sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
9d76afb7c8d905b9fc4ef403cc73e6d0d36ab98785338a31c4e22f6708daf795 | Python | 1,279 | 41 | from __future__ import annotations
import pytest
pytest.importorskip("psi4")
from ase.build import molecule
from quacc.recipes.psi4.core import static_job
def test_static(tmp_path, monkeypatch):
monkeypatch.chdir(tmp_path)
atoms = molecule("H2")
output = static_job(atoms, charge=0, spin_multiplicity=... |
6c7d638c4cc66ab24fca23520d6940ea1c0c2489f53946ba1263363426c2fbf5 | Python | 1,280 | 45 | """
Optuna example to demonstrate setting the maximum number of trials in
a shared database when multiple workers are used.
In this example, we optimize a simple quadratic function. We use multiple
script runs (workers) to demonstrate the use of max_trial_callbacks,
which allows the user to set a maximum number ... |
c4e631b39995defa407b3bd3774ad0342e704f78acc4af7000d056774af6556c | Python | 1,281 | 32 | #
# MIT License
#
# Copyright (c) 2022 GT4SD team
#
# 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, copy, modify, merge,... |
61e47429a7565f0fd985e0b536d006d6a5481243a04461dcdb7c7e62d196ecd5 | Python | 1,282 | 46 | """Legacy editable installation process, i.e. `setup.py develop`.
"""
import logging
from typing import Optional, Sequence
from pip._internal.build_env import BuildEnvironment
from pip._internal.utils.logging import indent_log
from pip._internal.utils.setuptools_build import make_setuptools_develop_args
from pip._inte... |
d5d07710dcd67d17c1a42f328b423a7a243d89740241428e8390ff9a467bedd2 | Python | 1,282 | 38 | from .autograd import get_autograd_func
from .module_quantization import (
QuantizeForwHTE,
QuantizeForwHTEBackwHTE,
QuantizeForwHTEBackwStochastic,
QuantizeForwStochastic,
QuantizeForwStochasticBackwStochastic,
get_fxp_forw_quantization_module,
get_fxp_forwbackw_quantization_module,
)
from ... |
cfd60e052b2ef09918448e205c9db2c3b8a7ec000a48a735ebf1c4d9c342fbc0 | Python | 1,283 | 32 |
from sklearn.covariance import EmpiricalCovariance
import numpy as np
def partial_corrconn(activity_matrix, target_ts=None):
"""
activity_matrix: Activity matrix should be nodes X time
target_ts: Optional, used when only a single target time series (returns 1 X nnodes matrix)
Output: co... |
d509cf90279aebe7669b1b592b41fb9304de95e7d48e9870da80317b52a5b251 | Python | 1,283 | 32 | import difflib
from typing import Iterable
import ipywidgets as widgets
def multi_checkbox_widget(descriptions:Iterable):
""" Widget with a search field and lots of checkboxes
Parameters
----------
descriptions:
"""
search_widget = widgets.Text()
options_dict = {description: wid... |
0667df08ccfc46ff446bd7fbb2477259ea6750dd0e550080bbb7d73c0ab98223 | Python | 1,284 | 42 | import bpy
import numpy as np
from databpy.attribute import AttributeTypes
from databpy.object import create_bob
from . import coll
def create_data_object(
array: np.ndarray,
name: str = "DataObject",
collection: bpy.types.Collection | None = None,
world_scale: float = 0.1,
) -> bpy.types.Object:
... |
35254cb0187a64b2c6622ccf3f7a4c0d9c4a09b236ee2fecd395d70b8db5caf3 | Python | 1,284 | 29 | from logging import getLogger
from ..graphoelement import Ripple
lg = getLogger(__name__)
class DetectRipple:
def __init__(self):
"""Design ripple detection.
Ripples were detected as follows.
First, data were filtered between 80–100 Hz (two-pass FIR bandpass filter, order = 3 cycles of t... |
6bca69e4364dc3a56841a539e766eeefdc0b7ac65238eaa55d1d67ff56def302 | Python | 1,284 | 46 | import tensorflow as tf
import os
import numpy as np
import matplotlib.pyplot as plt
import utils
# Load model:
loaded = tf.keras.models.load_model(r'C:\Users\leroy.volmer\PycharmProjects\BCS\logs\gradient_tape\date-time\saved_models\model_28900')
# Load params:
param_path = os.getcwd() + '/params.json'
pa... |
88153a5c73708ae6ec0a910e97ef09e006c66e95959e5c3a406ce56c1af13d69 | Python | 1,284 | 29 | import numpy as np
import pandas as pd
from tests.mock_data import MockCuppaClassifier, MockTrainingData
from cuppa.classifier.feature_importance import FeatureImportance
class TestFeatureImportance:
def test_can_initialize_from_cuppa_classifier(self):
feat_imp = FeatureImportance.from_cuppa_classifier(... |
a18c9d8ecc20ec3da7d5c1571f45abac1752a4953729edcbf8ed7c24f757dc03 | Python | 1,285 | 55 | # external
import pytest
# project
import textdistance
ALG = textdistance.SmithWaterman
# https://en.wikipedia.org/wiki/Needleman%E2%80%93Wunsch_algorithm
NW_MATRIX = {
('A', 'A'): 10,
('G', 'G'): 7,
('C', 'C'): 9,
('T', 'T'): 8,
('A', 'G'): -1,
('A', 'C'): -3,
('A', 'T'): -4,
('G', '... |
b79dc7041e0a74ef766ae0c10316b1061d613d3fe751293275ccc194ae7ce5e9 | Python | 1,285 | 46 | import sys, argparse
from pybioshell.core.data.io import read_scorefile
if len(sys.argv) < 2 :
print("""
Reads Rosetta scorefile and prints only it's requested part
EXAMPLE:
python3 filter_scorefile.py 1pgx-abinitio.fsc 1pgx-abinitio-bis.fsc score -50.0 40.0
Call python3 filter_scorefile.py -h for full help... |
2212bdaaec97d1146e59335c83a7762464803946ccea6ca6da9ff65e32d3c1fe | Python | 1,286 | 67 | """
requests.compat
~~~~~~~~~~~~~~~
This module previously handled import compatibility issues
between Python 2 and Python 3. It remains for backwards
compatibility until the next major version.
