
#
# Check the installation and environment variables of the toolbox and its dependencies.
#
# Copyright (c) 2013 Polytechnique Montreal <www.neuro.polymtl.ca>
# License: see the file LICENSE
# TODO: if fail, run with log and display message to send to sourceforge.
# TODO: check chmod of binaries
... |
4092f8e2949203729c5858da199ad9d4729484bc42af3a67c37db1ef276c26b1 | Python | 18,316 | 484 | # Copyright (c) 2022 PaddlePaddle 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 app... |
adacce42f001f9642cf4ba3c589faa593ca5bc324543d3f259b60e4f9d3c5e3c | Python | 18,318 | 472 | from contextlib import closing
from io import StringIO
from os import path
from typing import Optional
import numpy as np
from gym import Env, logger, spaces, utils
from gym.envs.toy_text.utils import categorical_sample
from gym.error import DependencyNotInstalled
MAP = [
"+---------+",
"|R: | : :G|",
"|... |
d3ee615afc931fc29dea1c42d0f15c01727db386ea3f82cb95616ded54f4b837 | Python | 18,319 | 549 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType
import copy as _copy
class Newshape(_BaseLayoutHierarchyType):
_parent_path_str = "layout"
_path_s... |
f9d0593771351b2684360854aefe18531b26f44fbb8d8086bfb973fd4e4e2043 | Python | 18,322 | 353 | import csv
import itertools
import os
from collections import OrderedDict
import PIL.Image
import numpy as np
import torch
import torchvision.transforms
from torch.utils.data import Dataset
from datasets.basic import MultiSiteDataset
from utils.lung_cropping_tools import get_crop_model, learning_based_lung_cropping
f... |
dfc28c6ee7e3f20c2ea24b10b781bc21e12fb0a1f42660c6ab6ca1192112db02 | Python | 18,327 | 428 | import sys
import os
import math
import copy
import numpy as np
import pandas as pd
import textwrap
import seaborn as sns
from scipy import stats
from statsmodels.distributions.empirical_distribution import ECDF
from sklearn.preprocessing import MinMaxScaler
from plotnine import *
import matplotlib.pyplot a... |
849b2235a7f255f8ea413fcb6ad075e6a9b50039b5b209b13a6ba2b3f02f2bc0 | Python | 18,331 | 536 | #!/usr/bin/env python3
"""
Deterministic STEPS 3D calcium diffusion in realistic morphologies with
geodesic binning
Last updated: 20.08.2026
Author: Laura Keto
Description
-----------
This script performs deterministic 3D calcium diffusion simulations in
realistic astrocyte branchlet morphologies using the STEPS Tet... |
ee8e92f3d0fd19acc9c1527b7c3a5282d1b1ea6ded4ec3afdbf3a0c7753f69a4 | Python | 18,333 | 663 | import os
from collections.abc import Iterable
from time import sleep
from pydantic import BaseModel
from celery import Signature, Task, chain, chord, group, shared_task
from celery.canvas import signature
from celery.exceptions import Reject, SoftTimeLimitExceeded
from celery.utils.log import get_task_logger
from ce... |
54564cc5958a983f72dfaae4f9a363a8c344e2d7b84e78ab27b4f2d27888b786 | Python | 18,335 | 557 | # Copyright 2025 Google.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, soft... |
6a7957d4bb6b31e88eafece9f0cdf6cb7771d651636bf6e88eea4e1f737d5d1a | Python | 18,340 | 657 | """Handles the constants, everything that is displayed in the widget"""
# License: GNU General Public License v3.0
import os
import numpy as np
METHODS = ["PCMCI", "PCMCI+"]
TESTS = ["ParCorr", "RobustParCorr", "ParCorrMult", "ParCorrWLS", "GPDC", "GPDCtorch", "CMIknn", "CMIsymb", "Gsquared", "CMIknnMixed", "Regression... |
ff377fc09dde04e7d65c94791a03842db837c816f6f0ef010c32992110c2087d | Python | 18,341 | 426 | import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' # FATAL
import scipy
import scipy.io as sio
from scipy.sparse.csgraph import dijkstra
from scipy.sparse import lil_matrix
import sklearn
from sklearn.metrics import pairwise_distances_chunked
from sklearn.decomposition import PCA
from sklearn.preprocessing import Sta... |
be25217ac78ad45f4eb1f774785a3bd70b96d4a119a0fd358f50e3a1bc3946dd | Python | 18,358 | 509 | # -*- coding: utf-8 -*-
