sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
aee345c2b91c62ab571fbabae3b4e7a7f2e56602e45f0b525c8d2bfb51809d09 | Python | 959 | 35 | import numpy
def rotate(matrix, degree):
if abs(degree) not in [0, 90, 180, 270, 360]:
print("raise error or just return nothing or original")
if degree == 0:
return matrix
elif degree > 0:
return rotate(zip(*matrix[::-1]), degree-90)
else:
return rotate(zip(... |
cc1c2c33afbd196e8830539452beb0df478965d51a3f10d4658fc9e06062d73b | Python | 959 | 32 | import pyclesperanto_prototype as cle
# list names of all available OpenCL-devices
print("Available OpenCL devices:" + str(cle.available_device_names()))
# list CPUs and GPUs separately
gpu_devices = cle.available_device_names(dev_type="gpu")
print("Available GPU OpenCL devices:" + str(gpu_devices))
cpu_devices = cl... |
e8f28dc19e5a1d81ae63617ac96265cbf2fddea7821d5b8277176de248eb7da3 | Python | 959 | 29 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# 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 applicab... |
fd6d4019cb13f40fca77d1a493c5ae7f8c4bf8903ce066083037b40a8193a7c3 | Python | 959 | 36 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Sep 20 11:46:14 2018
@author: Carlos A Ariza, PhD
"""
#Montage of images
# import the necessary packages
from imutils import build_montages
from imutils import paths
import pandas as pd
import cv2
cv_df = pd.read_csv('../data/cv_feat.csv', index_col... |
26ab6efc74db5a259c50642e189d1421bc446899913987fac7faf908b58aa926 | Python | 960 | 34 | """Standalone tissue-masking / background-removal GUI tool.
Reads a folder (or several folders) of stitched section TIFFs and
writes "cleaned" versions with non-tissue background zeroed out.
Method: shared brain mask computed from the brightest-coverage
channel via multi-Otsu (3 classes) + morphology, applied t... |
50be86db9d0c1e8fd4549632be4704724c098f6f0bdeb2599a7a6205b9377660 | Python | 960 | 36 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward import configs, suites
import common_setup
SEARCH_REVS = ["issue439-base", "issue439-v1"]
LIMITS = {"search_time": 1800}
SUITE = suites.suite_satisficing_with_ipc11()
configs_satisficing_core = configs.configs_satisficing_core()
CONFIGS = {}
for name in ... |
61595cebb0fbf65b74a36cbc9e5def0a879f15c2d454af688c1bf3fa4856bc3b | Python | 960 | 27 | from typing import Optional
import yacs.config
from pytorch_image_classification import get_default_config
from pytorch_image_classification.config.config_node import ConfigNode
def find_config_diff(
config: yacs.config.CfgNode) -> Optional[yacs.config.CfgNode]:
def _find_diff(node: yacs.config.CfgNode,... |
68693ad7543279e06beb9d2a96acacb0fa996e3dc95867d93a8778d804e78f57 | Python | 960 | 28 | import numpy as np
import nibabel as nib
import argparse
import scipy.ndimage as ndimage
def convert_file(inname, outname):
img = nib.load(inname)
header = img.header
img_data = img.get_fdata()
iso_voxels = np.min(header.get_zooms())
zoom_ratio = tuple(np.array(header.get_zooms()) / iso_voxels)
... |
6ac4ba72711f1b4d3691db6261d585b26ed9e38bc3eabb41a9f90646a530f9ac | Python | 960 | 46 | import meep as mp
from meep import mpb
# Compute the bands at the X point for a quarter-wave stack Bragg
# mirror (this is the point that defines the band gap edges).
# the high and low indices:
n_lo = 1.0
n_hi = 3.0
w_hi = n_lo / (n_hi + n_lo) # a quarter_wave stack
geometry_lattice = mp.Lattice(size=mp.Vector3(1... |
8ce76ce7264aa7a7765c2b48b1db388135f23ca304afce0334ce0c58f6818f35 | Python | 960 | 41 | # external
import pytest
# project
import textdistance
ALG = textdistance.LCSSeq
@pytest.mark.parametrize('left, right, expected', [
('ab', 'cd', ''),
('abcd', 'abcd', 'abcd'),
('test', 'text', 'tet'),
('thisisatest', 'testing123testing', 'tsitest'),
('DIXON', 'DICKSONX', 'DION'),
('random... |
b917e8b57994230e913748d26452d755149c1e7709af02c90e6089a7e7d4487f | Python | 960 | 29 | import cv2
import numpy as np
import torch
def label2rgb(alpha, img, mask):
labeled_img = cv2.addWeighted(decode_segmap(mask).transpose(1, 2, 0).astype(int), alpha, img.astype(int), 1 - alpha,
0)
return torch.from_numpy(labeled_img.transpose(2, 0, 1))
def decode_segmap(imag... |
d46900eac8dcc376774eea461d75bd9dad5514db51cc76f63280676a79ed30a1 | Python | 960 | 32 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# 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 applicab... |
95921fbc33c90e62dd37b24e8e715c32d7542ab959f15313348461b1dc20cca7 | Python | 961 | 14 | from ..utils import format_channel_location_dict
STROKEPATIENTSMI_CHANNEL_LIST = ['FP1', 'FP2', 'Fz', 'F3', 'F4', 'F7', 'F8', 'FCz', 'FC3', 'FC4', 'FT7',
'FT8', 'Cz', 'C3', 'C4', 'T3', 'T4', 'CPz', 'CP3', 'CP4', 'TP7', 'TP8',
'Pz', 'P3', 'P4', 'T5',... |
a36210f6e1b384efc0c01f245f84e96b1df149a6ba0f2c1243e6808141c08f51 | Python | 961 | 33 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# 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 applicab... |
