sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
1c9e6b15a1c0f93b58099f21513ac1560539773c34f6d9b81db66911fcc34122 | Python | 166 | 3 | from .dpm_solver import DPMSolverDiffuser
from .general import VariancePreservingDiffuser, VarianceExplodingDiffuser
from .score_dynamics import ScoreDynamicsDiffuser |
5a32247c3e63e03c774154bafbe44b99ca7a154fa09d1aa97a29ba601ee63a72 | Python | 168 | 7 | def metapipeline(
pipelines: list,
close: bool = True,
adgile: bool =True
) -> None:
for p in pipelines:
p.pipeline(close=close, adgile=adgile)
|
a42c1fc8641d6b529858367149d9300bf9d434c9790e59723f53725e556e4dcd | Python | 169 | 3 | from .session import Session, SessionCollection
from .med_associates import parse_ma_session, parse_ma_directory
from .tdt import parse_tdt_session, parse_tdt_directory
|
2f2ed2a0418f48875114201c2263bf7b1ff06bc26bec35428f745ba05b9c4a04 | Python | 170 | 6 | # -*- coding: utf-8 -*-
# The standard library now has an interruptible pool
from multiprocessing.pool import Pool as InterruptiblePool
__all__ = ["InterruptiblePool"]
|
72c4f7872049399609ce454b430394a7cc5092fb6a9562fa2822811312668dec | Python | 170 | 9 | from setuptools import find_packages, setup
setup(
name='DXGB',
packages=find_packages(),
version='0.1.0',
author='Jianing Lu',
license='gpl-3.0',
)
|
13d7c7324a901372f276f4f8d21d06627b208321733e023000a6429aaa972a89 | Python | 171 | 6 | import pandas
import sys
df = pandas.read_csv(sys.stdin, sep=' ')
df[df["fdurGP"].notna()].to_csv(sys.stdout,sep=' ',index=False)
#df.dropna(thresh=1).to_csv(sys.stdout)
|
1bd6d7f4b160367808edc6e9ed0fb9e0677e350567cc74520be768828d0811b9 | Python | 172 | 7 | import sys
import pandas as pd
df = pd.read_csv(sys.stdin, sep=' ', keep_default_na=False)
gb = df.groupby('sentid')
for _, _df in gb:
print(' '.join(list(_df.word)))
|
592725317b77523cc3de79c09034fe53f2de2075a250d996d84fe0152bb05b38 | Python | 172 | 2 | from .mlp import build_mlp_model, build_lr_mlp_model, build_smlp_model, plot_mlp_model, PlotMLPCallback, MLPNetwork, MOVotingRegressor
from .al import CompositionGenerator
|
eb6d50c5d5765af3998a8812557c6f56b6576b001355e6079742b3e1be034080 | Python | 173 | 8 | # import stuff
from placerg.funcs import *
from placerg.funcsrg import *
from placerg.funcsall import *
from placerg.objects import *
from scipy.optimize import curve_fit
|
397da2a4400eb266cdceca30c427c3bc82c562e24eb4635c0d9e150e6ab1520e | Python | 174 | 6 | #!/usr/bin/env python3
"""Compatibility entry point; accepts the same options as run_end_to_end.py."""
from run_end_to_end import main
if __name__ == "__main__":
main()
|
5850bc40020935a6b50d7cdffb5ba59eb66f3b3a002302f1d4f7e53e83711ac8 | Python | 174 | 7 | """
Public API for function executor engines to be used with ``map`` and ``apply``.
"""
from pandas.core.apply import BaseExecutionEngine
__all__ = ["BaseExecutionEngine"]
|
bf317fe890a3b9807ab617043e8858d732d026a8d373b4e50c7c020190b90f8a | Python | 174 | 6 | __all__ = ['ModelBase', 'ModelEDNN3D', 'ModelStacked', 'ModelTwin']
from .ModelBase import *
from .ModelEDNN3D import *
from .ModelStacked import *
from .ModelTwin import *
|
e6038ddab94fd7ac31129920da283fee0224f4c7eff69d3fc1216a5ed6b8ceb7 | Python | 174 | 10 | """Gradec: Meta-analytic gradient decoding."""
from . import decode, fetcher, plot, segmentation
__all__ = [
"segmentation",
"decode",
"fetcher",
"plot",
]
|
ca778d5295eb9bfe01ed59b0eeb21f12a0a80f6076f1162fe45b8cb30e561e6e | Python | 175 | 4 | from evcouplings.complex.protocol import *
from evcouplings.complex.alignment import *
from evcouplings.complex.distance import *
from evcouplings.complex.similarity import *
|
08baedf081eb3adcfe56c1e9222d67cc71c4270a8c0b7b895b36854d308cd348 | Python | 177 | 7 | """Pre-built denoising algorithms."""