#
# pythonguide documentation build configuration file, created by
# sphinx-quickstart on Wed Aug 4 22:51:11 2010.
#
# 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.
#
#... |
c418816b3a1141e395d09e5970dd54935ea4b8b3f2ed6f092f2ced7313de7070 | Python | 18,366 | 472 | import copy
from typing import List, Tuple, Union
try:
from typing import Literal
except ImportError:
from typing_extensions import Literal
import numpy as np
import scipy
from anndata import AnnData
from ..logging import logger_manager as lm
# --------------------------------------- Normalizing sparse arra... |
1ad60b1ed8a288131fc4c54a368889d25874f0985ccf3c80e048b1d60f8efdd4 | Python | 18,367 | 569 | import os
from math import log
import argparse
def even(x):
x = int(x)
if x % 2 != 0:
raise RuntimeError("Expected even number but received {}".format(x))
return x
def str2bool(v):
if isinstance(v, bool):
return v
if v.lower() in ('true', 'y', 't'):
return True
elif ... |
a8752faf87b53cc067e9d098f95c4bcc4769be773ffdfcca7aab2c6a0ae00bec | Python | 18,372 | 755 | from itertools import cycle
import numpy as np
from plotly.subplots import make_subplots
from plotly.colors import qualitative
from cvsx.unit_conversions import convert
def latex(s: str):
if s.startswith("p_") or s.startswith("q_") or s.startswith("v_"):
s = s[0].upper() + s[1:]
parts = []
for s... |
d317b98fe6f8b36ce67f6b6530a05500a8301b99c52a03777a647bad708b697b | Python | 18,372 | 431 | import nibabel as nb
import numpy as np
def load_mgh(filename):
""" import mgh file using nibabel. returns flattened data array"""
mgh_file=nb.load(filename)
mmap_data=mgh_file.get_data()
array_data=np.ndarray.flatten(mmap_data)
return array_data;
# function to load mesh geometry
def load_mesh_geo... |
e66a2453574fb629aeb26e6a34d29276e3d260bbcd5522c80e67f8dcd6ca04fc | Python | 18,380 | 424 | #!/usr/bin/env python3
"""
NanoVar
This is the main executable file of the program NanoVar.
Copyright (C) 2021 Tham Cheng Yong
NanoVar is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the Li... |
13430e55098e46381afeda9ff6ec2e0b7f68e83fbf02458cd090a8c0f86fe5e7 | Python | 18,383 | 476 | import locale
locale.setlocale( locale.LC_ALL, 'en_US.UTF-8' )
import re
import pandas as pd
import camelot
import pdfminer
from pdfminer.high_level import extract_pages
try:
from local_extractor.utils import common_utils
except ImportError:
import sys, os, pathlib
path = pathlib.Path(__file__).absolute(... |
6555d2b31c027772995cc8d63ceeb038add662bb010eabeece919382ed87f899 | Python | 18,385 | 489 | import json
import logging
import optparse
import os
import signal
import sys
import time
import traceback
from dataclasses import asdict
from http.server import BaseHTTPRequestHandler, HTTPServer
from ethoscope_node.backup.helpers import GenericBackupWrapper, UnifiedRsyncBackupClass
from ethoscope_node.utils.configur... |
812c9e6d5cd34c661b151a313b1347a4e294f1d6405a7789ed82cdeb6431aa0c | Python | 18,391 | 379 | """
.. _tut-sensor-level:
Tutorial part 1: RSA on sensor-level MEG data
---------------------------------------------
In this tutorial, we will perform sensor-level RSA analysis on MEG data.
We will explore how representational similarity analysis (RSA) can be used to study the
neural representational code within vis... |
2049c119520e79221e462754e55e65d395041d0839d603ae2a2a720ef40c649a | Python | 18,398 | 572 | # -*- coding: utf-8 -*-
# %% [markdown]
# # Find Fixed Points
# %% [markdown]
# The goal of this tutorial is to learn about fixed point finding by running the algorithm on a simple data generator, a Gated Recurrent Unit (GRU) that is trained to make a binary decision, namely whether the integral of the white noise inp... |
1cd71c3f60f71d5e02c2dbaa9cb2e439bc4beeb7f233293758ac87186bcc2cd2 | Python | 18,399 | 378 | # -------------------------------------------------------------------------------------
# Code with functions to plot results from model fittting
# Marta Blanco-Pozo, 2023
# -------------------------------------------------------------------------------------
import os
import joblib
import pandas as pd
import seaborn ... |
1bbe26b04b845d8d81703c73478cb2db78451dbac70a4b4fa469cd4689ce36ce | Python | 18,403 | 514 | """Utility methods for ome_zarr access."""
import csv
import json
import logging
import os
import urllib
import webbrowser
import xml.etree.ElementTree as ET
from collections.abc import Iterator
from datetime import UTC, datetime
from http.server import ( # type: ignore[attr-defined]
HTTPServer,
SimpleHTTPReq... |
a79cb42dfc33e126227bdba27ae7a024d7d5cc5c8fd7f7a5f26c68d501024e0a | Python | 18,412 | 482 | # Copyright (c) 2025, Tri Dao
import math
from functools import partial
from typing import Optional, Tuple, Union
import torch
from torch import Tensor
from einops import rearrange, repeat
from flash_attn.ops.triton.rotary import apply_rotary
def rotate_half(x, interleaved=False):
if not interleaved:
x... |
a58108a7567bcc7512e2079ed82d134be74837d0137a1e773c6987cd043bc662 | Python | 18,420 | 532 | """Interleaved same-runner A/B performance gate for the nightly workflow.