"""
from pip._vendor import chardet
import sys
# -------
# Pythons
# -------
# Syntax sugar.
_ver = sys.version_info
#:... |
613e7758771a0faeed6fe66fec522d0483c048300082b920c539211429d7b76d | Python | 1,286 | 34 | # Configuration file for the Sphinx documentation builder.
#
# For the full list of built-in configuration values, see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Project information -----------------------------------------------------
# https://www.sphinx-doc.org/en/master... |
619ffe8f03fa65a767bed308933c76da229d0c34409de0c5ac34eab308a351a0 | Python | 1,286 | 38 | import argparse
import sys
from Bio import SeqIO
def parse_args(args):
parser = argparse.ArgumentParser(
prog="split_fasta.py",
description="Step1. split multiple fasta downloaded from GISAID and saved as: format is 'Isolate name | Segment | Isolate ID'.Each fasta file will be saved as 'segt_IsolateID... |
7660d815e193192369c40ebaac882ac71ce8a8057151372a1e5b862fd36d55bf | Python | 1,286 | 47 | from __future__ import print_function, division
import numpy as np
import pandas as pd
"""
Methods for paritioning labels into train/test sets by image. Partitions are stratified on image source and number
of objects per image.
"""
def stratify(labels, nbins=5):
strata = []
for source,group in labels.groupby... |
8db90df0cdf3d317df23e7e0b239de0bcf1142b29080c51be43572a8526b0455 | Python | 1,286 | 47 | """
Created on Fri Nov 19 22:51:28 2021
@author: Haotian Teng
"""
import numpy as np
from itertools import product,repeat
dataset = "/home/heavens/bridge_scratch/m6A_Nanopore/merged_dataset_diff/"
chunks_f = dataset + "chunks.npy"
seq_lens_f = dataset + "seq_lens.npy"
seqs_f = dataset + "seqs.npy"
chunks = np.load(ch... |
2703330f117cf9e43d174d170d3b29da61ee5787004630e26ed0c4b3c762e1d4 | Python | 1,289 | 42 | import re
from typing import Any
from wikibaseintegrator.datatypes.basedatatype import BaseDataType
class EntitySchema(BaseDataType):
"""
Implements the Wikibase data type 'entity-schema'
"""
DTYPE = 'entity-schema'
def __init__(self, value: str | int | None = None, **kwargs: Any):
"""
... |
ce73a9e539e5d663bd741912647e35c503e20025981be5e03b9df890b90c8a68 | Python | 1,289 | 42 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward import suites
import common_setup
REVS = ["issue546-v1"]
LIMITS = {"search_time": 300, "search_memory": 1024}
SUITE = suites.suite_optimal_with_ipc11()
CONFIGS = {
"blind-fd-limits": ["--search", "astar(blind())"],
"blind-lab-limits": ["--search"... |
330f0cf2979d7db4bce5546ce5c29fd20b76e4461835bf12ce20cd027256ba7a | Python | 1,291 | 55 | # external
import pytest
# project
import textdistance
ALG = textdistance.NeedlemanWunsch
# https://en.wikipedia.org/wiki/Needleman%E2%80%93Wunsch_algorithm
NW_MATRIX = {
('A', 'A'): 10,
('G', 'G'): 7,
('C', 'C'): 9,
('T', 'T'): 8,
('A', 'G'): -1,
('A', 'C'): -3,
('A', 'T'): -4,
('G',... |
08a443b6ba47bd6dcf3980c580dc0fc1307dedb456a6907408dd64048a7e1846 | Python | 1,292 | 31 | from typing import List, Callable, Dict
import torch
from torch import nn
from .base import AtomicModule
from ..layer import EmbeddingLayer
from ..utils import expand_para, find_distances
class ANI(AtomicModule):
def __init__(self,
embedding_layer : EmbeddingLayer,
n_layers ... |
6fde8f040c187ab48e99de2f8aaa6d26310499daf972049699ff8e25bfd812ba | Python | 1,292 | 42 | import numpy as np
import scipy
from wsilearn.utils.cool_utils import is_list_or_tuple
def _array_row_metric(x, metric_fct, unravel1=True, **kwargs):
if is_list_or_tuple(x):
x = np.array(x)
elif unravel1 and (len(x.shape) == 1 or x.shape[0] == 1 or x.shape[1] == 1):
x = x.ravel()
if len(x... |
7b1e08495963522855daff8071a91317c44823a7d3362f3144fc9089bd409677 | Python | 1,292 | 50 | import os
import sys
read_dir_path = sys.argv[1]
output_dir_path = sys.argv[2]
model_name = sys.argv[3]
dir_list = os.listdir(read_dir_path)
batch=0
modeltype = ''
if model_name == "default":
batch=512
modeltype = 'default'
elif model_name == "TINYX1":
batch=1600
modeltype = 'tinynoskipx1'
eli... |
965544f7f57a0817d339165cd256bf6cb1b9c8ce75c5caf4937cbaa1d4dc2b7a | Python | 1,293 | 39 | import torch
def calculate_asymmetric_quant_params(
min_float: torch.FloatTensor,
max_float: torch.FloatTensor,
min_quant: torch.IntTensor,
max_quant: torch.IntTensor,
eps: torch.FloatTensor,
):
