sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
ee134b662e192e13553707d9fc884d689813016741a805d52ab2644d3e8f7def | Python | 324 | 9 | """initialize pyprep."""
import pyprep.ransac as ransac # noqa: F401
from pyprep.find_noisy_channels import NoisyChannels # noqa: F401
from pyprep.prep_pipeline import PrepPipeline # noqa: F401
from pyprep.reference import Reference # noqa: F401
from . import _version
__version__ = _version.get_versions()["versio... |
81cb617e8502f7a06a707145b60d58a1f9e56ef271aedf9399ceb56e9c24595a | Python | 325 | 20 |
def predict_mc_dropout(test_data, model, passes):
predictive_posterior_mean = None
variance = None
return predictive_posterior_mean, variance
if __name__=="__main__: ":
# load test preprocessing
# load pretrained model
# specify number of passes through the network
predict_mc_drop... |
a91dcc83c38c6ee5e297eabbf8d76b800d5b42c308f3698aaace78e56cff8bdd | Python | 325 | 8 | try:
import torch_geometric
except ImportError as e:
raise ImportError(
"To run the torcheeg with graph neural networks and related transforms, you need to install `torch_geometric`. Please refer to `https://pytorch-geometric.readthedocs.io/en/latest/notes/installation.html`."
) from e
from .to imp... |
e922cd57347d8d2d246137cc432271568084e37a0f7c2c00907cafe941f30840 | Python | 325 | 16 | #!/bin/env python3
'''
Verify Feynman-like diagram
'''
import yaml
import sys
import pdlfeynman as fy
yp = lambda *x: print(yaml.safe_dump(x, allow_unicode=True))
assert len(sys.argv) == 2
diagram = yaml.safe_load(open(sys.argv[1]))
is_valid, message = fy.diagram.is_valid(diagram)
print(message)
assert is_valid, mes... |
e3c4c492a1c5c9710702016d899f185c2fc037cc99b7e1f6351f3c2e592e592e | Python | 326 | 15 | class AverageMeter:
def __init__(self):
self.reset()
def reset(self):
self.val = 0
self.avg = 0
self.sum = 0
self.count = 0
def update(self, val, num):
self.val = val
self.sum += val * num
self.count += num
self.avg = self.sum / self.... |
42e782520a853db7b5f0fd55b3355ff1d3854ab00e1a4f2589afa6e032195437 | Python | 327 | 17 |
import scanpy as sc
# Data reading
input_file = "Dementia/SEA_AD_MTG.h5ad"
adata = sc.read_h5ad(input_file)
# Get highly variable genes
sc.pp.highly_variable_genes(adata, n_top_genes=2000, inplace=True, subset=True)
# Scale
sc.pp.scale(adata)
# Write the output file
adata.write_h5ad("Dementia/Dementia_processed.... |
d63abde795e48962495c62921442930035cc3cafc6d7b463b4e0bda9626a3d58 | Python | 327 | 20 | from topaz.model.classifier import LinearClassifier
class TestLinearClassifier():
def test_init(self):
pass
def test_width(self):
pass
def test_latent_dim(self):
pass
def test_fill(self):
pass
def test_unfill(self):
pass
def test_forward(self):
... |
a9ff1e305b9fb17bd767792a89897ab7c5926ce2e1ac8e4e3ae0473a7ff21d15 | Python | 328 | 9 |
# Copyright 2023 The Xron Authors. All Rights Reserved.
#
#This Source Code Form is subject to the terms of the Mozilla Public
#License, v. 2.0. If a copy of the MPL was not distributed with this
#file, You can obtain one at http://mozilla.org/MPL/2.0/.
"""Initial file for the package"""
from xron._version import __v... |
d0cc7887baddd22cdd6b7a3bbf5ef10a4ff65ac96d93259cd46f07b4b0552214 | Python | 328 | 10 | def get_vhdl_templates(padding_len, layer_name):
if padding_len == 0:
suffix = "_not_padding"
else:
suffix = "_zero_padding"
template_file_name = f"{layer_name}{suffix}.tpl.vhd"
test_template_file_name = f"{layer_name}{suffix}_tb.tpl.vhd"
return template_file_name, test_template_fi... |
77bbb0ff6bc4cb716f595d576f89e43f22597efc6d0a96acf2619b4bd3e4f0b2 | Python | 329 | 8 | # Copyright 2017 The Chiron Authors. All Rights Reserved.
#
#This Source Code Form is subject to the terms of the Mozilla Public
#License, v. 2.0. If a copy of the MPL was not distributed with this
#file, You can obtain one at http://mozilla.org/MPL/2.0/.