aea24f388018435ba037ea96ba4f56a21dea8404c3eca73b7f0aa2ba5f81dd4d | Python | 961 | 36 | import argparse
import os
import glob
from learning_experiment import LearningExp
parser = argparse.ArgumentParser()
parser.add_argument('path', help="Path to directory with learning experiment log files")
args = parser.parse_args()
files = glob.glob(os.path.join(args.path, '*_log.txt'))
for file in files:
... |
1481525023188270cc73139f1936ad2e590cae01f1a63f74bc8861a0411084da | Python | 962 | 40 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, MaiaEnvironment
from downward import suites
from common_setup import IssueConfig, IssueExperiment, is_test_run
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue701-base", "issue701-v1"]
CON... |
162101836c9866eea28279e96658d56126b9648c541494f87a57bdb32004b8bc | Python | 962 | 24 | import json, os
from regtools.registration.report import _render_methods, _render_reproduce, _render_manifest
def test_methods_paragraph_mentions_atlas_and_method():
meta = {"atlas": "allen_ccf_25um", "registration_method": "ants", "random_seed": 42, "has_laplacian": True}
html = _render_methods(meta, "... |
7482989fbee19260e737b762a953eb17aaf6678d82a0eab7c529d3edce8c6952 | Python | 962 | 32 | from __future__ import annotations
import pytest
pytest.importorskip("phonopy")
pytest.importorskip("seekpath")
import numpy as np
from ase.build import bulk
from numpy.testing import assert_almost_equal, assert_array_equal
from quacc.atoms.phonons import get_phonopy
def test_get_phonopy():
atoms = bulk("Cu")... |
ae73db9619462a7b7ebffd2fe22053eedcd257b3d4617f96f80a18b39183b17d | Python | 962 | 37 | """Provide a convenient way to link to GitHub issues and pull requests.
Link to any issue or PR using :gh:`issue-or-pr-number`.
Adapted from:
https://doughellmann.com/blog/2010/05/09/defining-custom-roles-in-sphinx/
"""
# Authors: The PyPREP developers
# SPDX-License-Identifier: MIT
from docutils.nodes import refe... |
9039a7f19839f4c0eb569177095259276d60034b807b4277d1fd4d524497e9a2 | Python | 963 | 33 | """
PREPROCESS FUNCTIONS
These functions preprocess the data used by the algorithm based on user-set preferences.
"""
def preprocess(self):
if self.DO_DIV:
divide(self)
elif self.DEBUG:
print("\nDividing is not enabled!\n")
if self.USE_LESS:
reduce(self)
elif self.DEBUG:
... |
0f466dccdd1063d4c739caaa641f907c1e4f1ce52def23e635665006fff521e2 | Python | 965 | 27 | """Testing plot function for unrolled sequences."""
import matplotlib as mpl
import numpy as np
from pypulseq import Sequence
from console.interfaces.acquisition_parameter import AcquisitionParameter
from console.interfaces.unrolled_sequence import UnrolledSequence
from console.pulseq_interpreter.sequence_provider imp... |
cb334e6f434fc8f608f6f192361f8f6e1f97fde93141ec55754c7e6ac5ed50b8 | Python | 965 | 29 | # coding: utf-8
from . import _init_paths
import numpy as np
import Sim3DR_Cython
def get_normal(vertices, triangles):
normal = np.zeros_like(vertices, dtype=np.float32)
Sim3DR_Cython.get_normal(normal, vertices, triangles, vertices.shape[0], triangles.shape[0])
return normal
def rasterize(vertices, tr... |
dcd5271a3495f50d8da8fa149a46cdb2b8138515610422a078c339d9894dd04b | Python | 965 | 28 | from tensorflow.keras import layers
from tensorflow.keras.models import Model
from tensorflow.keras.applications import ResNet50V2
def resnet_model(num_classes, input_shape):
inputs = layers.Input(input_shape)
base_model = ResNet50V2(include_top = False, weights='imagenet', pooling='avg', input_tensor=inp... |
5b0c4a8928ba246ec5a7ea2a73faa64693d840d0bb99806064c31e038dc43567 | Python | 966 | 27 | import pandas as pd
import numpy as np
from pyfaidx import Fasta
import argparse
import vcf as pyvcf
from pyensembl import Genome
import tqdm
import os
from sptransformer import Annotator
import torch
if __name__ == '__main__':
annotator = Annotator()
gtf = annotator.gtf
tis_names = ['Adipose Tissue', 'Bl... |
f75551bcb392926f17c70d96ca720f9366365761479c2ee81b158a2ecd014f48 | Python | 966 | 38 | # Save neuron positions in motor cortical macrocolumn model
from os.path import join
import sys
dir_data = join("..", "data")
dir_model_parameters = "settings_2013_31_120RMT"
sys.path.append(dir_model_parameters)
from net_esser import net_esser
import settings_main
import pickle
# Initialize dummy delay_... |
47c2a12570e95509d300a614637ccdcdd1cdc9b05be7ff35b60a10a7558d972c | Python | 967 | 25 | """"""
"""
Prosper_nn provides implementations for specialized time series forecasting
neural networks and related utility functions.
Copyright (C) 2022 Nico Beck, Julia Schemm, Henning Frechen, Jacob Fidorra,
Denni Schmidt, Sai Kiran Srivatsav Gollapalli
This file is part of Propser_nn.
Propser_nn is free softw... |
a95628f1dc48125f9bbe9f949121f8654226513be560c1aaf73c045377813140 | Python | 967 | 25 | """"""
"""
Prosper_nn provides implementations for specialized time series forecasting
neural networks and related utility functions.