scale_factor = (max_float - min_float) / (max_quant.float() - min_quant.float())
scale_factor =... |
bc6ea4d96e48de28d300a656bc9899f6b08fde2a12e8984d96cb51bac794a269 | Python | 1,293 | 13 | """UNDECIDED_BY_CLASS.py 2026-09-25. Share of neurons with no transmitter call (nt_type empty in the table the models
use) by cell class, and what Shiu's rule does with them. Output 06-OUTPUT/undecided_by_class.txt"""
import pandas as pd
a = pd.read_csv('D:/eucys/02-DATA/flywire-annotations/Supplemental_file1_neuron_an... |
a3e15bc8212ff6288d35f49c7ab8147711a6a140f19a89af3e341e69074cce7a | Python | 1,294 | 39 | import os
import numpy as np
hartree2ev = 27.211386024367243
bohr2ang = 0.5291772105638411
hpro_rng = np.random.default_rng(seed=42)
OPENMX_VERSION = '3.9'
OPENMX_BASIS_TABLE = os.path.join(os.path.dirname(__file__), 'from_openmx', 'opmx_basis.txt')
OPENMX_LINEAR_RGRID_DEN = 100.0
def _load_openmx_basis_specs_2019... |
06c1644632d1d4c952a8f1f5bd2dafa4313aca5a150fbfcbb88575de744729cd | Python | 1,295 | 39 | from importlib.machinery import ModuleSpec
from typing import cast
import cocotb
import pytest
from elasticai.creator.file_generation.resource_utils import get_file_from_package
from elasticai.creator.testing import CocotbTestFixture, eai_testbench
@cocotb.test()
@eai_testbench
async def my_testbench(dut, x, input_... |
9709f56021905166c0ac6ec4ce448a5a47d79cf6acf831ea75b419b9cb4ad6fc | Python | 1,295 | 38 | """registration_diagnostics.json emission helper."""
import json
import os
from regtools.registration.pipeline import _write_diagnostics_json
def test_writes_present_blocks(tmp_path):
diag = {
"deformation_regularity": {
"folding_fraction": 0.002,
"jdet_min": 0.1,
... |
e2a1b0fa560a6c8691296b565ccb3182f9d0b46fdb7a0ff3b7fc04dbb95aafee | Python | 1,295 | 42 | """Smoke test for the stitching GUI gain-compensation toggle.
The gain-compensation checkbox defaults ON and is gated on the vignetting checkbox
(gain compensation needs the flat-field). See regtools/stitching/gui.py.
"""
from __future__ import annotations
import os
import pytest
pytest.importorskip("P... |
2c94721b51465efdac9efa2d21f63f510c4f859f682d5dfa5204704806110406 | Python | 1,296 | 37 | from utils.api import get_filters_result_from_project
from preprocess import TCGA_Project
from utils.logger import setup_logging
from pathlib import Path
from utils import set_random_seed
SEED = 1126
set_random_seed(SEED)
if __name__ == '__main__':
setup_logging(Path('./Logs/Tests/'))
project_id = 'TCGA-PRAD... |
9e16fe59d6c3e31c7096ec1294eec4eef4c2b3b2aee214bc82bf666309fe7668 | Python | 1,296 | 35 | # 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... |
b36756ecda7c0b9a1dca79d9848b855b82e152eca10c6274c30866b648dc8479 | Python | 1,296 | 50 | # modified from 3DDFA-V2
import sys
sys.path.append('..')
import cv2
import numpy as np
import scipy.io as sio
from Sim3DR import RenderPipeline
def _to_ctype(arr):
if not arr.flags.c_contiguous:
return arr.copy(order='C')
return arr
cfg = {
'intensity_ambient': 0.75,
'color_ambient': (1, ... |
532154a0f89959de6d70c4764acb9b100335c217f8658ea3aeb98a10479cdf51 | Python | 1,297 | 43 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, MaiaEnvironment
from common_setup import IssueConfig, IssueExperiment, is_test_run
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue591-base", "issue591-v1"]
CONFIGS = [
IssueConfig(heur... |
66abb1c19f3d1f10b6cdd85f6a1a792566da88385693b8ce680a5747a4846b38 | Python | 1,297 | 42 | 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_atoms_supercell_by_phonopy, get_phonopy
def test_get_p... |
7d6b52a8479c95a2aa905cbeccd94cb0fc2d67f8c60a61d81c7b2faff2da9625 | Python | 1,297 | 55 | # Librairies
import os
import sys
code_path = os.path.split(os.path.split(os.getcwd())[0])[0]
sys.path.append(code_path)
import numpy as np
import argparse
from setting import *
from simulate_data import *
from loader import *
from graphs import *
from utils import *
# Arguments
argParser = argparse.ArgumentParser()
... |
905cce3c5edfc73f4e55a30123f13eaccd36717a01088aefc7b2734aace76d8d | Python | 1,298 | 14 | """Post hoc (5 Oct, after HEMIBRAIN_BENCH H1 PARTLY): v2LN30's lead onto uPNs counting only synapses inside the antennal lobe
(dendritic), since APL's synapses onto uPNs lie in the calyx and the hemibrain's antennal lobe is cut by the volume edge."""