"""Initial file for the package"""
from xron._version import __... |
5fb7ff30d4f8be64cfff9a2021324cf229960433533b024b8d268b0d93cef57e | Python | 330 | 11 | #!/usr/bin/python
# -*- coding:utf-8 -*-
# -*-mode:python ; tab-width:4 -*- ex:set tabstop=4 shiftwidth=4 expandtab: -*-
from control.gxipy.gxiapi import *
from control.gxipy.gxidef import *
from control.gxipy.gxwrapper import *
__all__ = ["gxwrapper", "dxwrapper", "gxiapi", "gxidef"]
__version__ = '1.0.18... |
c2851c4b645bdded4a91e36905229e37d7ac87c8f7418c0b04bd50471d49fc28 | Python | 330 | 14 | from .band import *
from .band_pyeeg import *
from .coefficient import *
from .concatenate import *
from .correlation import *
from .downsample import *
from .flatten import *
from .normalize import *
from .pick import *
from .rearrange import *
from .reshape import *
from .spectrum import *
from .to import *
from .fli... |
eaa7d12f9eefd8358105076abfec3f4fbd0ac4ad22a3066208b5611127e3dfa6 | Python | 330 | 12 | import sys
import shutil
def shutil_rmtree(path, ignore_errors=False, onexc=None):
if sys.version_info >= (3, 12):
return shutil.rmtree(path, ignore_errors, onexc=onexc)
def _handler(fn, path, excinfo):
return onexc(fn, path, excinfo[1])
return shutil.rmtree(path, ignore_errors, onerror=... |
5aa14fdcd35522cd6163dd3705dbe9e4f079306f1480f46a6d5736d937bd2d99 | Python | 331 | 15 | from . import patch
from .data.constant import *
import sys
import logging
logger = logging.getLogger("")
logger.setLevel(logging.INFO)
format = logging.Formatter("%(asctime)-10s %(message)s", "%H:%M:%S")
handler = logging.StreamHandler(sys.stdout)
handler.setFormatter(format)
logger.addHandler(handler)
__version__... |
8423b3012340622aa5252a83c1e7b977bbf42280bf60394110c04d16040b62f2 | Python | 331 | 9 | """assemblyfire"""
from assemblyfire.version import __version__
from assemblyfire.config import Config
from assemblyfire.spikes import SpikeMatrixGroup
from assemblyfire.assemblies import Assembly, AssemblyGroup, ConsensusAssembly
from assemblyfire.topology import AssemblyTopology
from assemblyfire.syn_nnd import SynN... |
f907b49322b6bd02a2e4c3da5351dab8fbbd3c128cad48caafad2d6405818c55 | Python | 331 | 11 | from neuron import h
from nrn import *
load_hoc_obj=h
#self.hoc_obj.execute('load_file("'+str(self.model)+'")')
#self.hoc_obj.execute('load_file("stdrun.hoc")')
load_hoc_obj.load_file(str("hh_pas.hoc"))
load_hoc_obj.load_file("stdrun.hoc")
#self.vec=h.Vector
load_vec=load_hoc_ob... |
680c2034f4a7a9078da400d387f64e5c150406b35e6c03c75c4c9cee99b832b7 | Python | 332 | 5 | from deeplabcut.create_project.new import create_new_project
from deeplabcut.create_project.new_3d import create_new_project_3d
from deeplabcut.create_project.add import add_new_videos
from deeplabcut.create_project.demo_data import load_demo_data
from deeplabcut.create_project.human_dataset import create_pretrained_hu... |
6fd3bac315e13e9b7992aecfdab01a86954238c667649c3179ac91742a13bfcc | Python | 332 | 10 | #! /usr/bin/env python
from lab.parser import Parser
print 'Running axiom evaluation time parser'
parser = Parser()
parser.add_pattern('axiom_time_inner', r'AxiomEvaluator time in inner evaluate: (.+)', type=float)
parser.add_pattern('axiom_time_outer', r'AxiomEvaluator time in outer evaluate: (.+)', type=float)
par... |
fdd8e4802a5829d0f7049aabbac9a5b548d92732994a6377e1e3408c82450bee | Python | 332 | 15 | from cog import BaseModel, BaseRunner, Input
class Output(BaseModel):
text: str
score: float
tags: list[str]
class Runner(BaseRunner):
def run(
self,
prompt: str = Input(description="Input prompt"),
) -> Output:
return Output(text=f"generated: {prompt}", score=0.95, tags=... |
1a959bef57ab4d207f0382e01fa2ab2435591e551a29085621bb2b96852d6e66 | Python | 333 | 16 | import os
def main(*args, **kwargs):
i = 0
while os.path.exists("results{}".format(i)):
i += 1
os.mkdir("results{}".format(i))
os.system("mv allpara.yaml log.txt *err* *out* results{}".format(i))
os.system("cp input.yaml results{}".format(i))
print("Done!")
if __name__ == "__main__":... |
2baa608a07b6c82aaacf3a03ac5ed6bd61272b7e138053d41cb9107ed7c6a5b1 | Python | 333 | 8 | # regtools/gui - Shared GUI components
#
# Constants, widgets, and viewers used across all GUI tabs.
#
# Import directly from submodules:
# from regtools.gui.gui_constants import APP_STYLESHEET, ...
# from regtools.gui.widgets import MultiLineButton, DropButton
# from regtools.gui.gui_shared import auto_co... |
7c15e29b3d06022f7203f0c26b66dee467452b9f2f302b20c83382c128fb0670 | Python | 334 | 8 | #from deeplabcut.utils.make_labeled_video import *
from deeplabcut.utils.auxiliaryfunctions import *
from deeplabcut.utils.video_processor import *
from deeplabcut.utils.plotting import *
from deeplabcut.utils.conversioncode import *
#from deeplabcut.utils.frameselectiontools import *
# from deeplabcut.utils.auxfun_vi... |
88ccf3ac418cde7edcf61cc3c575ada6f67620f7f7586e79c139a9f9b75a7622 | Python | 334 | 10 | from .constants import BINARY_MODE, MULTICLASS_MODE, MULTILABEL_MODE
from .jaccard import JaccardLoss
from .dice import DiceLoss
from .focal import FocalLoss
from .lovasz import LovaszLoss
from .soft_bce import SoftBCEWithLogitsLoss
from .soft_ce import SoftCrossEntropyLoss
from .tversky import TverskyLoss
from .mcc i... |
a7fd2941ebe389d5b401cd3bdfbc74e0ea438554b61a29f82b03e5877d457b2a | Python | 334 | 8 | import inspect