Copyright (C) 2022 Nico Beck, Julia Schemm, Henning Frechen, Jacob Fidorra,
Denni Schmidt, Sai Kiran Srivatsav Gollapalli
This file is part of Propser_nn.
Propser_nn is free softw... |
ae29a659cc85f1aad64b6f47a1cae3eb355eced5b2802e7e6a3ddc75c1f51ec7 | Python | 967 | 53 | from .config import (
PlotConfig,
)
from .morphospace import (
compute_umap_from_pca,
plot_morphology_states,
)
from .categories import (
plot_category_states,
)
from .composition import (
build_composition_tables,
plot_category_composition,
)
from .profiles import (
build_morphometric_p... |
eb387c2c1c5e10048e956d656c52dae7803ea0b0c08a4e075fda2bf86dddaad3 | Python | 967 | 32 | from pathlib import Path
import bpy
from . import data
from .template import install, uninstall
ASSET_DIR = Path(__file__).resolve().parent
# The shipped asset library, built from the sources in molecularnodes/nodes/
# (python -m nodebpy.assets build). Not tracked in git — see resources.blend
# for the data-only datab... |
53b1583e1de8189349a352495f95eca7cf218ef0edc8e01b478d3f7b8b46f73d | Python | 968 | 43 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
test_pymrmr
----------------------------------
Tests for `pymrmr` module.
"""
import io
import pandas as pd
import requests as rq
import sys
import unittest
from pymrmr import mRMR
class TestPymrmr(unittest.TestCase):
def setUp(self):
data_url = 'http://h... |
63469a55fc43997c84bfacba953ada80cb5cb87397e71c6be184a185c3474b60 | Python | 968 | 37 | #!/bin/env python3
'''
Apply a chain reactions for the quasi-particles in the 2D patterns of cardiac
arrhythmia
'''
import yaml
from pdlfeynman.particle import *
from pdlfeynman.reaction import *
from pdlfeynman.pool import ParticlePool
from pdlfeynman.history import ReactionHistory
# applying a list of reactions...
... |
7064f559d7c2eae9ca7fa7ac6523bbda914d7b3a9c5b569697b696e8580236e4 | Python | 968 | 25 | """"""
"""
Prosper_nn provides implementations for specialized time series forecasting
neural networks and related utility functions.
Copyright (C) 2022 Nico Beck, Julia Schemm, Henning Frechen, Jacob Fidorra,
Denni Schmidt, Sai Kiran Srivatsav Gollapalli
This file is part of Propser_nn.
Propser_nn is free softw... |
c3546da5541a81a7944da4d88b84aa8a6be05d51bf36d1d680543a05573868d5 | Python | 968 | 25 | """"""
"""
Prosper_nn provides implementations for specialized time series forecasting
neural networks and related utility functions.
Copyright (C) 2022 Nico Beck, Julia Schemm, Henning Frechen, Jacob Fidorra,
Denni Schmidt, Sai Kiran Srivatsav Gollapalli
This file is part of Propser_nn.
Propser_nn is free softw... |
cb019871549a49ff8ff6211eb57d52872a823a81ad7ced96101ffbcf39b5cc6f | Python | 968 | 30 | import torch
import torch.nn as nn
import torch.nn.functional as F
class ConvBlock(nn.Module):
"""
Basic convolutional block.
Consists of a convolutional layer, a max pooling layer and a dropout layer.
"""
def __init__(
self,
in_channels: int,
out_channels: int,
... |
f7baac74c4004f1b78b859ad1881c79951f3b7af3b7d0ca176124be74eef160f | Python | 968 | 27 | # Copyright (c) OpenMMLab. All rights reserved.
import logging
from mmcv.utils import get_logger
def get_root_logger(log_file=None, log_level=logging.INFO):
"""Get the root logger.
The logger will be initialized if it has not been initialized. By default a
StreamHandler will be added. If `log_file` is s... |
0fc5d6ec7326ba33f063fe2f8187165a0acc324c56f089f0667c128b7be324b5 | Python | 969 | 32 | import argparse
import pandas as pd
from measures import form2meaning_ratio
def main():
"""TODO: Docstring for main.
:returns: TODO
"""
parser = argparse.ArgumentParser()
parser.add_argument("input_languages_path")
args = parser.parse_args()
# Ambiguity measures: 1 - ( #num_unique_mess... |
0933486f8c0aa86bba38872cb460dc5fa99b7fd39e71856dc595bde36afa481e | Python | 970 | 25 | """"""
"""
Prosper_nn provides implementations for specialized time series forecasting
neural networks and related utility functions.
Copyright (C) 2022 Nico Beck, Julia Schemm, Henning Frechen, Jacob Fidorra,
Denni Schmidt, Sai Kiran Srivatsav Gollapalli
This file is part of Propser_nn.
Propser_nn is free softw... |
85c1e976ff3f4ac21893cf98bfc161da25894be18e3b84e5f5f9ec2101f6d356 | Python | 970 | 42 | #!/usr/bin/env python
import sys, subprocess, re
import matplotlib.pyplot as plt
INFILE = sys.argv[1]
OUTFILE = 'contact_map.png'
if len(sys.argv) > 2 : OUTFILE = sys.argv[1]
x = []
y = []
cnts = []
nres = 0
for line in open(INFILE) :
if line.strip()[0] == '#' : continue
tokens = re.split("\s+",line.strip(... |
99f1ea821a96a7781be0c4cdecd93584c42389c4f82c1509ec6157b07246fc07 | Python | 970 | 35 | import scipy.stats
import autograd.numpy as np
from autograd.extend import defvjp, primitive
from autograd.numpy.numpy_vjps import unbroadcast_f
from autograd.scipy.special import gamma, psi
cdf = primitive(scipy.stats.gamma.cdf)
logpdf = primitive(scipy.stats.gamma.logpdf)
pdf = primitive(scipy.stats.gamma.pdf)
de... |
68a227c0b9b97321ed5624bd43da302ab9dddaa47ace951e0784b791f4d925cb | Python | 971 | 25 | """"""
"""
Prosper_nn provides implementations for specialized time series forecasting
neural networks and related utility functions.