import re, pandas as pd
HB = 'D:/eucys/02-DATA/hemibrain/v1.2/exporte... |
77b110049a78c12c4c088312168b244171686640f969c369e102b5f32839eb76 | Python | 1,299 | 43 | # 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... |
ca8207d3a55b6474bc98ac7c617730fdc7d243635487f5dd254f14a919ca811e | Python | 1,299 | 29 | import unittest
from parameterized import parameterized
from HyDGL.qm_data import QmData
from HyDGL.enums.nbo_type import NboType
from HyDGL.file_handler import FileHandler
from tests.utils import Utils, TEST_FILE_QM_DATA_OREDIA
class TestQmData(unittest.TestCase):
@parameterized.expand([
[
... |
cc112536d2f370d1d10b814484079a6fc569dff87db96f6ac6267d0b962618e4 | Python | 1,299 | 23 | # Copyright 2020 Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# ht... |
0f82ca160ca61512b4bd7a19805fd9ecf47af019c4c2e7d0e6fc86fd28a80245 | Python | 1,300 | 39 | # -*- coding: utf-8 -*-
import tensorflow as tf
from pinn.layers import CellListNL
class LJ(tf.keras.Model):
"""Lennard-Jones Potential
This is a simple implementation of LJ potential
for the purpose of testing distance/force calculations.
Args:
tensors: input data (nested tensor from datase... |
3724511a0c3c064d869f1febc0d563c5a31beecf2147313f0ab396c385845a76 | Python | 1,300 | 56 | # %%
import sys, os
sys.path.append(os.path.abspath(".."))
sys.path.append(os.path.abspath("."))
import torch.optim as optim
import torch.nn as nn
import torch
import prosper_nn.models.deep_feed_forward.deep_feed_forward as deepff
import prosper_nn.utils.sensitivity_analysis as sens_analysis
# %% Parameter
input_dim... |
6d3e9dc67e6f5b0ebd846aff9410fe837f1d4fd6c018edd25c02684bac2c7ce4 | Python | 1,300 | 36 | import json
import os
def test_launch_writes_job_bat_and_lock(tmp_path):
from regtools.ome_zarr_converter.terminal_runner import launch_job_in_terminal
recorded = {}
def fake_spawn(root, bat_path):
recorded["root"] = root
recorded["bat"] = bat_path
job = {"type": "point... |
c3e9164f4d3538acf0c3b0db9c4e41a13ea824fff9e0598b523eb0b9478b374a | Python | 1,300 | 28 | #
# MIT License
#
# Copyright (c) 2022 GT4SD team
#
# 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, copy, modify, merge,... |
563a621d74bfebc2a8c0d0e28d87836f4a5ed88b92931fc948f2dc9853fe6622 | Python | 1,301 | 27 | #
# MIT License
#
# Copyright (c) 2022 GT4SD team
#
# 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, copy, modify, merge,... |
0b76c0a73344e86ca2925af6a83170d37d74b04ff1497b0b54bc5418ce95ebda | Python | 1,302 | 44 | '''
Script that handles ECFP data input for the DNN
'''
import numpy as np
import pandas as pd
import torch
from torch.utils.data import Dataset
from tqdm import tqdm
class CustomDataset(Dataset):
def __init__(self, partition, ml_table_filename, accession):
self.partition = partition
self.accessi... |
7949dbc04fd8c452076fea2561ab3d289b83b804f46d0b1099e0d6870af69143 | Python | 1,302 | 44 | #!/usr/bin/python3
import numpy as np
import nibabel as nib
import argparse
import os
parser = argparse.ArgumentParser()
# parser.add_argument('-indir', nargs=1, type=str)
parser.add_argument('-inpath', nargs=1, type=str)
parser.add_argument('-outdir', nargs=1, type=str)
parser.add_argument('-filename', nargs=1, t... |
ed80c6d44cc2bc2665b19d3a8184b63ed6230e43a9d9c28520c639b89e727913 | Python | 1,302 | 31 | """
This file is part of Myonset.
Myonset 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 License, or
(at your option) any later version.
Myonset is distributed in the hope that it will b... |
7014494db875959a6e67d21051f65371bb6244ca84c689b397d75f595b81dd00 | Python | 1,303 | 36 | """Test the interface calculation"""
from eudockscore.utils.pdb import get_ca_coords, get_sparse_matrix
from eudockscore.utils.interface import (
get_pair_interface_residues,
get_target,
)
from eudockscore.utils.find_interfaces import PositiveDatabaseBuilder
import numpy as np
import pandas as pd
import torch
... |
a5ceb04ef18d11b4fba16831094b686ac2fbbf4dd5178b57658a26d7902b5cba | Python | 1,303 | 46 | import numpy as np
min_volt, max_volt = -100, 50
min_cur, max_cur = 0, 0.5
dynamic_type = 'v'
def volt_norm(array_):
if dynamic_type == 'v':
return (array_ - min_volt) / (max_volt - min_volt)
elif dynamic_type == 'i':
return (array_ - min_cur) / (max_cur - min_cur)
else:
raise Not... |
31432398fc3d0d69c644d453b4a27772f4fc9491ed59953db9909b7d05a4f322 | Python | 1,304 | 57 | # external
import pytest
# project
import textdistance
ALG = textdistance.DamerauLevenshtein
COMMON = [
('test', 'text', 1),
('test', 'tset', 1),
('test', 'qwy', 4),
('test', 'testit', 2),
('test', 'tesst', 1),
('test', 'tet', 1),
('cat', 'hat', 1),
('Niall', 'Neil', 3),
('alumi... |
1f4f55443d853e496b354817185e7cd37369c99c5019edcc57b8a2d07b561d46 | Python | 1,305 | 50 | """Nexus acquisition manager example."""