from regtools.ccf_boundary_editor.viewer import CCFContourViewer
def test_dispatch_2d_atlas_uses_section_browse_not_section_prompt():
src = inspect.getsource(CCFContourViewer._dispatch_2d_atlas)
assert "load_2d_section_browse" in src
assert "getInt" not in src # no up-front section-... |
8ca2cda7423f5c34ab446423d807356c834e44231cfb0e7225cdc3a9b676f403 | Python | 335 | 8 | from pertpy.metadata._cell_line import CellLine
from pertpy.metadata._compound import Compound
from pertpy.metadata._cytokine import Cytokine
from pertpy.metadata._drug import Drug
from pertpy.metadata._look_up import LookUp
from pertpy.metadata._moa import Moa
__all__ = ["CellLine", "Compound", "Cytokine", "Drug", "M... |
dd56b3d1d3049b024623f63937a34fd2fbefc0b37941c213672f4d73750c4aa7 | Python | 335 | 11 | import warnings
from cog import ExperimentalFeatureWarning, Input, current_scope
warnings.filterwarnings(action="ignore", category=ExperimentalFeatureWarning)
def run(
text: str = Input(description="Example text input"),
) -> dict[str, dict[str, str]]:
return {"inputs": {"text": text}, "context": current_sc... |
0d086da3a5edbbcba2f86002032680dd06264af16a525886a973d1c570ec59b9 | Python | 336 | 3 | from data.ClinicalDatasets import PreopClassificationDataset, PreopSurvivalDataset, PostopSurvivalDataset, PostopClassificationDataset
from data.ImageDatasets import ImageClassificationDataset, ImageSurvivalDataset, ImageSegmentationDataset
from data.RadiomicsDatasets import RadiomicsClassificationDataset, RadiomicsS... |
74dba7ce86f686d284f59c31560ceaf1edf07381ab1ba1f379c8d945f4f0497a | Python | 336 | 13 | import dataclasses
import pytest
from elasticai.creator_plugins.quantized_grads.fixed_point import (
FixedPointConfigV2,
)
def test_two_complement_fixed_point_config_is_frozen():
config = FixedPointConfigV2(total_bits=8, frac_bits=2)
with pytest.raises(dataclasses.FrozenInstanceError): #
config... |
ebc699cd592aa5778369c6596c5ab597490171827a0cd7079a80677394bfc996 | Python | 336 | 21 | from memory_profiler import profile
f=open('hi.txt','w+')
@profile(stream=f)
def my_func():
a = [1] * (10 ** 6)
b = [2] * (2 * 10 ** 7)
del b
return a
@profile(stream=f)
def my_func1():
a = [2] * (10 ** 6)
b = [3] * (2 * 10 ** 7)
del b
return a
if __name__ == '__main__':
my_func(... |
f764da40a6e77c406b4cba6f4c4429b41e421e898cea3a5d963baeadb962fc2f | Python | 336 | 7 | # -*- coding: utf-8 -*-
from .biaffine import BiaffineSemanticDependencyModel, BiaffineSemanticDependencyParser
from .vi import VISemanticDependencyModel, VISemanticDependencyParser
__all__ = ['BiaffineSemanticDependencyModel', 'BiaffineSemanticDependencyParser',
'VISemanticDependencyModel', 'VISemanticDep... |
6bd0ea7e7facf6caa574d8f754fe14c4583882534a58966e6109509213cb1866 | Python | 337 | 17 | """
Logging utilities.
"""
import logging
LOGGER = logging.getLogger("qupat_processing")
def setup_logging(level):
"""Setup application logger."""
logging.basicConfig(
format="%(asctime)s;%(levelname)s;%(message)s",
datefmt="%Y-%m-%dT%H:%M:%S",
level=logging.WARNING,
)
LOGGER... |
22724ce21a06dfe08a04185d800741dce4b486989f03dc97bbdd7fbd457ac968 | Python | 338 | 15 | # Libraries
import os
import sys
code_path = os.path.split(os.path.split(os.getcwd())[0])[0]
sys.path.append(code_path)
from setting import *
from download_data import *
# Download
data_path = os.path.join(set_path(), "tcga")
database = "ttg"
cancers = ["all", ]
for cancer in cancers:
download_dataset(data_path, ... |
b0bdbf5b1f38a32b25a0b824056df4bcd1f730307212249c518cc53f09f8d305 | Python | 338 | 9 | __author__ = 'martinez'
__version__ = "$Revision: 001 $"
from .filters import vtkSurfBorderAlgorithm
from .filters import vtkClosestCellAlgorithm
from .filters import vtkAddAttributesAlgorithm
from .filters import vtkFilterSurfBorderAlgorithm
from .filters import vtkClosestPointAlgorithm
from .filters import vtkFilter... |
9ae19315fa2bdf3573921444162469132bad9ca7f08b961da30ad00d85494e89 | Python | 339 | 12 | import logging
def get_logger():
logger = logging.getLogger(name='DPS')
logger.setLevel(logging.INFO)
formatter = logging.Formatter("%(asctime)s [%(name)s] >> %(message)s")
stream_handler = logging.StreamHandler()
stream_handler.setFormatter(formatter)
logger.addHandler(stream_handler)
... |
6d1573a2cc0d762aa773165eab2116f53c17bc1cebdc6e28f2a9347b002be215 | Python | 340 | 9 | import pickle, sys
file = sys.argv[1]
trials = pickle.load(open(file, "rb"))
alldicts = trials.trials
loss = trials.losses()
for i in range(len(loss)):
print(str(int(alldicts[i]['misc']['vals']['leftpos'][0]))+'\t'+str(int(alldicts[i]['misc']['vals']['rightpos'][0]))+'\t'+str(loss[i])+'\t'+str(alldicts[i]... |
8ba35f10ffae3a93d2f8a94b394977d9a662c49ef9a8f2cdc425beab8b59aa07 | Python | 340 | 11 | """Geometry Registration - 2D slice-to-CCF registration via Agarwal's
edge/contour geometry-processing engine.
See README.md for architecture and attribution.
"""
from .types import RunParams, RunResult
from .pipeline import run
from .damage_aware import damage_mask
__all__ = ["RunParams", "RunResult", "ru... |
afe52751ef072e8e57149cfc8a74dc38e4e2bbfb313618076fa57094652594e2 | Python | 340 | 12 | from typing import List, Optional
def main(args: Optional[List[str]] = None) -> int:
"""This is preserved for old console scripts that may still be referencing
it.
For additional details, see https://github.com/pypa/pip/issues/7498.