The previous nightly gate ran three whole smoke suites back to back (parent,
release anchor, current) and compared single medians. Runner drift over those
five minutes read as a regression: a row with no TorchLens code failed the gate
at 1.40x, ... |
8df1d4ba3b3b386ea010798f9219b4f8e6790a36dab5f15c452cf74009887ccb | Python | 18,422 | 547 | import pytest
import textwrap
import types
import warnings
from itertools import product
import rpy2.rinterface_lib.callbacks
import rpy2.rinterface_lib._rinterface_capi
import rpy2.robjects
import rpy2.robjects.conversion
from rpy2.rinterface.tests import utils
try:
import IPython
except ModuleNotFoundError as no... |
930c883db4df7d1e947ff4d72d0dd649d2c1902fee648be89ab3ebcc765993a8 | Python | 18,429 | 412 | """Auto pipeline for object detection task"""
# pylint: disable=bad-whitespace,missing-class-docstring,bare-except
import time
import os
import math
import copy
import logging
import pprint
import json
import pickle
from typing import Union, Tuple
import uuid
import shutil
import numpy as np
import pandas as pd
from a... |
00a3785313f7da1c733ec16bac27fcf3f12577a8bbb2ee6a3724ea3227b98458 | Python | 18,440 | 447 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Oct 14 15:13:14 2020
@author: Audrey Mazancieux
This script performes "event-related" analyses for one subject that has
performed the local-global task on signal extracted from an ROI in native or
standardised space (using the extract_timeSerie scri... |
6046a4756fa024d542a99192bf4a7383f8897ec6816f46117659c0f241cbbb6c | Python | 18,442 | 520 |
# This file helps to compute a version number in source trees obtained from
# git-archive tarball (such as those provided by githubs download-from-tag
# feature). Distribution tarballs (built by setup.py sdist) and build
# directories (produced by setup.py build) will contain a much shorter file
# that just contains t... |
8c0f45192aa075ff800e1db7e74fec3eda404c42591d296c80aeb99ebc2657bb | Python | 18,445 | 511 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType
import copy as _copy
class Grid(_BaseLayoutHierarchyType):
_parent_path_str = "layout"
_path_str =... |
0c0ea88d789be1cefba8a5c0c55a120a8a17ed8b5224b433b0add4bde397fb85 | Python | 18,451 | 527 | # -*- coding: utf-8 -*-
import tensorflow as tf
## ResNet base model ##
class ResNet(tf.keras.models.Model):
def __init__(self, stacks, version, use_bias, classes, bn_ep=1.001e-5):
super(ResNet, self).__init__()
self.version = version
self.stacks = stacks
# initial layers
... |
d2b2294b1b108301d21666023f7259d6e633272e629e9d5f5bf5cbebf4c02b54 | Python | 18,462 | 539 | from __future__ import annotations
import sys
import pytest
import env # noqa: F401
from pybind11_tests import ConstructorStats
from pybind11_tests import methods_and_attributes as m
NO_GETTER_MSG = (
"unreadable attribute" if sys.version_info < (3, 11) else "object has no getter"
)
NO_SETTER_MSG = (
"can'... |
5e3592ebe824d0e51b2236ce2cb6b53885574bd5f955aa2035b5d9662639d0be | Python | 18,474 | 489 | # Copyright (c) 2022 PaddlePaddle 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 app... |
487f7e1bf10b875a6e45052126dfd42578ac51ae320842b088b506b6fbf2e7e2 | Python | 18,477 | 583 | """Round-28/31 capture-attribution regression pins.
Locks the fixes for the round-31 capture-reseal findings (review) and the
validation false-negative hunt (review): H2 runtime tensor control-arg parents,
H1/M3 foreach attribution, M4 element-overlap alias propagation, M5 in-place
grad_fn metadata, M6 tensor property... |
f01221b184389b4525240e3cd3a599653b2c634122141d740ae781e45509e7ac | Python | 18,478 | 495 | """Resumability + self-description contract tests for :func:`torchlens.extract_dataset`.