from mrpro.algorithms.denoiser.total_variation_denoising import total_variation_denoising
__all__ = [
'total_variation_denoising',
]
|
0f68350bf33ed333161c6d2ca0c3ca84dc8095858c8250badabec016c11bcb60 | Python | 177 | 10 | # -*- coding: utf-8 -*-
from collections import namedtuple
__all__ = ["Model"]
Model = namedtuple(
"Model", ("log_prob_fn", "compute_log_prob_fn", "map_fn", "random")
)
|
33d2a29dd1ef30da5e0eac3d090ac0abd33f064640f0fcbe7da1099791812ab2 | Python | 179 | 11 |
from __future__ import annotations
import os
import sys
sys.path.append('.')
sys.path.append('..')
sys.path.append('../../')
path = os.path.abspath(os.path.dirname(__file__))
|
fceb44f05fd0bde6cd82e0a5f17269254edd1ceba71c0e51ca3e5e3a60bf1d0e | Python | 179 | 8 | from . import config
from . import control
from . import data
from . import models
from . import server
from . import simulations
from . import timeseries
from . import utilities
|
2f77f2a38629f3f104e184140f7ea279c44b2837de40cff37bd93013e79e1563 | Python | 181 | 4 | """Module contains code for LDA analysis."""
# Define package version.
# This is read dynamically by setuptools in setup.cfg to determine the release version.
__version__ = "0.0.1"
|
ad7952953bf3c74f8907df22405c41faa274827758b2551b41ccc22ffd2216c1 | Python | 181 | 4 | from pycaret.internal.display.display import CommonDisplay, DummyDisplay
from pycaret.utils.generic import enable_colab
__all__ = ["CommonDisplay", "DummyDisplay", "enable_colab"]
|
be3d120a6feb0518d60940397434ad44c0f575093ac6304c84ad4f665a66d01a | Python | 181 | 8 | """Calling cards data analysis in Python"""
from pycallingcards.datasets._datasets import (
SP1_Cre_data,
SP1_K562HCT116_data,
mouse_brd4_data,
mousecortex_data,
)
|
fe059edc44b5cf3eeeafd85548fa53d1cc879bbc2f29375b055720f38376e358 | Python | 185 | 7 | import sys
import pandas as pd
df = pd.read_csv(sys.stdin, sep=' ')
network = int(sys.argv[1])
df = df[df.network == network]
df.to_csv(sys.stdout, sep=' ', index=False, na_rep='NaN')
|
ced5115a05136299eecf7b0798e1a9c0b5efdcfd9657b73c16660a836b78a208 | Python | 186 | 11 | import numba.cuda
def start_profiling(do_prof):
if (do_prof):
numba.cuda.profile_start()
def stop_profiling(do_prof):
if (do_prof):
numba.cuda.profile_stop()
|
e44a120b4906b611db259b71705da0032805c7d640d8760e3a99f48bfe7fe5a7 | Python | 186 | 11 | """Calling cards data analysis in Python"""
from pycallingcards.reading._read import (
combine_qbed,
read_barbodes,
read_qbed,
read_rna,
save_bed,
save_qbed,
)
|
48fa7d8391e2fef29ee37b0b914e70cbbee0ac49389dfaa169334650f11b294f | Python | 187 | 3 | from .modek_product import modek_product, modek_fold, modek_unfold
from .m_product import mprod, mtran, facewise, t_eye
from .transformation_matrices import dct_matrix, random_orthogonal
|
c787335b6cb0935e8164d1d1a5cc78f3299c680198629c64a958981fccfc56c2 | Python | 189 | 8 | # b2b_synchrony/__init__.py
from .EEG_device import EEG
from .bispectrum import bispec
from .stopwatch import timer
from .graphs import Graph
__all__ = ["EEG", "bispec", "timer", "Graph"] |
0efea898456a04dcdc8394830e15ff732cedf30623ab735bb92be6987ce8abc0 | Python | 191 | 8 | from pandas.tests.extension.decimal.array import (
DecimalArray,
DecimalDtype,
make_data,
to_decimal,
)
__all__ = ["DecimalArray", "DecimalDtype", "make_data", "to_decimal"]
|
92ea760fa71da70156e8a671e34eac161620ba5fa47e5826749fc35504322564 | Python | 191 | 8 |
import numpy as np
from skimage import morphology as morpho, io as skio, filters, util, measure
import tube2
import align
from cine import Cine
from sklearn.ensemble import IsolationForest
|
9b8175e6e2b88a4606de423cafe7f642435550bde2b97c36426a5b3f63cf235a | Python | 192 | 7 | __all__ = ['data', 'evaluation', 'test', 'utils', 'nn']
from windseer import data
from windseer import evaluation
from windseer import test
from windseer import utils
from windseer import nn
|
3d9873b5b1936972d33861d9daf73b9cfb10ec6d0f71a258fa8fa0e7e5e4fb0f | Python | 193 | 7 | """
Benchmarks in this directory should depend only on tslibs, tseries.offsets,
and to_offset.