Copyright (C) 2022 Nico Beck, Julia Schemm, Henning Frechen, Jacob Fidorra,
Denni Schmidt, Sai Kiran Srivatsav Gollapalli
This file is part of Propser_nn.
Propser_nn is free softw... |
6b227027833f182347b7121124e4aac5602ff5380b5310dc4fd1ceb1507ed251 | Python | 971 | 36 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
from lab.experiment import Experiment
from lab.steps import Step
from downward.reports.compare import CompareConfigsReport
from common_setup import get_experiment_name, get_data_dir, get_repo_base
import os
DATADIR = os.path.join(os.path.dirname(__file__), 'data')
exp ... |
c927cc3d8ecbb9ae8d88fcc647bc2a8d9adb2a21ae5138162e2ec6f323415c92 | Python | 971 | 24 | from REACTRL.img_modules.img_data import train_loader, test_loader
from REACTRL.env_modules.net_framework import *
from REACTRL.env_modules.img_conv import *
from boss.bo.bo_main import BOMain
from boss.pp.pp_main import PPMain
from datetime import datetime
import pandas as pd
def func(X, model=None, method='resnet18'... |
f331c4406d13077aec594ff3eda144375a401ce96765ea66a579ff8a94ec8433 | Python | 971 | 26 | """
Modified by Mayank Kabra
Original by DeepLabCut2.0 Toolbox (deeplabcut.org)
copyright A. & M. Mathis Labs
https://github.com/AlexEMG/DeepLabCut
Please see AUTHORS for contributors.
https://github.com/AlexEMG/DeepLabCut/blob/master/AUTHORS
Licensed under GNU Lesser General Public License v3.0
"""
from deeplabcut ... |
6a7eaea2ec2128f025bd0858a4d3691aaf44272b1f3083afbc26cede84a8476e | Python | 972 | 37 | import os
import platform
from pip._vendor.rich import inspect
from pip._vendor.rich.console import Console, get_windows_console_features
from pip._vendor.rich.panel import Panel
from pip._vendor.rich.pretty import Pretty
def report() -> None: # pragma: no cover
"""Print a report to the terminal with debugging ... |
2bc3f001179c6b84644e8f157548c400b50de0ed019e0084e4d8b21fc595cfa2 | Python | 974 | 33 | import unittest
import os
import random
import shutil
from torcheeg.model_selection import KFold
from torcheeg.datasets import DEAPDataset
class TestKFold(unittest.TestCase):
def setUp(self):
shutil.rmtree('./tmp_out/')
os.mkdir('./tmp_out/')
def test_k_fold(self):
io_path = f'./tmp_... |
6e47f3ba83f495361904e0af4230690687d4fe042c16f068a0c679d5c0328141 | Python | 974 | 25 | """"""
"""
Prosper_nn provides implementations for specialized time series forecasting
neural networks and related utility functions.
Copyright (C) 2022 Nico Beck, Julia Schemm, Henning Frechen, Jacob Fidorra,
Denni Schmidt, Sai Kiran Srivatsav Gollapalli
This file is part of Propser_nn.
Propser_nn is free softw... |
7a609a809bf721bcfd0030dd8296e4d97e5b5d35eecfca957fcc406a1eb0ddee | Python | 974 | 25 | """"""
"""
Prosper_nn provides implementations for specialized time series forecasting
neural networks and related utility functions.
Copyright (C) 2022 Nico Beck, Julia Schemm, Henning Frechen, Jacob Fidorra,
Denni Schmidt, Sai Kiran Srivatsav Gollapalli
This file is part of Propser_nn.
Propser_nn is free softw... |
924328500c901ac167b10f3470c6ccc9ef227f1ffe0317ddc555e357b03783a9 | Python | 974 | 33 | # from jax.scipy.special import logsumexp
from netket.vqs import MCState, expect, expect_and_forces
from flax.core.scope import CollectionFilter, DenyList # noqa: F401
from .operator import InfidelityOperatorUPsi
from tre_tvmc.driver.utils import calc_full_chunk_size
@expect.dispatch
def infidelity(vstate: MCState... |
825a0554d411aacf13bbe18f0a0cf353f464251e9f44c22f9d47ebda15742260 | Python | 975 | 25 | """"""
"""
Prosper_nn provides implementations for specialized time series forecasting
neural networks and related utility functions.
Copyright (C) 2022 Nico Beck, Julia Schemm, Henning Frechen, Jacob Fidorra,
Denni Schmidt, Sai Kiran Srivatsav Gollapalli
This file is part of Propser_nn.