Covers the artifact-v2 resume mechanism (extract memo D1: append-only fsynced
ledger, commit protocol, field-by-field signature compare, crash-safety proven
via a hard child-process death) and the self-describing bounded manifest ... |
635a3f3a35a25a9699279f1282f15d37f246a582698f4b7665c7fee0752f586b | Python | 18,479 | 579 | """Tests of decoding for `pynapple` package."""
from contextlib import nullcontext as does_not_raise
from itertools import product
import numpy as np
import pytest
import pynapple as nap
def get_testing_set_n(n_features=1, binned=False, bin_size=1.0, time_units="s"):
combos = np.array(list(product([0, 1], repe... |
015f55684688bb6bd587a5d1749b2c134211e09497c977c161e8b2246ba3f0c0 | Python | 18,490 | 445 | """Final end-to-end integration gates for influence geometry."""
from __future__ import annotations
from collections.abc import Iterator
from fractions import Fraction
from pathlib import Path
from unittest import mock
import pytest
import torch
from support.rf_isolation import preserved_rf_registry
from torch impor... |
3ab6e664adccd79c529a408767d5f0ae6f191335499a7538f4e9874c363ad924 | Python | 18,490 | 417 | """Directpose implementation"""
# pylint: disable=line-too-long, redefined-builtin, missing-class-docstring, unused-variable,unnecessary-comprehension
import math
from typing import List, Dict
import torch
from torch import nn
from torch.nn import functional as F
from torch.autograd import Variable
import numpy as np
... |
55b751d76346863c830d32f5cc03a333cea12289d46c087e92fe01ee31da7436 | Python | 18,497 | 451 | """Generate a diffusion map embedding
"""
import numpy as np
has_sklearn = True
try:
import sklearn
except ImportError:
has_sklearn = False
def compute_diffusion_map(L, alpha=0.5, n_components=None, diffusion_time=0,
skip_checks=False, overwrite=False,
eige... |
97db0f85c672e6856133c2283ea36c3078acef43ca511a5d888aaa85c29a30e5 | Python | 18,497 | 473 | """
Created on 15/07/2014
@author: Andrew Robinson
Modification on 24/10/2022
Addition of LDAP3 auth provider using the ldap3 module. The original LDAP auth provider uses the python-ldap library which
has external dependencies like openldap client libs. ldap3 is a pure Python LDAP v3 client library.
@author: Mahend... |
8f428a353bdb017c1bfd32661d88521663493b5b3c5906a9be1cd186985ad41e | Python | 18,498 | 543 | # Copyright (c) 2022 PaddlePaddle 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 app... |
b57dfe102f5a1989ee092cf4d8327364fec5e56ab13f000d454816051a6d6a4e | Python | 18,503 | 514 | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from http.client import RemoteDisconnected
import json
import numpy as np
import torch
import torch.nn.functional as F
from torch import nn
class NBLoss(torch.nn.Module):
def __init__(self):
super(NBLoss, self).__init__()
def for... |
81b094d521b7024bfad5250087736d7cfc1911408b7bc566cebdac379db18083 | Python | 18,505 | 520 |
# This file helps to compute a version number in source trees obtained from
# git-archive tarball (such as those provided by githubs download-from-tag
# feature). Distribution tarballs (built by setup.py sdist) and build
# directories (produced by setup.py build) will contain a much shorter file
# that just contains t... |
1ca97b29de73c9e403f9a75b63f1d3e3464f08853b4aca7f74c8b33762c4a930 | Python | 18,506 | 550 | """
Functions to realign time series relative to a reference time.
"""
from numbers import Number
import numpy as np
from .. import core as nap
from ._process_functions import _perievent_continuous, _perievent_triggered_average
def compute_event_triggered_average(
data,
events,
binsize,
window=0,
... |
55bf09ce5fe6f47458c5d90b2e014381069d0a8a44e832e88d082e4abc63159c | Python | 18,509 | 482 | import os
import subprocess
import numpy as np
import pickle as pkl
import nibabel as nib
from os.path import join as pjoin
from scipy.stats import pearsonr, permutation_test
from nibabel.gifti import GiftiDataArray, GiftiImage
from sklearn.linear_model import LinearRegression, Lasso
from sklearn.metrics import r2_scor... |
222dbac2d7c80ce0b188cb57399e5ab6a84c7f8a6dc6d8aee9d14166bfe59b06 | Python | 18,515 | 464 | """HD256 varlen API, cache, and CUDA-graph regression tests on SM100/SM110.
None and fresh CUDA scalar maxima must share a device-driven specialization
without host reads; Python integers retain rectangular scheduling in the backward.
Set FLASH_ATTENTION_HD256_STRESS=1 for additional randomized cases.