"""
from pip._internal.utils.entrypoints import _wrapper
re... |
576aae5ae48a99803a8b65acbd00ab8e25823123432de63dbb353a46371159f0 | Python | 342 | 18 | from elasticai.creator.ir import attribute
from .default_handlers import dgraph_handlers as default_handlers
from .ir2torch import (
DataGraph,
Ir2Torch,
IrFactory,
get_default_converter,
)
__all__ = [
"DataGraph",
"Ir2Torch",
"get_default_converter",
"default_handlers",
"IrFactory... |
68c7b704b22d54e4d5a74e07b044d8b56b3c4d395a9addee33f9b3789ca5d3cb | Python | 343 | 11 | from pyntbci.tests.test_classifiers import *
from pyntbci.tests.test_eeg import *
from pyntbci.tests.test_gates import *
from pyntbci.tests.test_stimulus import *
from pyntbci.tests.test_stopping import *
from pyntbci.tests.test_transformers import *
from pyntbci.tests.test_utilities import *
if __name__ == "__main__... |
fbcac05f17bf4c43cd6fcb041b8193408022b0f716ddec84faf9b94aa635dfe0 | Python | 343 | 8 | from herdingspikes import probe
# from herdingspikes.parameter_optimisation import OptimiseParameters
from herdingspikes.hs2 import HSDetection, HSClustering, HSDetectionLightning
from herdingspikes.version import __version__, __commit__, base_version
__all__ = ["probe", "OptimiseParameters", "HSDetection", "HSClust... |
55ab625350072a1730666968402077acdd18f876e25b6ca9770937afab8fa9be | Python | 344 | 12 | from setuptools import setup
setup(
name="viper_clustering",
version="0.3",
description="Package to cluster ViPER triple assembly output.",
author="Lander De Coninck",
author_email="lander.deconinck@kuleuven.be",
url="https://github.com/Matthijnssenslab/ViPER",
packages=["viper_clustering"]... |
6e409c63793bcd6f6804bd7b5ec6466316083fca27ad66834e1896629e0bcfed | Python | 344 | 13 | from .model import MoleculeModel
from .mpn import MPN, MPNEncoder
from .attention import MultiBondAttention, MultiBondFastAttention, MultiAtomAttention, SublayerConnection
__all__ = [
'MoleculeModel',
'MPN',
'MPNEncoder',
'MultiBondAttention',
'MultiBondFastAttention',
'MultiAtomAttention',
... |
d550c96be7753ecede38c4cf162c793d6dd5ac0d3b5332ddd7ad7629935ba40f | Python | 344 | 17 | import pandas as pd
area = "output_and_income" # "consumption_and_orders", "prices", "output_and_income"
n_evaluate_targets = 19
past_horizon = 24
forecast_horizon = 3
train_test_split_period = pd.Period("2011-01-01", freq="M")
# Model Training
batch_size = 32
n_epochs = 50
patience = 10
# Model Parameters
n_featu... |
2c82c7c0c2ef8fd58170698a5401d6b32c446858aff49e8407db410cb0f6c3ff | Python | 345 | 26 | """"
Catalog example for testing analysis.catalog
# Author: Vladan Lucic
# $Id$
"""
#from __future__ import unicode_literals
__version__ = "$Revision$"
identifier = u'exp_3'
results_file = u'results_3.dat'
results_obj = u'results_3.pkl'
cleft_columns_obj = u'cleft_columns_3.pkl'
category = u'first'
feature = ... |
8756c43251aa341db61f2412c5b494a0bf7af3c1af7e39a209c8dac061efd0ec | Python | 345 | 8 | try:
import torch_geometric
except ImportError as e:
raise ImportError(
"To run the torcheeg with graph neural networks and related transforms, you need to install `torch_geometric`. Please refer to `https://pytorch-geometric.readthedocs.io/en/latest/notes/installation.html`."
) from e
from .vi... |
0d841affc0f7fe7985fe524135ddffd6c50ae3b32fc05e08d0a075c3bf11d8b1 | Python | 346 | 17 | # Module to simulate quantal data
from pyclamp.qnp.qsim import binoqsim
from pyclamp.dsp.iofunc import writeDTFile
outpath = '/tmp/bqa_test.tab'
e = 10.
n = 6
q = 100.
u = 0.1
v = 0.2
s = [0.2, 0.5, 0.8]
usegamma = [True, True]
num = 128
binom = binoqsim(e, n, q, u, v, 0.5, usegamma)
data = binom.simulate(num, s)
wri... |
0f4358a54016ddb44b962dbecc79b3505d91143a4e448103567551c42092f71f | Python | 346 | 10 | import sys
assert len(sys.argv) == 4, "Must have two input lists and one output list"
first = open(sys.argv[1], 'r').readlines()
first = [x.strip() for x in first]
second = open(sys.argv[2], 'r').readlines()
second = [x.strip() for x in second]
diff = list(set(first).difference(set(second)))
open(sys.argv[3], 'w').wr... |
a1cb422fdd26414ad18702705c4c461d2195f538cd0fb6481fa16f3848cdce3f | Python | 346 | 17 | from itertools import count
import os
def _try_remove(f):
try:
os.remove(f)
except OSError:
return False
return True
def cleanup_temporary_files(args):
_try_remove(args.sas_file)
_try_remove(args.plan_file)
for i in count(1):
if not _try_remove("%s.%s" % (args.plan_fil... |
d68b5390a9b04b833fd8a2acd61077e5addd725e49936b460f13ccf69724b685 | Python | 346 | 17 | import json
from helpers import network
def main():
import sys
with open(sys.argv[1], "r") as fid:
cfg = json.load(fid)
M = network.load_network(cfg["connectome"]["loading"])
network.override_connectivity(M, cfg["connectome"]["override"])
M.to_h5(cfg["connectome"]["save"])
if __name__ ... |
ef4a3683ffbd4adbe511fa3474e60100c19d1878b938f2cc95ff75ee385d8b38 | Python | 346 | 20 | # built-in
from math import isclose
# external
import pytest
# project
import textdistance
ALG = textdistance.bz2_ncd
@pytest.mark.parametrize('left, right, expected', [
('test', 'test', 0.08),
('test', 'nani', 0.16),
])
def test_similarity(left, right, expected):
actual = ALG(left, right)
assert ... |
19ef9eb73d6aa648b70840c0bcb3dd25969ba36161e9b5d36f3c9c0138e349fb | Python | 347 | 16 | # -*- coding: utf-8 -*-
import os
import subprocess
import sys
ROOT_DIR = os.path.dirname(__file__)
def _program(name, args):
return subprocess.call([os.path.join(ROOT_DIR, "bin", name)] + args, close_fds=False)
def obabel():
suffix = '.exe' if os.name == 'nt' else ''
raise SystemExit(_program('obabel... |
74e940a5547d54d1ddf075a3ffd49359f4e631ce76eb7b3f3b8b91795ffc97af | Python | 347 | 17 | import keras
from .models_factory import ModelsFactory
class KerasModelsFactory(ModelsFactory):
@staticmethod
def get_kwargs():
return {
'backend': keras.backend,
'layers': keras.layers,
'models': keras.models,
'utils': keras.utils,
}
Classifi... |
ed59e3863d08aa6a83f2a14a1b051a8fa2af0b04ff668357d00ee1bf8270b16b | Python | 347 | 20 | # built-in
from math import isclose
# external
import pytest
# project
import textdistance
ALG = textdistance.bwtrle_ncd
@pytest.mark.parametrize('left, right, expected', [
('test', 'test', 0.6),
('test', 'nani', 0.8),
])
def test_similarity(left, right, expected):
actual = ALG(left, right)
assert... |
82161c9b4e67b41ac079304e8b0a348c194717eb9e3130b8b0c42fe08ea606e6 | Python | 350 | 14 | """Init file."""