i.e. any code changes that do not touch those files should not need to
run these benchmarks.
"""
|
8257de5841dcfa75a4449ca10d381cf41195d63f1172c4eed7195132c722200c | Python | 193 | 9 |
from pathlib import Path
from ecgdigitize.image import openImage
import ecgdigitize
image = openImage(Path('lead-pictures/002-49853179.png'))
print(ecgdigitize.estimateRotationAngle(image)) |
a1acab699f1655dea65e1083a38e2db2a626de6ebc109c3070253145ccc784b6 | Python | 194 | 5 | from evcouplings.align.alignment import *
from evcouplings.align.pfam import *
from evcouplings.align.protocol import *
from evcouplings.align.tools import *
from evcouplings.align.ena import *
|
fcc793aa23e4abc30178934cbe4052760eacf0ffc817ecc587c9260fc2940104 | Python | 195 | 11 | """Fixtures for CLI tests."""
import pytest
@pytest.fixture
def parser():
"""Full CLI argument parser."""
from lightning_pose.cli.main import _build_parser
return _build_parser()
|
060bb7530849fbb1786161fb779d80f62ae70c71e40283c9248f995b7264b78e | Python | 200 | 12 | import os
import sys
import matplotlib.pyplot as pl
import numpy as np
# sys.path.prepend(os.path.abspath(os.path.join(__file__, "..", "..", "..")))
# import emcee
def plot_acor(acorfn):
pass
|
7e24d47166292b1bf3277ff4128cd7947cf6abc80d3dde87336ccba6ba20552a | Python | 202 | 5 | from evcouplings.compare.ecs import *
from evcouplings.compare.distances import *
from evcouplings.compare.mapping import *
from evcouplings.compare.pdb import *
from evcouplings.compare.sifts import *
|
1281a5261d732b091b292a8279fb88722f9fd54128e6cc43e53dd56413f0b388 | Python | 203 | 9 | import sys
import configparser
config = configparser.ConfigParser()
config.optionxform = str
config.readfp(sys.stdin)
split_ids = config['data']['split_ids']
print(' '.join(split_ids.strip().split()))
|
9c42e48532ca3a491e78f247837f47f73b9d36d14470aaaafa99e51d336b56a7 | Python | 203 | 9 | # -*- coding: utf-8 -*-
from .aggregator import SumAggregator, ConcatAggregator, NeighAggregator
Aggregator = {
'sum': SumAggregator,
'concat': ConcatAggregator,
'neigh': NeighAggregator
}
|
556bcace8d28ae24e28a6c6e7b154ddb76e287b8775e579d4ef6adf9e44684fa | Python | 205 | 6 | """Public API for loading trained models and running predictions."""