"""
import os
f... |
764f874e824b73d9c832cd32105e8f7d8cef525431890a8404ef9db2fe1ccae4 | Python | 18,516 | 520 |
# This file helps to compute a version number in source trees obtained from
# git-archive tarball (such as those provided by githubs download-from-tag
# feature). Distribution tarballs (built by setup.py sdist) and build
# directories (produced by setup.py build) will contain a much shorter file
# that just contains t... |
9ef4f34e005dcd752e0d45e9b71b8d0366835d1951637896dfba5cabede24422 | Python | 18,517 | 437 | '''
Copyright 2021 Twente Medical Systems international B.V., Oldenzaal The Netherlands
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 requir... |
d7e0a4f6d969868f0746608a0016a63028ccedae7048117ddc69a7057b560f35 | Python | 18,525 | 554 | import fnmatch
import io
import logging
from uuid import UUID
import requests
from requests.exceptions import ConnectionError, HTTPError
from .cromwell_metadata import CromwellMetadata
logger = logging.getLogger(__name__)
def requests_error_handler(func):
"""Re-raise ConnectionError with help message.
Cont... |
48e2fe09312ae8ffe4503d3439c0fb1465cc11241e3ce65b01f2dc607a83dccb | Python | 18,526 | 495 | """Utilities to help job and tool code setup jobs."""
import json
import os
import shutil
import threading
from typing import (
Any,
cast,
NamedTuple,
Optional,
)
from galaxy.files import (
ConfiguredFileSources,
DictFileSourcesUserContext,
FileSourcesUserContext,
)
from galaxy.job_executi... |
2f2b8c2b89dc100a1f8531d527c08fdc4017210d6e99442fc885806becb76568 | Python | 18,534 | 470 | #!/usr/bin/env python
"""
Integration tests for the notification system.
Tests end-to-end workflows and component interactions.
"""
import datetime
import json
import os
import tempfile
import time
from unittest.mock import MagicMock, Mock, patch
import pytest
from ethoscope_node.notifications.base import Notificat... |
45311666a14a2803b115f7294c658c2193ff3bbee78d9c5be04423ef4686f417 | Python | 18,535 | 507 | """
Target Detection Analysis Module for Node
This module provides node-side analysis capabilities for target detection data
collected from ethoscope devices, including failure pattern analysis, dataset
management, and reporting functionality.
"""
__author__ = "giorgio"
import json
import logging
import shutil
from ... |
b0bd71d4f5904325bc5cd576930dc2a198503486b4d60c9397f1472fd739508f | Python | 18,538 | 374 | """Train YOLOv3 with random shapes."""
import argparse
import os
import logging
import time
import warnings
import numpy as np
import mxnet as mx
from mxnet import nd
from mxnet import gluon
from mxnet import autograd
import gluoncv as gcv
gcv.utils.check_version('0.6.0')
from gluoncv import data as gdata
from gluoncv ... |
d29a7ed0ffd6f335738013834134ffcd9fb2a09dc78f7a3741e5a33c5e2ab946 | Python | 18,538 | 462 | # Copyright (c) MONAI Consortium
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, so... |
14654c474682fcd05ac5ef2755654785118dfb8633fbaabae1d838cbeb7465e5 | Python | 18,554 | 472 | """Spatial markers.
"""
import warnings
from random import sample
from typing import Tuple
import anndata
with warnings.catch_warnings():
warnings.simplefilter("ignore")
import geopandas
import numpy as np
import pandas as pd
from joblib import Parallel, delayed
from ..configuration import SKM
@SKM.check_... |
fb530090a824e7249d144579cad42ebbab22203f2b51c0b549655554d00ab1a2 | Python | 18,556 | 492 | import numpy as np
from keras.src import layers
from keras.src import ops
from keras.src import random
from keras.src import testing
class OneStateRNNCell(layers.Layer):
def __init__(self, units, state_size=None, **kwargs):
super().__init__(**kwargs)
self.units = units
self.state_size = s... |
adb2409c16d740c538398c7aefbd063ca749caa954df0f60666407df5a0bd49e | Python | 18,568 | 374 | """Train YOLOv3 with random shapes."""