import logging
def get_logger() -> logging.Logger:
return logging.getLogger("ISMRMRD")
from .write_acquisition_to_mrd import write_acquisition_to_mrd
from .mrd_helper import get_nexus_acquisition_system, set_mrd_counters
__all__ = [
"write_acquisition_to_mrd",
"get_nexus_acquisition_sys... |
7dd79d7ef6184201c8df58fcf4fdab4b339a06f06592d8c8e6eb4f541d9ea05b | Python | 351 | 9 | try:
import torch_geometric
except ImportError as e:
raise ImportError(
"To run the torcheeg with graph neural networks and related transforms, you need to install `torch_geometric`. Please refer to `https://pytorch-geometric.readthedocs.io/en/latest/notes/installation.html`."
) from e
from .rgnn i... |
92af44386e7012eb114ac01866d16e3ea8ad97473098c28d42e8a26619fb2eb8 | Python | 351 | 8 | from trainer import Trainer
if __name__ == "__main__":
wandb_api_key = ""
train_class = Trainer(wandb_api_key, "config-128.yaml", "EMMA_Ferret_3M_shifted", 0, False)
train_class.run_model_pipeline(layer = 1, stream = 2)
#train_class.run_model_pipeline(layer = 1, stream = 2)
#train_class.run_model_p... |
e9f204f2a34c8d01d76da826a89f5b73678c616b47561b14337e95c950245342 | Python | 351 | 16 | from enum import Enum, auto
class OrbitalOccupationType(Enum):
'''Enum class for the different types of orbital occupancy in the data.'''
# general
NATURAL_ELECTRON_CONFIGURATION = auto()
LONE_PAIR = auto()
LONE_VACANCY = auto()
BOND_ORBITAL = auto()
ANTIBOND_ORBITAL = auto()
DONOR ... |
3076b430f0754548f6d962a824db405989e6512918440675d27535018734ec55 | Python | 353 | 9 | # """A collections of pre-defined VGG models."""
from .vgg_cifar10 import VGG_CIFAR10
from .vgg_cifar10_spike import VGG_CIFAR10_spike
from .cnn1_cifar10 import CNN1_CIFAR10
from .cnn1_cifar10 import WQ_CNN1_CIFAR10
from .cnn2_cifar10 import CNN2_CIFAR10
from .cnn1_cifar10_full import CNN1_CIFAR10_FULL
from .cnn2_cifa... |
375b7ebdb9029a75bd56dab2ff9d4d6c313fd6867361c5f60b3c270f7b0f4ff9 | Python | 353 | 15 | #! /usr/bin/env python
from lab.parser import Parser
class RawMemoryParser(Parser):
def __init__(self):
Parser.__init__(self)
self.add_pattern('raw_memory', r'Peak memory: (.+) KB', type=int, required=False)
if __name__ == '__main__':
parser = RawMemoryParser()
print 'Running RawMemoryPa... |
79a626e815aa0907d9711516ebf038e86b7b26450a6606d8bb70d88713285c31 | Python | 353 | 15 | import cv2
cv2.TrackerCSRT_create
try:
OPENCV_OBJECT_TRACKERS = {
"csrt": cv2.TrackerCSRT_create,
"kcf": cv2.TrackerKCF_create,
"boosting": cv2.TrackerBoosting_create,
"mil": cv2.TrackerMIL_create,
"tld": cv2.TrackerTLD_create,
"medianflow": cv2.TrackerMedianFlow_create,
"mosse": cv2.TrackerMOSSE_create
}
exc... |
7acf0428cbd78f9c93a087d0fa97f70efe539c879e33ab0c1342d6fa7e1e707a | Python | 353 | 17 | """
pygments.__main__
~~~~~~~~~~~~~~~~~
Main entry point for ``python -m pygments``.
:copyright: Copyright 2006-2023 by the Pygments team, see AUTHORS.
:license: BSD, see LICENSE for details.
"""
import sys
from pip._vendor.pygments.cmdline import main
try:
sys.exit(main(sys.argv))
except Ke... |
3165dd87eaf5970e13ee9289a33d672b306538370d0b97ec04afa73bfc825ac7 | Python | 355 | 9 | import pytest
from main import commands
@pytest.mark.parametrize("cmd", commands.values(), ids=list(commands.keys()))
def test_scripts_dry_run(cmd):
"""Just make sure all scripts work with dry run"""
# Just add some dummy arguments
args = {k:"" for k in cmd.script.__code__.co_varnames if k != "dry_run"}
... |
69bb72686e9080da9bc104ecffcab5ac95123ebefc6a410e2d88090d71e0b4b3 | Python | 355 | 20 | """
TextDistance.
Compute distance between sequences.