Propser_nn is free softw... |
a66942375ce684a2d0185fcce5e10361b63c6a72ecc901ca6d88a04cf7d13e20 | Python | 975 | 33 | import os
import warnings
import argparse
from yacs.config import CfgNode
from .default import get_cfg_defaults
# thanks Jack yet again :)
def load_cfg(config_file=None, freeze=True, add_cfg_func=None):
"""Load configurations
"""
cfg = get_cfg_defaults()
if add_cfg_func is not None:
add_cfg_fu... |
2c255d6370bc9987ab3837050506388bd8dbf9faad9de69e75edd7b2ce09474c | Python | 976 | 28 | """Evaluators for survival predictions and model-specific prediction formats."""
from .competing_risks_evaluator import CompetingRisksEvaluator
from .interval_cen_evaluator import IntervalCenEvaluator
from .lifelines_evaluator import LifelinesEvaluator
from .multi_state_evaluator import MultiStateEvaluator
from .point... |
886347d55938144d726901bcefbe4a2752ac9b194a0f0f51078add03034165f5 | Python | 976 | 27 | import argparse
import glob
import re
import os
def main():
parser = argparse.ArgumentParser(description='Rename files in a time series by a specific offset.')
parser.add_argument('--source', type=str, help='Path to the source files', required=True)
parser.add_argument('--offset', type=int, help='Offset ... |
90fc87396ce07a1a525e77a597b3840ec19ed4e6818d46c89715a740782dc604 | Python | 976 | 37 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward import suites
import common_setup
REVS = ["issue527-v2"]
SUITE = suites.suite_optimal_with_ipc11()
CONFIGS = {
"astar_occ_lmcut": [
"--search",
"astar(operatorcounting([lmcut_constraints()]))"],
"astar_occ_seq": [
"--search... |
020e21b6eeebeae94efb637d729d6d75e67181a24e805098d2605756c95c4871 | Python | 977 | 30 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# 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 applicab... |
2c41ad5c2dc04605e884238e0171277f671aea31e107652294320a6da86f1340 | Python | 977 | 27 | from typing import Callable, Tuple
import torch.nn as nn
import yacs.config
from .cutmix import CutMixLoss
from .mixup import MixupLoss
from .ricap import RICAPLoss
from .dual_cutout import DualCutoutLoss
from .label_smoothing import LabelSmoothingLoss
def create_loss(config: yacs.config.CfgNode) -> Tuple[Callable,... |
abce3f8e4cda32c52bdc3d2443305cd030c36ff70cc2feca2ca725f05dcf7c75 | Python | 977 | 25 | import os
import pandas as pd
import unittest
import sys
sys.path.append(os.path.dirname(os.path.realpath(__file__)) + "/../../src")
from hornet.uml import create_features
class TestCreateFeatures(unittest.TestCase):
def test_create_features_creation(self):
# Test case 1: Check if 'afmccpow' column is... |
cb2e9d585c37d080db83d23285503d02b2d01e68a8651434cd678cc207583674 | Python | 977 | 24 | from REACTRL.img_modules.img_data_2_messy import train_loader, test_loader
from REACTRL.env_modules.net_framework import *
from REACTRL.env_modules.img_conv import *
from boss.bo.bo_main import BOMain
from boss.pp.pp_main import PPMain
from datetime import datetime
import pandas as pd
def func(X, model=None, method='r... |
04303a8bd9469ca46b0092481b4d3f7d0f6f4cd5647316fe9dc531f7738e6a62 | Python | 978 | 33 | probe_map = {'208175_s_at':'DMP1',
'221150_at':'MEPE',
'221166_at':'FGF23',
'223869_at':'SOST',
'204879_at':'PDPN',
'208233_at':'PDPN',
'221898_at':'PDPN',
'226658_at':'PDPN',
'202310_s_at':'COL1A1',
'202311_s_at':'COL1A1',
'1556499_s_at':'... |
ce2b6710b3e140cf1bdce4b02f7de16cc6f69d41ee6cbd7b999eab3e49f31f8d | Python | 978 | 37 | import boto.sqs
from boto.sqs.message import Message
import preprocessing
import time
import json
import os
import sys
def get_connection():
secrets_subpath = ".cloudvolume/secrets/aws-secret.json"
secret_path = os.path.join(os.path.expanduser('~'), secrets_subpath)
with open(secret_path) as f:
aws_secrets... |
f90b104d274b5ff16033e18aad0cafbe61da2c1a625c21e9561094e3bf1db3a0 | Python | 978 | 35 | #!/usr/bin/env python
from __future__ import print_function
import os
results = {}
version_files = [x for x in os.listdir(".") if x.endswith(".version.txt")]
for version_file in version_files:
software = version_file.replace(".version.txt", "")
if software == "pipeline":
software = "nf-core/rts"
w... |
301b46a67504e5a33ab458cddd289bda7107f5183ef27a5d1d030c175620b554 | Python | 979 | 36 | from collections.abc import Callable
from typing import Protocol
class DummyLowerable(Protocol):
more_data: list[str]
class Translator(Protocol):
def register(self, name: str, fn: Callable) -> Callable: ...
class CallablePluginSymbol:
def __init__(self, fn: Callable[[DummyLowerable], str]):
se... |
3348c149ebcda853e4da8062eb804ddd1b2e047044fac44e6bc8b7a6a79b82dc | Python | 979 | 33 | # Copyright (c) OpenMMLab. All rights reserved.
from abc import ABCMeta, abstractmethod
from mmcv.runner import BaseModule
ON_APU = False
FIT = False
class BaseBackbone(BaseModule, metaclass=ABCMeta):
"""Base backbone.