import argparse
import os
import logging
import time
import warnings
import numpy as np
import mxnet as mx
from mxnet import nd
from mxnet import gluon
from mxnet import autograd
import gluoncv as gcv
gcv.utils.check_version('0.6.0')
from gluoncv import data as gdata
from gluoncv ... |
2de0723de9eff256afb6ff95f79cb6e1dbc243f691f2984a759e74d5e1e49b9c | Python | 18,572 | 388 | """
Functionalities to aid in feature selection to characterize signaling patterns from spatial transcriptomics. Given a
list of signaling molecules (ligands or receptors) and/or target genes
"""
import argparse
import os
from typing import List, Literal, Optional, Union
import numpy as np
import pandas as pd
import s... |
98d350c973c742d802d6341139dbd4ed2dd48a93a6c36295bc5b1e9b9ed52fed | Python | 18,576 | 564 | import collections
import math
import numpy as np
from keras.src import backend
from keras.src import tree
from keras.src.backend.common import is_float_dtype
from keras.src.backend.common import standardize_dtype
from keras.src.trainers.data_adapters import data_adapter_utils
from keras.src.utils.module_utils import... |
ca9db3766734a99334ac32282b3ea5adda5daad6ba82991a70b07db4240c5727 | Python | 18,576 | 478 | import re
import pytest
import torch
from einops import rearrange
from flash_attn.models.gpt import (
GPTLMHeadModel,
remap_state_dict_hf_gpt2,
shard_state_dict_tp,
combine_state_dicts_tp,
)
from flash_attn.utils.generation import InferenceParams
from flash_attn.utils.pretrained import state_dict_from_... |
b79b1f1b623e7790569b44b91294f1811c38f24e7b17b5f81843c92b1ba7e1d5 | Python | 18,581 | 561 | import pytest
from pyrosm import get_data
@pytest.fixture
def test_pbf():
pbf_path = get_data("test_pbf")
return pbf_path
@pytest.fixture
def helsinki_pbf():
pbf_path = get_data("helsinki_pbf")
return pbf_path
@pytest.fixture
def helsinki_region_pbf():
pbf_path = get_data("helsinki_region_pbf"... |
ae1a320b41725277ec7c07cb2bb920099352d940db38bb6d0e8fa76487d238d2 | Python | 18,582 | 397 | import pathlib
import sys
import numpy as np
import optuna
import pandas as pd
import torch
import torch.nn as nn
from pyreadr import pyreadr
from sklearn.metrics import roc_auc_score, precision_recall_curve, auc
from torch.utils.data import Subset, DataLoader
from datasets import VisitSequenceWithLabelDataset, pad, ... |
c2f777079a573c7a5999f6d60871ff45082963ca2966aa78895476ef217735ef | Python | 18,590 | 549 | """Reusable read-only Panel tables for LarvaDataset step and endpoint data."""
from __future__ import annotations
from html import escape
from collections.abc import Callable
from typing import TYPE_CHECKING, ClassVar
import pandas as pd
import panel as pn
from larvaworld.lib.param.custom import EndpointDataFrame, ... |
7d8b8ba6992042f36967b1cc7925fcdfd66edb6417e24266a15cb841d2968b3e | Python | 18,593 | 538 | import numpy as np
import pandas as pd
from anndata import AnnData
import scipy.spatial as spatial
from numba.typed import List
from numba import njit, jit, prange
from stlearn.tools.microenv.cci.het_helpers import (
edge_core,
get_between_spot_edge_array,
get_data_for_counting,
add_unique_edges,
... |
f4273d89415baf4b205ca125f4fac49b7f6902132453adbc624d6609e65291d1 | Python | 18,593 | 330 | import torch
import torch.nn as nn
import numpy as np
from .losses import smoothl1_loss, l1_loss, SigmoidFocalClassificationLoss
from external_src.group_free_3D.OR_4D.OR_4D_detection_dataset import DC
def compute_points_obj_cls_loss_hard_topk(end_points, topk):
box_label_mask = end_points['box_label_mask']
s... |
4e4d2e53d2a6ceab02b32004ebc1a5ab2d9d9ef5be591234a1ab8698573483fa | Python | 18,598 | 442 | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... |
0008fedc6695b31a81c3bb5a1b355263fd1474c70fbf9e5fb2facdacbfba3f5c | Python | 18,605 | 554 | #############################################
# This file contains scripts to perform the #
# Convolutional Neural Net experiments. #
# #
# Author: Jonas Ditz #
#############################################
import argparse
import os
import pickle
im... |
10176267074a7c088f729bc36e3a46c81ca4c3b3efe8611819fd9ca9fdb1d492 | Python | 18,609 | 562 | """
glm.py
This module contains functions to run and analyse GLMs predicting ROI activity
from stimulus and behavioural information for data generated by the Allen
Institute OpenScope experiments for the Credit Assignment Project.
Authors: Colleen Gillon
Date: September, 2019
Note: this code uses python 3.7.