30+ algorithms, pure python implementation, common interface.
"""
# main package info
__title__ = 'TextDistance'
__version__ = '4.6.2'
__author__ = 'Gram (@orsinium)'
__license__ = 'MIT'
# version synonym
VERSION = __version__
# app
from .algorithms import * #... |
63e421eb391076edea4587cc179ae22cf4837da977b6037fcb40ff42bb627739 | Python | 356 | 15 | from language import load_input_language
def test_language():
lang1 = load_input_language("B1")
assert isinstance(lang1.get_word_by_id(2), str)
scene = lang1.get_scene_by_id(2)
assert isinstance(scene, tuple)
shape, angle = scene
print(shape)
print(angle)
assert isinstance(shape, int... |
7c954e8b5219834dcf04fa771388f9a3335754bc5d636a1d730daf90bf7b022c | Python | 356 | 11 | import protonets.data.geometry
def load(opt, splits):
# if opt['data.dataset'] == 'omniglot':
# ds = protonets.data.omniglot.load(opt, splits)
if opt['data.dataset'] == 'geometry':
ds = protonets.data.geometry.load(opt, splits)
else:
raise ValueError("Unknown dataset: {:s}".format(o... |
84b8671172248b63ac84ac7854a70f24e2d1ab7b34facfd9161e06047eed18c3 | Python | 356 | 13 | """Top-level package for m6A-calling."""
__author__ = """Mitchell Robert Vollger"""
__email__ = "mrvollger@gmail.com"
__version__ = "0.1.0"
from .m6a_cnn import *
from .m6a_supervised_cnn import *
from .m6a_semi_supervised_cnn import *
from .m6a_semi_supervised_cnn_predict import *
from .m6a_cnn_gen import *
from .m... |
1eba0a65914e01d428988ae6bb5e7eb54d01585aa3a0cd5f4ac0a502a6d05ac8 | Python | 357 | 16 | import logging as _logger
logging = _logger.getLogger('tensorlayer')
logging.setLevel(_logger.INFO)
_hander = _logger.StreamHandler()
formatter = _logger.Formatter('[TL] %(message)s')
_hander.setFormatter(formatter)
logging.addHandler(_hander)
def info(fmt, *args):
logging.info(fmt, *args)
def warning(fmt, *ar... |
8442d61f750dda29419ed7336e7d4124e233244a2213cc3d1fe82c4794deb849 | Python | 357 | 13 | from typing import List, Optional
__version__ = "23.2.1"
def main(args: Optional[List[str]] = None) -> int:
"""This is an internal API only meant for use by pip's own console scripts.
For additional details, see https://github.com/pypa/pip/issues/7498.
"""
from pip._internal.utils.entrypoints import... |
a7a87711b08b780d03f60e05d2c7e704b0d1c0e7a20725d4760a81670d8cc712 | Python | 358 | 10 | from collections.abc import Iterable, Iterator
from importlib import import_module as _import_module
from typing import Any
def import_symbols(module: str, names: Iterable[str]) -> Iterator[Any]:
"""import names from a module and yield the resulting objects."""
m = _import_module(module)
for name in set(n... |
1fd2f7df954998dc129b3ecb88e53b6d99e88d8f851bc4936c271de11ae2d03a | Python | 359 | 16 | """
Tests for geometry
# Author: Vladan Lucic (Max Planck Institute for Biochemistry)
# $Id$
"""
from __future__ import unicode_literals
from __future__ import absolute_import
__version__ = "$Revision$"
from .test_vector import TestVector
from .test_affine import TestAffine
from .test_affine_2d import TestAffine2D
f... |
2ffb70f8ab6cc6f65b29f9b1e0be39dac6896f15828f1b0d4d2345e8ccbbaaf4 | Python | 359 | 24 | """
Global variables for the package
"""
__author__ = 'martinez'
import numpy as np
MAX_FLOAT = np.finfo(float).max
NO_CONNECTION = -1
STR_2GT_EL = 'edge_length'
STR_CELL = 'cell_id'
STR_2FIL_LEN = 'fil_len'
STR_2FIL_CT = 'fil_ct'
STR_2FIL_SIN = 'fil_sin'
STR_2FIL_SMO = 'fil_smooth'
STR_2FIL_MC = 'fil_mc'
WR... |
b30a94ea39b6f4b6c7e2c9466b7513c5801a31408b3b33d8d6a4cc6b8b6fecf1 | Python | 359 | 14 | import sys
import importlib
__version__, _, _ = sys.version.partition(' ')
try:
# Allow Debian and pkgsrc (only) to customize system
# behavior. Ref pypa/distutils#2 and pypa/distutils#16.
# This hook is deprecated and no other environments
# should use it.
importlib.import_module('_distutils_sys... |
bc473126b18ecfa6675cb3547dd995c117f1740ae0219cfe185055bc30095f48 | Python | 359 | 13 | from .copula_graphic import CopulaGraphic
from .kaplan_meier import KaplanMeier, KaplanMeierArea
from .nelson_aalen import NelsonAalen
from .turnbull import TurnbullEstimator, TurnbullEstimatorLifelines
__all__ = [
"CopulaGraphic",
"KaplanMeier",
"KaplanMeierArea",
"NelsonAalen",
"TurnbullEstimator... |
f1f58b98e9665584f907fffc9ff3c8d98be9b30495917ff7f05878c1fcbd6d7a | Python | 360 | 8 | from .src.adder_range_violation import adder_range_violation as adder_range_violation
from .src.adder_ripple_carry_signed import (
adder_ripple_carry_signed as adder_ripple_carry_signed,
)
from .src.adder_ripple_carry_unsigned import (
adder_ripple_carry_unsigned as adder_ripple_carry_unsigned,
)
from .utils im... |
f8a7fdd3058faffdb4913ece2c2ec977755aa6e1d3362c2aafea2f7c158da9d7 | Python | 360 | 14 | MODEL_REGISTRY = {}
def register_model(model_name):
def decorator(f):
MODEL_REGISTRY[model_name] = f
return f
return decorator
def get_model(model_name, model_opt):
if model_name in MODEL_REGISTRY:
return MODEL_REGISTRY[model_name](**model_opt)
else:
raise ValueError("... |
a49e42e5d022b9468d2bc1a78da48671fea8cfb8f19ee5b89876d71d099f1ec2 | Python | 361 | 10 | import keras_applications as ka
from .__version__ import __version__
def get_submodules_from_kwargs(kwargs):
backend = kwargs.get('backend', ka._KERAS_BACKEND)
layers = kwargs.get('layers', ka._KERAS_LAYERS)
models = kwargs.get('models', ka._KERAS_MODELS)
utils = kwargs.get('utils', ka._KERAS_UTILS)
... |
61f66c7471951ecc0260153e3ba6e04ac89957d06cb70e953fc31b98b78f5c94 | Python | 362 | 9 | import pandas as pd
import pickle
data = pd.read_pickle("/Users/bguillouet/These/trajectory_review/data/extracted/starting_from/Caltrain_city_center_v3.pkl")
traj_list = [group[["lons","lats"]].values for _,group in data.groupby("id_traj")]
pickle.dump(traj_list, open("/Users/bguillouet/These/trajectory_distance/da... |
74c73692c5a3757493c344f36f35f715d4df4393ff8400a6dbf8dcc0a5af9b93 | Python | 362 | 8 | class BaseModel:
def __repr__(self):
"""A mixin implementing a simple __repr__."""