# %%
import matplotlib.pyplot as plt
import numpy as np
import console
from console.interfaces.dimensions import Dimensions
from console.service.acquisition_manager import AcquisitionControlManager
from console.utilities.sequences import tse_3d
# %%
seq, _ = tse_3d.constructo... |
5577c550334eae588bfe9d380a6da3fa4843dc32610956a3cfc2414669b735bc | Python | 1,305 | 38 | # Material "Ambient Occlusion", dumped by nodebpy.assets.dump_library.
# Rebuild the library with nodebpy.assets.build_library (nodebpy build).
# The class is a recipe for the material's shader tree — build recreates the material and runs it into material.node_tree.
from bpy.types import ShaderNodeTree
from nodebpy imp... |
655b54a9e9a11f5e6992327f2bd52eeab6319e5b9980fbd76b124b945ac1120b | Python | 1,305 | 34 | from .base_converter import BaseConverter
from ..operators import ACSConv
class ACSConverter(BaseConverter):
"""
Decorator class for converting 2d convolution modules
to corresponding acs version in any networks.
Args:
model (torch.nn.module): model that needs to be converted
Warnings:... |
d9a23b51f1fdb25af7d8cfde331e17d6e2776667821bb1f71caf50b0417b2782 | Python | 1,305 | 34 | from plantsegtools.proofreading import BasicProofread
import argparse
def parse():
parser = argparse.ArgumentParser()
parser.add_argument('-r', '--path-raw', type=str, required=True, help='path to raw file')
parser.add_argument('-dr', '--dataset-raw', type=str, default='raw',
requi... |
02f7c6d29684a28af3549a832c06a69b86c836cba5cda951ca1151e5597b4257 | Python | 1,306 | 52 | import yaml
from pathlib import Path
from pydantic import BaseModel
from typing import Any
class ArrayAction(BaseModel, extra='forbid'):
name: str
method: str
# The name of an optional reference signal
ref_name: str | None = None
alt_ref_names: list[str] | None = None
kwargs: dict[str, ... |
169402f60657a47db5c7d575c4d471ff288a91c97dccb069be71bc589cfe22b7 | Python | 1,306 | 44 | import unittest
import torch
from torcheeg.models import BCGenerator, BCDiscriminator, BGenerator, BDiscriminator
class TestGAN(unittest.TestCase):
def test_bgan(self):
g_model = BGenerator(in_channels=128)
d_model = BDiscriminator(in_channels=4)
z = torch.normal(mean=0, std=1, size=(1, 1... |
6dd6044ce9a0628f9e56623901666eb1c345a7788fe6247d4af2f606368a91e6 | Python | 1,306 | 43 | import torch
import torch.nn as nn
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
# Define loss
def mtl_loss(x, y, weight, criterion, model):
argmax = nn.Softmax(dim=1)
logits = model(x)
loss = 0
for (i, logit) in enumerate(logits):
pred_logit = argmax(logit)
loss... |
cf415301d7f54e75f65b74e628cd9694774325152709e1d50b70d7ece45b98e2 | Python | 1,307 | 40 | import unittest
import os
import sys
sys.path.append(os.path.dirname(os.path.realpath(__file__)) + "/../../src")
from hornet.model import retrieve_mean_and_sigma
class TestRetrieveMeanAndSigma(unittest.TestCase):
def setUp(self):
self.path = ".model_test_rms"
self.empty_path = ".model_test_empty_r... |
36f90406a827448767f12134931470fb19820a237b7022c7ff17a272200965ff | Python | 1,309 | 37 | import os.path as osp
import numpy as np
from .io import _load
def make_abs_path(d):
return osp.join(osp.dirname(osp.realpath(__file__)), d)
class ParamsPack():
"""Parameter package"""
def __init__(self):
try:
d = make_abs_path('../3dmm_data')
self.keypoints = _load(osp.join(d, 'keypoints_sim.npy'))
... |
f492c596f55b718fa296a6df26d0e80c7539746406da23c05915a40fa4f9a504 | Python | 1,309 | 40 | import distutils.command.bdist_rpm as orig
from ..warnings import SetuptoolsDeprecationWarning
class bdist_rpm(orig.bdist_rpm):
"""
Override the default bdist_rpm behavior to do the following:
1. Run egg_info to ensure the name and version are properly calculated.
2. Always run 'install' using --sin... |
ecff10875817f8ead59d365e52afa03d29b6ad843fac9bc9d4747fed01a70380 | Python | 1,310 | 42 | from __future__ import annotations
from importlib.util import find_spec
from pathlib import Path
from shutil import rmtree
TEST_RESULTS_DIR = Path(__file__).parent / "_test_results"
TEST_SCRATCH_DIR = Path(__file__).parent / "_test_scratch"
TEST_RUNINFO = Path(__file__).parent / "runinfo"
has_parsl = bool(find_spec(... |
ef5be54867c8cfcfd3896f51e6a020a3d1b67f68698207135363f136294d73e5 | Python | 1,310 | 48 | # Node group "Ray Origin" (ShaderNodeTree), dumped by nodebpy.assets.dump_library.