This class defines the basic functions of a backbone. Any backbone that
inherits this c... |
3ffcc1345934cd43d988b3fbfee49ebb47d273e61381af5283c0961a8913a53c | Python | 979 | 24 | from REACTRL.img_modules.img_data_2_class import train_loader, test_loader
from REACTRL.env_modules.net_framework import *
from REACTRL.env_modules.img_conv import *
from boss.bo.bo_main import BOMain
from boss.pp.pp_main import PPMain
from datetime import datetime
import pandas as pd
def func(X, model=None, method='r... |
7d28f652b9e353faf6fbada785dad50835025f0655bab43e85e80dbab26353e7 | Python | 979 | 24 | from PIL import ImageDraw
from typing import Optional
from .shape import Shape, calculate_short_side
class Cross(Shape):
def draw(self, draw: ImageDraw.Draw, color: tuple[int, int, int]):
x_vertical = self.x + self.width // 4
y_vertical = self.y
x_horizontal = self.x
y_horizontal =... |
929ee8dddcb99f2bd1d4957d0149cefb79056b5df9e21129d80cbb7283712c42 | Python | 979 | 24 | from REACTRL.img_modules.img_data_2_target import train_loader, test_loader
from REACTRL.env_modules.net_framework import *
from REACTRL.env_modules.img_conv import *
from boss.bo.bo_main import BOMain
from boss.pp.pp_main import PPMain
from datetime import datetime
import pandas as pd
def func(X, model=None, method='... |
9ec0b9d78d8ec6efb7ba089a9aa3a39696903ae8987b95ec1c94b8ca7b7ca97f | Python | 979 | 24 | from REACTRL.img_modules.img_data_3_class import train_loader, test_loader
from REACTRL.env_modules.net_framework import *
from REACTRL.env_modules.img_conv import *
from boss.bo.bo_main import BOMain
from boss.pp.pp_main import PPMain
from datetime import datetime
import pandas as pd
def func(X, model=None, method='r... |
34b72890421a40fd1d0e1cf52ee825d1457281627bc3a12ba3233f9b3d6b309b | Python | 980 | 31 | from queso.utils import *
import qutip as qt
# n = 6
# inds = list(kbits(n))
#
# lst = list(range(n))
# for s in inds:
# a = [lst[i] for i in range(n) if s[i] == 1]
# b = [lst[i] for i in range(n) if s[i] == 0]
# print(a, b)
# %%
n = 6
# rho = qt.ket2dm(qt.rand_ket(dims=[[2] * n, [1] * n]))
... |
7decb76bc87c0183bf7503dc8099aa38b0cc1cfd37269b6a4bf288ed2ba20564 | Python | 980 | 29 | #!/usr/bin/env python
"""
Automated Recognition and Classification of Histological layers.
Machine learning for histological annotation and quantification of cortical layers pipeline
"""
import importlib
from setuptools import find_packages, setup
spec = importlib.util.spec_from_file_location("layer_recognition.versi... |
acf57dc54bf799bbf14e3c69d50c971796ca1d8acf2dbb2f2d4a2b6ef496516b | Python | 980 | 25 | """"""
"""
Prosper_nn provides implementations for specialized time series forecasting
neural networks and related utility functions.
Copyright (C) 2022 Nico Beck, Julia Schemm, Henning Frechen, Jacob Fidorra,
Denni Schmidt, Sai Kiran Srivatsav Gollapalli
This file is part of Propser_nn.
Propser_nn is free softw... |
4596a8950d486f52796a51eb12a24b5199f8a7f329cc8f563e734b2d3ab2c4a7 | Python | 982 | 36 | from sys import exit
import os
import platform
#os.environ['KMP_DUPLICATE_LIB_OK']='True'
import json
from utils import *
import torch.nn as nn
import torch.optim as optim
from torch.utils.data import DataLoader, Dataset
import time
import tifffile
#from scipy.ndimage.morphology import binary_erosion #distance_trans... |
8a40d4d0493ba7861941d8710bafa72b6254a3eebcb63bbb309e9691d046e413 | Python | 982 | 32 | import torch
import torch.nn as nn
import math
class lap_ablation_none_module(torch.nn.Module):
def __init__(self, channels=None):
super(lap_ablation_none_module, self).__init__()
@staticmethod
def get_module_name():
return "lap_ablation_none"
def forward(self, x):
epsilon = ... |
c47fc07c6a12b83200117e87fa64afd3bca4adbf1857b1f270a8671beb8ea966 | Python | 982 | 21 | """
toposampling - Topology-assisted sampling and analysis of activity data
Copyright (C) 2020 Blue Brain Project / EPFL & University of Aberdeen
This program is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public License as
published by the Free Software Foundation... |
da7f4cc398c20c312c07d69d34c459161b30859228a7dbb90b47937cf474fae1 | Python | 982 | 28 | import zipfile
import os
import subprocess
def unzip_file(zip_file_path, extracted_folder_path):
# Open the zip file
with zipfile.ZipFile(zip_file_path, 'r') as zip_ref:
# Extract each file one by one
for file_info in zip_ref.infolist():
zip_ref.extract(file_info, extracted_folder_... |
25dfbfc307ce4702cbdad47049e5ad5f0b0e89b99e7834d5478076ddd5b80b9f | Python | 983 | 37 | import torch
from torch import nn
from torch.nn import functional as F
from inv_vae.utils.helpers import to_var
class GraphConv(nn.Linear):
'''
graph convolutional layers.