return "<{klass} @{id:x} {attrs}>".format( # pylint: disable=consider-using-f-string
klass=self.__class__.__name__,
id=id(self) & 0xFFFFFF,
attrs=" ".join(f"{k}={v!r}" for k,... |
33ca4f64928097535782dc3e352cd3fb50443401c98405857decadeb3aaef576 | Python | 363 | 10 | from napari_bil_data_viewer import napari_experimental_provide_dock_widget
from napari_bil_data_viewer.dataset_info import get_datasets
# Test that datasets return a dict
assert isinstance(get_datasets(), dict)
# Test whether dock widget is accessable
def test_provide_dock_widget():
assert [callable(x) for x in ... |
6fa39f21a4a8de42e41d2cb6260d52092251c6f9ad25127478875fd38c0c890a | Python | 363 | 14 | from __future__ import print_function
from openbabel import openbabel as ob
# Initialize the OBConversion object
conv = ob.OBConversion()
if not conv.SetInFormat('smi'):
print('could not find smiles format')
# Read the smiles string
mol = ob.OBMol()
if not conv.ReadString(mol, 'CCCC'):
print('could not read the s... |
badd4c7d51b3bb8195a2f9fc8746dac2fe6a3fdf92d74a30f88c4d0fbad01795 | Python | 363 | 14 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Jul 5 09:39:37 2021
@author: leupinv
"""
# Participants code
G_N = ['g01', 'g03', 'g08', 'g10', 'g11', 'g12', 'g15', 'g16', 'g17', 'g19', 'g23', 'g24',
'g25', 'g28', 'g32', 'g33', 'g34', 'g37', 'g38', 'g39', 'g40', 'g41', 'g42', 'g44', 'g45',
... |
41f2be0c48ac6fad092eedd206d6bfabbbe3be87fb5b6243a7d25d2d833aa4d1 | Python | 364 | 13 | from ._int_arithmetic import int_arithmetic
from ._int_converter import int_converter
from .fxp_arithmetic import FxpArithmetic as FxpArithmetic
from .fxp_converter import FxpConverter as FxpConverter
from .fxp_params import FxpParams as FxpParams
__all__ = [
"FxpParams",
"FxpArithmetic",
"FxpConverter",
... |
c6dd073e3dedb8001e62eac83138add8ef206d2ebc49025a05437bd41867c9c7 | Python | 365 | 9 | from .dist import get_rank
from .diff_config import find_config_diff
from .env_info import get_env_info
from .logger import create_logger
from .metric_logger import AverageMeter
from .metrics import compute_accuracy
from .op_count import count_op
from .tensorboard import DummyWriter, create_tensorboard_writer
from .uti... |
d8bad97f486df28ce34e90582d2c1eba230db76f17a8c198bdd1c44c8fef1ea9 | Python | 365 | 13 | #!/usr/bin/env python
#================================================================
# Copyright (C) 2022 Yufeng Liu (Braintell, Southeast University). All rights reserved.
#
# Filename : __init__.py
# Author : Yufeng Liu
# Date : 2022-04-01
# Description :
#
#======================... |
3a429bc2f94760426189c986d07ef336548386c609d62c93e30f5e2020c85d34 | Python | 367 | 15 | """Sequence constructor init file."""
from . import system_settings
from .calibration import fid_tx_adjust, se_tx_adjust
from .spectrometry import se_projection, se_spectrum, t2_relaxation
from .tse import tse_3d
__all__ = [
"fid_tx_adjust",
"se_tx_adjust",
"tse_3d",
"se_projection",
"se_spectrum",... |
81e3dc712e41477c6c04cb5869feb1919aa6e15f7a9298b832c232a3538174ae | Python | 367 | 7 | #!/usr/bin/env python
import sys, wget, os
for line in open(sys.argv[1]):
pdb,lig = line.rstrip().split()
print(pdb,lig)
fname = wget.download('https://www.rcsb.org/pdb/download/downloadLigandFiles.do?ligandIdList=%s&structIdList=%s&instanceType=all&excludeUnobserved=false&includeHydrogens=false'%(lig,pdb),bar=No... |
c7f524dfc0d2916e361e6b650747524c5b323374342dce70e4e514ea4005d8df | Python | 367 | 13 | #!/usr/bin/env python
# ================================================================
# Copyright (C) 2022 Yufeng Liu (Braintell, Southeast University). All rights reserved.
#
# Filename : __init__.py
# Author : Yufeng Liu
# Date : 2022-04-01
# Description :
#
# ====================... |
ec96e26a887ce59e80a97fbf714e63af6a4abc84f489e3b423ffa7df169db895 | Python | 367 | 12 | from __future__ import absolute_import, print_function, division
import torch
def set_num_threads(num_threads):
if num_threads < 0: # use all cores
from multiprocessing import cpu_count
num_threads = cpu_count()
if num_threads > 0:
# set number of threads in pytorch
torch.set_n... |
fb01e216d278a26682745055ac0cafb751e71c0eb446b46976d3cfc5a7fac08c | Python | 367 | 16 | """
Set of utilities for segmentation and analysis of n-dimensional images.