"""
... |
e50dcb6ba91e8c6cc18d41b68171e1309b85aa4481009ba13d9d505dfa5b0147 | Python | 18,610 | 501 | import argparse
from multiprocessing.spawn import prepare
import random
import os
import glob
import matplotlib.pyplot as plt
import numpy as np
from pathlib import Path
import pandas as pd
from sklearn.linear_model import LogisticRegression, LogisticRegressionCV
from sklearn.model_selection import train_test_split
f... |
c43c0f164b12e9f8cea07de50d2d36b0d8f22fd368c627cf4a76e1e9320dfeae | Python | 18,622 | 455 | import pickle
import random
import numpy as np
import json
import os
import glob
from typing import List, Dict, Any
import warnings
warnings.filterwarnings('ignore')
## TODO: Interface config should be loaded from the config file rather than hardcoded here.
## @liuyang: 2025-03-20
GEN_INTERFACE_CONFIG = {
"interf... |
3a9b90a912285590b97c7ac465661715af6f5b3f07bf7b6998ccac649d7146fa | Python | 18,625 | 493 | import copy
from tqdm import tqdm
import torch
import torch.nn as nn
from graphmae.utils import create_optimizer, accuracy
from graphmae.models.gat import GAT
from graphmae.models.gin import GIN
from graphmae.models.gcn import GCN
from graphmae.models.dot_gat import DotGAT
from graphmae.models.gcnii import GCNII
impo... |
5e31430f491a8914a81f802039f9dfa3c1b13ed338f14652b20f94b491802a4e | Python | 18,625 | 560 | from __future__ import annotations
import json
from pathlib import Path
from typing import Final
import pytest
from labelme import _config
from labelme._config._migration import migrate_config
def _steer_home(*, monkeypatch: pytest.MonkeyPatch, home: Path) -> None:
monkeypatch.setenv("HOME", str(home))
# n... |
a9e410a9c8b0bab87baf662d861a1424b2cbaff3e469dc8007d66cc0ce2905ec | Python | 18,647 | 450 | """TensorFlow implementation of fully connected networks.
"""
from __future__ import print_function
from __future__ import division
from __future__ import unicode_literals
import logging
import warnings
import time
import numpy as np
import tensorflow as tf
import threading
import collections
import pdb
import deepch... |
34751a6a9abe609e53aa19f93fd1563b95c611fa8c43bc0bbd0350c30fc4df61 | Python | 18,654 | 455 | import os
import numpy as np
import pytest
from absl.testing import parameterized
from keras.src import backend
from keras.src import layers
from keras.src import models
from keras.src import ops
from keras.src import saving
from keras.src import testing
from keras.src.backend.common import AutocastScope
from keras.s... |
c188a3c62e762f1786f697852754ce896931f3fc0f4e2b4a89bca931036a9b34 | Python | 18,654 | 558 | #!/usr/bin/env python
# how to use this function...
# PYTHONPATH=lib python lib/galaxy/model/dataset_collections/types/semantics.py
import argparse
import ast
import os
import re
import sys
from io import StringIO
from typing import (
Annotated,
Any,
Literal,
NamedTuple,
)
import yaml
from pydantic im... |
af151b3f24aad550f0485711b0ec9f78990b84928c321a8e1617f6adcc9bc5a3 | Python | 18,657 | 326 | from __future__ import print_function, division
import os
import sys
import torch
import warnings
import numpy as np
import subprocess
from torch.autograd import Variable
from models import CompFCNNTarCNNModuleInception, CompFCNNTarCNN4Layers, CompFCNNTarCNNModule2Layers, CompFCNNTarCNN4LayersStride, get_model
from eva... |
1c0d0ecf6e2b68d48f2446ec02af79268d9e8cf8591e7257e0af092ed7d9f60a | Python | 18,658 | 526 | # This file helps to compute a version number in source trees obtained from
# git-archive tarball (such as those provided by githubs download-from-tag
# feature). Distribution tarballs (built by setup.py sdist) and build
# directories (produced by setup.py build) will contain a much shorter file
# that just contains th... |
16223aa1b75c36c7294dd8d5b9c55019521f2829e19567a448763967bb05fdbc | Python | 18,665 | 597 | """
Classes that build the larvaworld CLI argument parser.
Parser arguments are derived automatically from the canonical
:class:`param.Parameterized` configuration classes (or from registry parameter
dictionaries), so that the CLI surface stays in sync with the underlying
parameter definitions instead of duplicating t... |
34a9a6ecc6d53e80e880fde614931b20d98e5e642aba29106943b3e26595df51 | Python | 18,668 | 477 | import inspect
import os
import pickle
import numpy as np
import pytest
from absl.testing import parameterized
from keras.src import backend
from keras.src import constraints
from keras.src import layers
from keras.src import models
from keras.src import optimizers
from keras.src import testing
from keras.src.api_exp... |
e13796e44261243988ce9b5231636bb3a945f69c12e9234426f93766e2a062f2 | Python | 18,668 | 427 | """Keras base class for convolution layers."""