# Rebuild the library with nodebpy.assets.build_library (nodebpy build).
# Shared by several assets, which import it; not an asset itself.
# _build_group() is the source of truth: the docstring, __init__ and accessors are regenerated fro... |
b3d4d85852ceb62c8c60f422aef1b807a18b210a9dd65915e522269e2e664875 | Python | 1,311 | 44 | # Node group ".MN_world_scale" (GeometryNodeTree), dumped by nodebpy.assets.dump_library.
# Rebuild the library with nodebpy.assets.build_library (nodebpy build).
# Shared by several assets, which import it; not an asset itself.
# _build_group() is the source of truth: the docstring, __init__ and accessors are regenera... |
c7493b08dd2daaf5ed5202de6d4353a4a35ac65994f46f1d7a67aee590b7a4b8 | Python | 1,311 | 42 | import pytest
@pytest.fixture(scope="module")
def _qapp():
try:
from PySide6.QtWidgets import QApplication
except Exception as exc: # pragma: no cover
pytest.skip(f"PySide6 unavailable: {exc}")
return QApplication.instance() or QApplication([])
def _patch_git(monkeypatch):
... |
c318de7bbf74c8e0da21aea9750fe51e456a551f5408340664cca0e8cb992667 | Python | 1,312 | 40 | import pytest
from regtools.registration.core.registration.affine_methods import (
AFFINE_METHODS,
MATCHED_AFFINE_KWARGS,
resolve_affine_method,
)
def test_default_is_no_split():
affine_type, kwargs = resolve_affine_method("default", None)
assert affine_type is None # None => run the fu... |
cfa0e35e342aecd24def9ef71aed23d9ba19bbf601a8432fd7ec907be1b1e7fe | Python | 1,312 | 45 | from torch.utils.data import DataLoader
from torch.utils.data.distributed import DistributedSampler
import segm.utils.torch as ptu
class Loader(DataLoader):
def __init__(self, dataset, batch_size, num_workers, distributed, split):
if distributed:
sampler = DistributedSampler(dataset, shuffle=... |
e69a176b50542a54cdecdca78b4d6a76e1f22d4a261803a78ed5002b93c1c0c8 | Python | 1,312 | 35 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Oct 3 11:47:48 2022
@author: heavens
"""
import os
import h5py
import argparse
from xron.utils.seq_op import fast5_shallow_iter
from xron.utils.fastIO import read_fastq
def indexing(args):
fastq_records = read_fastq(args.fastq)
fast5_records =... |
f9bcaf4c04027d57daa8a8e3bb8d8a3f6f93e37950eaaa9a8241067a98e17d6a | Python | 1,312 | 33 | #
# MIT License
#
# Copyright (c) 2022 GT4SD team
#
# 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, copy, modify, merge,... |
7186921b2f8576ca6f625d99a537d5ac89e50bfdcece3af83964704fa220b483 | Python | 1,314 | 41 | from __future__ import print_function
from multiprocessing import Pool, TimeoutError, cpu_count
DATE_FORMAT = '%y-%m-%d_%H-%M-%S'
def get_max_cores(serial=False):
if serial:
return 1
#available_cores = MAX_SERIAL if serial else int(math.ceil(MAX_CPU_FRACTION * available_cores))
return max(1, cpu_... |
d93d0625fbf8dcad34e36305cedd58ac5af67f0b1069f6df4fc9d73d9fec0f22 | Python | 1,314 | 49 | import torch
import prosper_nn.utils.generate_time_series_data as gtsd
import prosper_nn.utils.create_input_ecnn_hcnn as ci
from prosper_nn.models.ecnn import ECNN
# Define network and data parameters
past_horizon = 10
forecast_horizon = 5
n_features_U = 2
n_features_Y = 2
n_data = 20
n_state_neurons = 4
batchsize = ... |
f637f206b98e28f932e2aa965c846a9f9f110df8e3a8143ae1c138fc10075fe4 | Python | 1,314 | 47 | import os
import csv
from tqdm import tqdm
from torchdrug import data, utils
from torchdrug.core import Registry as R
@R.register("datasets.PubChem110m")
@utils.copy_args(data.MoleculeDataset.load_csv, ignore=("smiles_field", "target_fields"))
class PubChem110m(data.MoleculeDataset):
"""
PubChem.