# Author: Antonio Martinez-Sanchez (Max Planck Institute for Biochemistry)
# Date: 02.04.14
"""
__author__ = 'martinez'
__version__ = "$Revision: 001 $"
from . import globals
from . import pexceptions
from . import disperse_io
from . import ... |
6563c63e9e4cdeaad43fc7092f14d0730e584996f5f325143348fb485a5221ce | Python | 368 | 14 | #!/usr/bin/env python
#================================================================
# Copyright (C) 2021 Yufeng Liu (Braintell, Southeast University). All rights reserved.
#
# Filename : tree_utils.py
# Author : Yufeng Liu
# Date : 2021-07-15
# Description :
#
#====================... |
562b5ec3c2e46d90e6abc11da2919c5e16c3eb47c5a218d4be2de46e9c74d0ce | Python | 369 | 14 | from wonambi import Dataset
from .paths import micromed_file
def test_dataset_events():
d = Dataset(micromed_file)
events = [ev['start'] for ev in d.read_markers()][::30]
data = d.read_data(events=events)
assert data.time[0].shape[0] == 512
assert data.time[0].shape[0] == data.data[0].shape[1]
... |
a3fe7e08dc188803fb67bea4fdde0a516beff878e423acaedd4cf7d9e9a06de8 | Python | 369 | 17 | #!/usr/bin/env python
#================================================================
# Copyright (C) 2022 Yufeng Liu (Braintell, Southeast University). All rights reserved.
#
# Filename : __init__.py
# Author : Yufeng Liu
# Date : 2022-11-10
# Description :
#
#======================... |
fce25abc86ce8e997646cef435b7b609cfa98fa727886bab601c94445ab3d0e3 | Python | 369 | 19 |
# read starting PDB, add unknown atoms, and fix up covalent geom, write out
# resulting PDB
inputPDB="rna_ini-allatom.pdb"
import protocol
protocol.loadPDB(inputPDB)
import regularize
regularize.addUnknownAtoms_new()
from regularize import fixupCovalentGeom
fixupCovalentGeom()
import os
base,ext = os.path.splitex... |
08fee60f0e6e69cbd7de3f06a8395f2b30557691882e7f56e5d98b1bb3f627ac | Python | 370 | 18 |
from config import MODEL_PATH
from watcher import Watcher
from restore_predict import restore
# adapt such that it works for all formats ('one-per-item', ...)
# restore commit in result.txt to ensure loading model parameters works
models = []
for i in range(10):
models.append(restore(MODEL_PATH + "model_fold{}.... |
17176d527de0d4bb5adf164e6457d90063d4d4c07e459cf0044772a66b900f3b | Python | 370 | 20 | """
Get expected value of loss of model before training
"""
NUM_OUTPUT_LOCS = 140
NUM_WF_PROBS = [0.6, 0.24, 0.12, 0.04]
#######################################
import torch
bce = torch.nn.BCEWithLogitsLoss()
y_hat = [0] * 10
y = [1, 0] * 5
y_hat = torch.tensor(y_hat, dtype=torch.float32)
y = torch.tensor(y, dtype... |
ace77733e1fd25b16675e6e415ce9d8e88c16deb0d98396cb31b0c4353ce451d | Python | 371 | 20 | """
Util directory module
# Author: Vladan Lucic (Max Planck Institute for Biochemistry)
# $Id$
"""
from __future__ import unicode_literals
from __future__ import absolute_import
__version__ = "$Revision$"
from . import nested
from . import attributes
from . import numpy_plus
from . import scipy_plus
from . import p... |
52110509d101fcf61f71273b8dcb71ae005e89dcbdb6de03693cc1d88e78f879 | Python | 372 | 13 | # Settings for base synapse parameters
params = {}
params["syn"] = {}
params["syn"]["AMPA"] = {"tau1": 0.5, "tau2": 2.4, "gpeak": 0.1, "e": 0}
params["syn"]["NMDA"] = {"tau1": 4, "tau2": 40, "gpeak": 0.1, "e": 0}
params["syn"]["GABAA"] = {"tau1": 1, "tau2": 7, "gpeak": 0.33, "e": -70}
params["syn"]["GABAB"] = {"t... |
48283e708f763cd17ccea9ec9e25e9cb9b8d553c08b64d958082309b52f3dff7 | Python | 373 | 12 | import torch
from torch import tensor
def generate_input_tensor_1d(in_channels, kernel_size, groups=1):
length = in_channels // groups * kernel_size
elements = tuple(tensor([-1.0, 1.0]) for _ in range(length))
return (
torch.cartesian_prod(*elements)
.reshape(2**length, in_channels // grou... |
b2f514b0fec3f3d6103d10e008e2a180d37d4aec89bdfd7326bad746872e831f | Python | 374 | 10 | from .amigos import AMIGOSDataset
from .bci2022 import BCI2022Dataset
from .deap import DEAPDataset
from .dreamer import DREAMERDataset
from .mahnob import MAHNOBDataset
from .seed import SEEDDataset
from .seed_feature import SEEDFeatureDataset
from .seed_iv import SEEDIVDataset
from .seed_iv_feature import SEEDIVFeatu... |
04ca2f2f96d59eb0f95b1b343a89cb2e5f64234fd939a367469951acbe05c4b5 | Python | 375 | 22 | import pytest
import jax
import time
@pytest.mark.parametrize(
"n_samples",
[
2,
4,
],
)
def test_jax_rng_generation(n_samples):
rng_key = jax.random.PRNGKey(time.time_ns())
rng_key, rng_subkey = jax.random.split(rng_key)
param = jax.random.uniform(
key=rng_key,
... |
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