----
inputs:
----
outputs:
'''
def __init__(self, in_feat_dim, out_feat_dim, device, bias=True):
... |
36b629b038a8d393e6846ad9c4f4cbcb63bd1b8529db9a529c2a84e00270a9cb | Python | 984 | 44 | import os
import torch
from torch_geometric.data import InMemoryDataset
import pickle
def read_sets(fpath, fold, split_type='warm'):
filename = split_type + '.kfold'
print(f"Reading fold_{fold} from {fpath}")
with open(os.path.join(fpath, filename), 'rb') as f:
kfold = pickle.load(f)
return ... |
da7ae53253c898d30063bba3a73f433284989f98577ba5039ab92049a5ba7547 | Python | 984 | 22 | import torch.nn as nn
from torch_geometric.nn import GATv2Conv
class Spider(nn.Module):
def __init__(self, input_num_features, hid_units, n_heads, nb_classes, edge_dim, dropout=0.0, activation=nn.ELU()):
super(Spider, self).__init__()
self.activation = activation
self.conv1 = GATv2Conv(inp... |
58c920bc993aaad601b10fafac96747668ef6a162ab6d752f266f66ebb966ed2 | Python | 985 | 32 | import os
os.environ.setdefault("QT_QPA_PLATFORM", "offscreen")
import pytest
pytest.importorskip("pyqtgraph")
@pytest.fixture(scope="module")
def qapp():
from PySide6.QtWidgets import QApplication
return QApplication.instance() or QApplication([])
def test_batch_tab_has_atlas_edit_pane_an... |
dd20b82505c9b8aa437194fd0a38a69d188e57a88dd7c3a2fbd78145d81c0303 | Python | 985 | 38 | """SWC data format defintion and services."""
import json
import numpy as np
class SWC(): # pylint: disable=too-few-public-methods
"""Definitions of the data format."""
TYPES = (SOMA, AXON, DEND, APIC) = range(1, 5)
COLS = (I, T, X, Y, Z, R, P) = range(7)
XY = slice(2, 4)
XZ = slice(2, 5, 2)
... |
f9ae0a96c389d310bdb37b0f903e4eaf486dc9824015d78b486f0e8614ff885e | Python | 985 | 31 | from __future__ import annotations
from importlib.util import find_spec
from pathlib import Path
from shutil import rmtree
import pytest
TEST_RESULTS_DIR = Path(__file__).parent / "_test_results"
TEST_SCRATCH_DIR = Path(__file__).parent / "_test_scratch"
has_prefect = bool(find_spec("prefect"))
if has_prefect:
i... |
4c90a338772e266e1e57b739727c9481de9c0003124e25782f21632513ea82c5 | Python | 986 | 34 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# 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 applicab... |
785daf3b82e9386a0fbc828a91b3df9f2badf214f852279b64fa5bf8160641d2 | Python | 986 | 43 | """
pygments.modeline
~~~~~~~~~~~~~~~~~
A simple modeline parser (based on pymodeline).
:copyright: Copyright 2006-2023 by the Pygments team, see AUTHORS.
:license: BSD, see LICENSE for details.
"""
import re
__all__ = ['get_filetype_from_buffer']
modeline_re = re.compile(r'''
(?: vi | vim... |
e45bbf26dfc35b3cc4c11fa89a3580b4516c2d9b08fd5857384c07cbe757ffc6 | Python | 986 | 35 | """Module contains all the exceptions
"""
class UnrecognizedFormat(Exception):
"""Could not recognize the format of the file for channels.
"""
def __init__(self, value):
self.value = value
def __str__(self):
return repr(self.value)
class MissingDependency():
"""Class to handle ... |
728c08d0f013c1a5e082bd6f57aeffcaed994cf22f2ff5596377502ad4725a82 | Python | 987 | 32 | import pytest
import elasticai.creator.nn.fixed_point as nn_creator
from elasticai.creator.arithmetic import FxpArithmetic, FxpParams
from tests.integration_tests.nn.fixed_point.precomputed_routine import (
routine_testing_precomputed_module,
)
@pytest.mark.ghdl
@pytest.mark.parametrize(
"total_bits, frac_bi... |
d9e573ef8c0ca4331edcae5b49fb5da67b1629b7c3a7b98d7226f062fe1c4414 | Python | 987 | 25 | import torch
import torch.nn as nn
import torch.nn.functional as F
def soft_dice_loss(logits, targets, smooth=1.0): # targets is one hot
probs = logits.softmax(dim=1)
n_classes = logits.shape[1]
loss = 0
for i_class in range(n_classes):
if targets[:,i_class].sum()>0:
loss += dice_lo... |
65d8d2af3c643f18547c2c313bf4bbfeaa46409af8c0664c514ab4d777c3dc7d | Python | 988 | 42 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward.suites import suite_optimal_with_ipc11
from downward.configs import default_configs_optimal
import common_setup
REVS = ["issue387-base", "issue387-v1"]
CONFIGS = default_configs_optimal()
# remove config that is disabled in this branch
del CONFIGS['astar... |
9ce0206faa30dbff2bb5dedfa44f73cf124ba94eb2a2db405a0ae05ea84c01a4 | Python | 988 | 42 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward.suites import suite_optimal_with_ipc11
from downward.configs import default_configs_optimal
import common_setup
REVS = ["issue386-base", "issue386-v2"]
CONFIGS = default_configs_optimal()
# remove config that is disabled in this branch
del CONFIGS['astar... |
b5ae7749ce21ed4968ffbfd51737d949872e34f559630e6bc103a0d2eeb7cca7 | Python | 988 | 34 | # Copyright (c) OpenMMLab. All rights reserved.
import mmcv
from .version import __version__, version_info
try:
from mmcv.utils import digit_version
except ImportError:
def digit_version(version_str):
digit_ver = []
for x in version_str.split('.'):
if x.isdigit():
... |
d034eae9f8d50d75113e1d5e6fb25d515e402f8997f5b1b21e91703a3f4e1f53 | Python | 988 | 42 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward.suites import suite_optimal_with_ipc11
from downward.configs import default_configs_optimal
import common_setup
REVS = ["issue386-base", "issue386-v3"]
CONFIGS = default_configs_optimal()
# remove config that is disabled in this branch
del CONFIGS['astar... |
cd7ee0a2ea43727d794d3f8d09c4c1eca65c03d74999e2291984388ec1b3e04e | Python | 989 | 30 | """Load nexus device configuration from file."""