This da... |
14e91ce4c9cfa33c585be73c8d633cd297ceec88fa9068f620a6e846b1088a16 | Python | 1,315 | 46 | import unittest
from torcheeg.datasets import SleepEDFxDataset, HMCDataset, ISRUCDataset, P2018Dataset
class TestSleepStageDetectionDataset(unittest.TestCase):
def test_sleep_edfx_dataset(self):
kwargs = {
'record': 'fake_record',
}
kwargs.update(SleepEDFxDataset.fake_record(... |
30b6c5ba96ad4b4a831d4e94450d8cb80ee54b3b551fd4fe28bb2045a10411fc | Python | 1,315 | 49 | import os
import sys
if sys.path[-1] != os.getcwd():
sys.path.append(os.getcwd())
import time
import json
from log.basic_logger import BasicLogger
def create_dir(dir_list):
assert isinstance(dir_list, list) == True
for d in dir_list:
if not os.path.exists(d):
os.makedirs(d)
class Tr... |
31c17e2c3943afc2836a965ad016cad70615a675f820bef1dc18a3a37e277671 | Python | 1,315 | 47 | #!/bin/env python3
"""
Plot PS
"""
import numpy as np
import matplotlib.pyplot as plt
import ithildin
import sys
def plot(it:int, ax:plt.Axes=None) -> list[plt.Artist]:
if ax is None:
ax = plt.gca()
artists = []
dt = sd.deltas[0]
t = sd.linspace(0)[it]
filaments = sd.filaments
filament... |
735e42c93cf854cf4ec8fbd51769727baedc7e84bf05c884fdb2f521ce38c397 | Python | 1,315 | 49 | import yaml
import numpy as np
import pickle
import os
import pandas as pd
from BEBE.models.preprocess import static_acc_filter
class BehaviorModel():
def __init__(self, config):
self.config = config
self.model_config = config['model_config']
self.metadata = config['metadata']
cols_includ... |
9a60c71ebf1837ec006cf7249ab03b3330896faf254c3c820a51126a2c40381d | Python | 1,315 | 64 | import plotly.graph_objects as go
import pandas as pd
# load dataset
df = pd.read_csv("volcano.csv")
# create figure
fig = go.Figure()
# Add surface trace
fig.add_trace(go.Surface(z=df.values.tolist(), colorscale="Viridis"))
# Update plot sizing
fig.update_layout(
width=800,
height=900,
autosize=False,... |
b2f14acd6a9af18937f339f6da54a1a15e569210d8d9ef079620a84895742d32 | Python | 1,315 | 35 | from wonambi.detect import consensus, match_events
rater1 = [
{'start': 3, 'end': 9, 'chan': 'Cz'},
{'start': 20, 'end': 25, 'chan': 'Cz'},
{'start': 30, 'end': 40, 'chan': 'Cz'},
{'start': 42, 'end': 42.5, 'chan': 'Cz'},
{'start': 98.1, 'end': 100, 'chan': 'Cz'},
{'star... |
cfa5ed822e302c88540da1ee0d7b39b788b85a202082db27bdd3f1ce56cfeea4 | Python | 1,315 | 42 | from copy import deepcopy
from os.path import dirname, split
from numpy import arange, atleast_2d, squeeze
try:
from mne import morph_data, SourceEstimate
except ImportError:
pass
class Morph:
def __init__(self, from_surf, to_surf='fsaverage', smooth=None):
self.from_surf = from_surf
self... |
f60401d9aead69f3a51e2ad08e2f317f2396c736f05a21367f3bf7c48c18fc66 | Python | 1,315 | 37 | from cloudvolume import CloudVolume
import numpy as np
from scipy import ndimage
src = CloudVolume('gs://neuroglancer/pinky100_v0/image_single_slices/cfsplit_manual', mip=5, cdn_cache=False);
roi = CloudVolume('gs://neuroglancer/pinky100_v0/image_single_slices/roicc', mip=6);
dst = CloudVolume('gs://neuroglancer/pinky... |
bab78d21b989c11a99a6e06ba1e0423d7a50c03a2b08d8ed7466ed0c50efcfa8 | Python | 1,316 | 36 | import os
import glob
import pandas as pd
import argparse
def combine_csv_files(directory, output_file="combined_ph_data.csv"):
try:
# Recursively find all CSV files in the directory
csv_files = sorted(glob.glob(os.path.join(directory, "**", "*.csv"), recursive=True))
if not csv_fi... |
0ec1048d3865330ba4b9fa3c5d88bb00c251d82e66e7c7f522bb55c518ea9127 | Python | 1,317 | 44 | import numpy as np
import pytest
from regtools.geometry_registration.pipeline import load_section
def test_load_section_grayscale_npy(tmp_path):
arr = (np.random.default_rng(0).random((12, 16)) * 255).astype(np.uint8)
p = tmp_path / "gray.npy"
np.save(p, arr)
data, nch = load_section(str(p)... |
327f92cdafda7405e293455952cba806d6273156ce0ce49a38bd10f8b158b984 | Python | 1,317 | 32 | """code for running light-weight object detection to locate animals and regions of interest (roi's)"""
import cv2
from pycoral.adapters import common
from pycoral.adapters import detect
from pycoral.utils.edgetpu import make_interpreter, run_inference
import logging
from time import perf_counter
logger = logging.getLo... |
c44fe2680e10f132fe47aa6ca59ef527c2b632917ae200611d0fdb747d9d76ce | Python | 1,317 | 37 | from .base_converter import BaseConverter
from ..operators import SoftACSConv
class SoftACSConverter(BaseConverter):
"""
Decorator class for converting 2d convolution modules
to corresponding soft-acs version in any networks.
Args:
model (torch.nn.module): model that needs to be converted
... |
83f6f5cd9ca7102df86c5c8a64898e3c31561d337d3b6e8d2343c65974581c75 | Python | 1,318 | 28 | from __future__ import print_function
from examples.pybullet.utils.pybullet_tools.pr2_problems import create_pr2, create_table, Problem
from examples.pybullet.utils.pybullet_tools.pr2_utils import get_other_arm, get_carry_conf, set_arm_conf, open_arm, \
arm_conf, REST_LEFT_ARM, close_arm, set_group_conf
from examp... |
8c0882973b75da30adaf683c73358cddeba623932fef7a7cfe61abf776976bdd | Python | 1,318 | 25 | # Copyright 2020 Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# ht... |
b2a8bb0679df16d549e3a802f00960ad997f007af213214319d5c0f45e3356ef | Python | 1,318 | 44 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DI... |
17c4aedb114029d5e3917067f63330945741ba78be86bf2c2874c4d285bf6bf7 | Python | 1,319 | 44 | from pylearn2.utils import serial
import sys
_, model_path = sys.argv
model = serial.load(model_path)
space = model.generator.get_output_space()
from pylearn2.config import yaml_parse
from pylearn2.gui.patch_viewer import PatchViewer
import numpy as np
dataset = yaml_parse.load(model.dataset_yaml_src)
grid_shape = No... |
899261bf80cdc8c7e31da40817977fcce9299411dc1ff28739b53de74a0426ec | Python | 1,319 | 49 | """Standalone GUI launcher for the tissue-masking tool.