from keras.src import activations
from keras.src import constraints
from keras.src import initializers
from keras.src import ops
from keras.src import regularizers
from keras.src.backend import standardize_data_format
from keras.src.layers.input_spec import InputSpec
from... |
f74c66ade6eef79f01f55c6f6c6d14bec45d18892411ad93705fbd377f5917a0 | Python | 18,676 | 405 | import argparse
from loader import MoleculeDataset, load_data
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from sklearn import metrics
from sklearn.metrics import roc_auc_score,accuracy_score,precision_score,recall_score,precision_recall_curve,f1_score
from skle... |
b4f6acc962219dbe8853c27129d5d3ef3a9955936ede727db7fbe7f10c7fc449 | Python | 18,687 | 584 |
"""Data type definitions.
This module provides the basic data types for Wyrm, like the
:class:`Data` and :class:`RingBuffer` classes.
"""
import copy
import logging
import numpy as np
from wyrm.processing import append_cnt
logging.basicConfig(level=logging.NOTSET)
logger = logging.getLogger(__name__)
class... |
af6ae4b680cd39cad0505f12f0c251910a81478b6d15d4f253ec0577759f64fa | Python | 18,699 | 361 | # !/usr/bin/env python
## created by Yun Hao @MooreLab 2021
## This script contains functions used for implementing LRP to evaluate relevance of DTox paths
## Module
import numpy as np
import pandas as pd
import torch
from functools import reduce
from operator import concat
from statsmodels.sandbox.stats.multicom... |
ef880f928b6297fa4d964fe425c97cd72e3fa589bba722d813b9cb6b4c651b05 | Python | 18,701 | 446 | import contextlib
import streamlit as st
import pandas as pd
import plotly.express as px
import http
import urllib
import re
import statsmodels.api as sm
import holoviews as hv
from holoviews import opts, dim
import requests
import duckdb
hv.extension('bokeh', logo=False) #draw interactive visualization using holoview... |
55e94cc8f56020951fea7d8a5c99530a673df832190646ccb650cfa6f76857a0 | Python | 18,704 | 653 | # Natural Language Toolkit: TextGrid analysis
#
# Copyright (C) 2001-2011 NLTK Project
# Author: Margaret Mitchell <itallow@gmail.com>
# Steven Bird <sb@csse.unimelb.edu.au> (revisions)
# URL: <http://www.nltk.org>
# For license information, see LICENSE.TXT
#
"""
Tools for reading TextGrid files, the format us... |
c60524fd92b9676b585d4cd41503e79593cd09d79238c7f54944a3ee87d4e02c | Python | 18,704 | 491 | #!/usr/bin/env python3
"""
Deterministic STEPS reaction-diffusion simulation with volume-matched
calcium injection.
Last updated: 20.08.2026
Author: Laura Keto
Description
-----------
This script performs a deterministic three-dimensional calcium-calmodulin
reaction-diffusion simulation in STEPS using the TetODE solv... |
eaf22795af923f1db610ac0d7d7a6b657e6169bf5ab72a17b6caf9a94985dd72 | Python | 18,708 | 543 | """Dynamo / fake-mode boundary: graceful typed degradation, never a raw crash.
Tensors inside a ``torch.compile`` region are data-free ``FakeTensor``s. Every
TorchLens step that reads a value -- ``safe_copy``, ``torch.equal``, ``.item()``,
``data_ptr()``, memory accounting -- is meaningless or fatal on them, so before... |
62619aaf61ead8bf376c2a57f12c06978bdd62d9dafc4400c4b4d0efb9a2e0aa | Python | 18,710 | 383 | # -----------------------------------------------------------------------------
# Copyright (c) 2015, The Deblur Development Team.
#
# Distributed under the terms of the BSD 3-clause License.
#
# The full license is in the file LICENSE, distributed with this software.
# -------------------------------------------------... |
deef6424932f22e5e7806c2dd37ae1eb0b81592861cd7e6cf9c05ab9b293bae0 | Python | 18,727 | 372 | # Adapted from
import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
from torch.distributions import Categorical, Normal
@torch.jit.script
def soft_clamp(x: torch.Tensor):
return x.div(20.).tanh_()
@torch.jit.script
def soft_clamp_scale(x: torch.Tensor):
return x.div(20.).tanh_... |
96d110b4aaf44aa01a0a34418b797461aba319178410983b841ba57604d5d5dc | Python | 18,732 | 469 | """The composition ledger: one row schema, closed vocabularies, seed rows (row 0.8).
Compo memo 3.1: tests own verification policy through this importable ledger;
production owns product truth (operation ids, operation-grain backend
capabilities) which rows REFERENCE by id and never restate. Every declared
cell carrie... |
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