import logging
from pathlib import Path
import yaml
from pydantic import ValidationError
from console.interfaces.device_configuration import NexusConfiguration, SystemLimits
log = logging.getLogger("Config")
def load_nexus_config(path: str | Path) -> NexusConfigurat... |
ea43e73c7115963b7a8d616d2e34edc50676bc236a67b5de61bf272a580b8d37 | Python | 989 | 30 | import MDAnalysis as mda
from molecularnodes.entities.molecule.imd import StreamingTrajectory
from .constants import data_dir
def _streaming_trajectory() -> StreamingTrajectory:
# a regular multi-frame universe stands in for an IMD stream, as `.next()`
# behaves the same and lets the test observe the reader's... |
52e2ae026b1651deeaaf1bc99704652393c67b3f33a4cb1f859ef5710d15e1d5 | Python | 990 | 33 | # -*- coding: utf-8 -*-
"""
adapted from addExchanges on Nov 23 2023
@author: meine
"""
import os
import sys
import cobra
from pandas import read_csv
from pathlib import Path
from reaction_class import Reaction
from variables import *
blank_model = cobra.Model("BiGG_exchanges")
compounds = read_csv(BIGG_COMPOUNDS, ... |
ea970006c691ec27c81e56c96ebdbf90c9152452ffcab6234f1e9255652708f4 | Python | 990 | 34 | from pip._vendor.packaging.version import parse as parse_version
from pip._internal.models.link import Link
from pip._internal.utils.models import KeyBasedCompareMixin
class InstallationCandidate(KeyBasedCompareMixin):
"""Represents a potential "candidate" for installation."""
__slots__ = ["name", "version"... |
520c178572d689c7006b66b258cbb820cb54d90d07dcf5aafd280d876a4ba6ee | Python | 991 | 32 | from gymnasium.envs.registration import register
from hippo.environments.w_maze import WmazeTasks, get_wmaze
from hippo.environments.action_perception import action_perception_loop
__all__ = ["get_wmaze", "action_perception_loop"]
def register_envs():
register(
id="MiniGrid-WMaze3-Task0-v0",
ent... |
66440635c86848cb08c4c0e1e0cac7c6b0a8977ff53f8c52e5b616d84b3e4564 | Python | 991 | 37 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Jul 20 17:45:42 2023
@author: felipe
"""
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.colors as colors
custom_map = colors.LinearSegmentedColormap.from_list("custom",["gray","yellow","orange","red"])
custom_map1 = colors.Linear... |
90ef7dd02d01f73829218ee4c3d9577ecab9ead0be4777559020625912ac8772 | Python | 991 | 37 | import boto.sqs
from boto.sqs.message import Message
import sys
import os
import json
def get_connection():
secrets_subpath = ".cloudvolume/secrets/aws-secret.json"
secret_path = os.path.join(os.path.expanduser('~'), secrets_subpath)
with open(secret_path) as f:
aws_secrets = json.load(f)
return boto.sqs.... |
a3c0a9bc76cb24d32ef353998c97c62956172584301eb15b84caa078a41074b1 | Python | 991 | 42 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward.suites import suite_optimal_with_ipc11
from downward.configs import default_configs_optimal
import common_setup
REVS = ["issue385-v3-base", "issue385-v3"]
CONFIGS = default_configs_optimal()
# remove config that is disabled in this branch
del CONFIGS['as... |
4581dc413fe25850fe942d93c4d3e1479b2d0472794c4194f25721a9e3fa16e0 | Python | 992 | 29 | from analyse import *
import subprocess
from jinja2 import Template
submission = Template("""#!/bin/bash
#PBS -W group_list=ku_10001 -A ku_10001
#PBS -N {{dirname}}_cluster
#PBS -m n
#PBS -l nodes=1:ppn=1:thinnode
#PBS -l mem=20gb
#PBS -l walltime=2:00:00
#PBS -e {{dirname}}_cluster_err
#PBS -o {{dirname}}_cluster_out... |
6c3fcf29bb53fc86369bf86581af1d9c4171c0aa5afb4d4fd874a6c4954bf6c4 | Python | 992 | 15 | #----------------------------------------------------------------------------------------------------------------------------
# Author: Brandon S Coventry CAP Lab Purdue University Weldon School of BME
# Date: 09/02/20
# Revision History: N/A
# Purpose: This is the setup file to get spiking reinforcement learni... |
709505c7b206599ce8ae8421e9b6b4317c82f100a9780bebd0347aa9e4e915e2 | Python | 992 | 31 | from Patient import PatientDataBase
# mods: gaussian, rectangle, noise, noise_gauss
mods = 'noise_gauss'
DATA_PATH_IN = "../../data/input_data"
DATA_PATH_OUT = "../data/output_data/" + mods
ct_data_out = "../data/output_data/png_org"
if __name__ == '__main__':
print('start initialization')
data_base = Patien... |
7a69563b8352b9c23ffd77f10d4d8002ad9454e683054e93c466c5bbba9e0b8b | Python | 992 | 31 | import os
os.environ.setdefault("QT_QPA_PLATFORM", "offscreen")
import numpy as np
import pytest
pytest.importorskip("PySide6")
import nibabel as nib
from PySide6.QtWidgets import QApplication
from regtools.ccf_boundary_editor.viewer import CCFContourViewer
_app = QApplication.instance() or QApplication([... |
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