Usage:
python -m regtools.tissue_masking.launch
"""
import os
import sys
# Ensure project root is on sys.path
from regtools import get_project_root
_project_root = get_project_root()
if _project_root not in sys.path:
sys.path.insert(0, _p... |
48fd00e749c96d9373bf9648858b916f7cbda8bc0675dda38c45d8618b24a348 | Python | 1,320 | 55 | import sys, math
from pybioshell.core.data.io import find_pdb
from pybioshell.core.data.basic import Vec3
from pybioshell.std import vector_core_data_basic_Vec3
from pybioshell.core.calc.structural import *
from pybioshell.utils import LogManager
LogManager.INFO()
if len(sys.argv) < 2 :
print("""
Calculates t... |
8ceb9b3a28f2d37eedfd973bdce8378a0e517b52b5297845e8e252fa76badeab | Python | 1,320 | 50 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
''' Segmentation of MRI for forward modeling '''
"""
Created on Thu Nov 18 14:08:04 2021
@author: david
"""
import os
import os.path as op
from stormdb.process import Freesurfer
from stormdb.base import mkdir_p
from stormdb.access import Query
from sys import argv
proj_... |
f67bb5137419e98d99a68cf18e9b4d6396cb106591620675b463bed325337d64 | Python | 1,320 | 36 | """HED analysis and summarization tools."""
from .analysis.event_manager import EventManager
from .analysis.file_dictionary import FileDictionary
from .analysis.hed_tag_manager import HedTagManager
from .analysis.hed_type_defs import HedTypeDefs
from .analysis.hed_type_factors import HedTypeFactors
from .analysis.hed_... |
a76d4f5a44637bcdf79ca1357bf9d9bf921b1a267934789bea9290125e48dd7b | Python | 1,321 | 57 | from __future__ import annotations
from .config import (
SPATIAL_COORDINATE_FEATURES,
FeaturePreparationConfig,
DimensionalityReductionConfig,
ClusteringConfig,
)
from .feature_preparation import (
FeaturePreparationEngine,
FeaturePreparationResult,
)
from .dimensionality import (
Dimensi... |
d920c50735a88e07553c22378e43539389e29d997beab99af27953fdac032eb5 | Python | 1,321 | 41 | # 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... |
1f5dee2ac4a0cd2a2aa1984a06fc64359c7d995960bf51b8010536ad7f1417c9 | Python | 1,322 | 39 | from setuptools import setup, Extension
import setuptools
import os
from setuptools.command.install import install
from setuptools.command.develop import develop
from setuptools.command.egg_info import egg_info
extensions = [Extension("libfwdbwdcpp",
["ChromA/util/FwdBwd.cpp"],
... |
58b30d0dcf74bb61b7ac1d2f04fd5de44cb259b5020790538c0e0e99cb3c7f11 | Python | 1,322 | 56 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu May 20 11:56:34 2021
@author: mpolonenko
"""
import numpy as np
# import matplotlib.pyplot as plt
from expyfun.io import read_hdf5, write_hdf5
import pip_trains_rme
import os
# %%
opath = '/mnt/data/peaky_pitch/'
stim_path = opath + 'stimuli/slices/cli... |
878e4dd04a4d97898de082cea0b97fb994004991b656649b8c1f49b27d9907d5 | Python | 1,322 | 29 | # Copyright 2020 Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# ht... |
c0e1bf5fe1f4991c6d4471380bcdb00d93dd29a02bbd17536f3c18b28c8b3e1a | Python | 1,322 | 37 | import logging
import pathlib
from NDATools import exit_error
logger = logging.getLogger(__name__)
def validate(args):
'''TODO before we move vtcmd code into here, we need to add an adapter for the command line options'''
exit_error('This command is not yet implemented')
def submit(args):
exit_error('... |
c3ee097262a07a2c5a9b51510d8cab860b452188a285557e7ac152495464307d | Python | 1,322 | 44 | from typing import List, Tuple
import numpy as np
import torch
import yacs.config
def cutmix(
batch: Tuple[torch.Tensor, torch.Tensor], alpha: float
) -> Tuple[torch.Tensor, Tuple[torch.Tensor, torch.Tensor, float]]:
data, targets = batch
indices = torch.randperm(data.size(0))
shuffled_data = data[i... |
dd0a17cb267db1e7e175f18c6bdee2bc9c10d3b9f855ebd6459db24859986088 | Python | 1,322 | 36 | import os
import glob
import pandas as pd
import argparse
def combine_csv_files(directory, output_file="combined_edema_data.csv"):
try:
# Recursively find all CSV files in the directory
csv_files = sorted(glob.glob(os.path.join(directory, "**", "*.csv"), recursive=True))
if not csv... |
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