from lightning_pose.api.model import Model
from lightning_pose.api.model_config import ModelConfig
__all__ = ["Model", "ModelConfig"]
|
0d44c7221ff36e22af4e61553b24d55cf81c6dfbfb3fe67f4cf2e24b70af4363 | Python | 206 | 4 | from .block_matrix import BlockMatrix # noqa: F401
from .dm_dataset import MatrixDataset # noqa: F401
from .dm_element import MatrixElement # noqa: F401
from .dm_filter import MatrixFilter # noqa: F401
|
0f85190ec558a5985192773b94301a19e75986fa56a6353fb8dd593ce969ab33 | Python | 208 | 8 | from .ecgdigitize import \
estimateRotationAngle, \
SignalDetectionMethod, \
SignalExtractionMethod, \
digitizeSignal, \
GridDetectionMethod, \
GridExtractionMethod, \
digitizeGrid |
510ce6e43bda9e737a586ebb0fc34535e0511d72a15404f7b44d0a84a11d3810 | Python | 210 | 4 | # MOFTransformer version 2.0.0
from moftransformer.datamodules import datamodule, dataset
from moftransformer.datamodules.dataset import Dataset
from moftransformer.datamodules.datamodule import Datamodule
|
cd6661ab6cb65a30e876fbc79c8445ce2eaaddbffa4401f41e6065a77e00fe38 | Python | 210 | 8 | #!/usr/bin/env python
# -*- coding: UTF-8 -*-
# Created by Roberto Preste
from mtoolnote.mtoolnote import annotate
__author__ = """Roberto Preste"""
__email__ = "robertopreste@gmail.com"
__version__ = '0.2.0'
|
06d5f7d30ebc402428bb4962cc43f56e75236f8b1000de5f1cff2fcfab380159 | Python | 211 | 11 | import datetime
__version__ = "0.6.0rc1"
__author__ = "Junshen Xu"
__copyright__ = f"{datetime.date.today().year}, {__author__}"
__email__ = "junshen@mit.edu"
__url__ = "https://github.com/daviddmc/NeSVoR"
|
2c9b89ba9704956ba8df2eddc24d7555db10e41c6dcc19c925bce8b9208d285b | Python | 212 | 5 | from .core import Pipeline # noqa: F401
from .dataslot import Dataslot # noqa: F401
from .filter import Filter # noqa: F401
from .filter_ray import FilterRay # noqa: F401
from .plot import Plot # noqa: F401
|
78404f09ad00f5ba143e64c5bc3770486945d67a67b1d9a7958a2c09d9308313 | Python | 213 | 9 | from .bias_field import n4_bias_field_correction
from .masking import (
brain_segmentation,
stack_intersect,
volume_intersect,
otsu_thresholding,
thresholding,
)
from .assessment import assess
|
e855535735c0eda4598b5da73d1c2f49ed39bbf8ce0e752f0f4a6604d5a15932 | Python | 214 | 9 | from brand import Booter
if __name__ == '__main__':
# parse command line arguments
args = Booter.parse_booter_args()
kwargs = vars(args)
# Run Booter
booter = Booter(**kwargs)
booter.run()
|
bf6cae03d5086519b72338c8fd8acacfdc89bcedb60827cc9fddfca5ea294985 | Python | 215 | 6 | class BaseLoader:
def read(f):
raise NotImplementedError("Reading is not implemented for this type")
def write(f, data):
raise NotImplementedError("Writing is not implemented for this type") |
97365d8c8c6bae3a5c183cbe8062c58c18c87ae66763ced78aae8edfe7ca5f82 | Python | 217 | 10 | # -*- coding: utf-8 -*-
# Import classes and functions from sub directory #
from sdna.net.core import *
from sdna.net.functional import *
# Add classes from directory #
from sdna.net.net import *
__all__ = ['Net']
|
c2bad9a9aef5f032259f8a68afa8a4474e32040b3497070958e13a368ed46347 | Python | 217 | 5 | from evcouplings.couplings.mapping import *
from evcouplings.couplings.model import *
from evcouplings.couplings.pairs import *
from evcouplings.couplings.tools import *
from evcouplings.couplings.mean_field import *
|
9885f1331d4f0ad5d08216bf72d0e9333fad89de8749d177feb403a1d57246a8 | Python | 218 | 6 | from .DropDownMenu import DropDownMenu
from .SelectPKLFile import SelectPKLFile
from .SelectSub import SelectSub
from .SelectSes import SelectSes
from .SelectAcqlab import SelectAcqLab
from .SelectROI import SelectROI
|
da0dbf06030c947479fd7b5d2677912c890422728ae63503a233868a8618ed55 | Python | 219 | 6 | from evcouplings.visualize.parameters import *
from evcouplings.visualize.pairs import *
from evcouplings.visualize.mutations import *
from evcouplings.visualize.misc import *
from evcouplings.visualize.pymol import *
|
8cc242cc569b1c363ff0f9b175ca155d42356ec2791c89d8984570631d3cfd5a | Python | 220 | 8 | from os.path import dirname, basename, isfile, join
import glob
modules = glob.glob(join(dirname(__file__), "*.py"))
__all__ = [
basename(f)[:-3] for f in modules
if isfile(f) and not f.endswith('__init__.py')
] |
1fd1a6233059023da65c4c766f6b99295805b39150b989afc6b87ffc3ac781a4 | Python | 221 | 7 | import warnings # suppresses plotnine warnings
warnings.filterwarnings('ignore')
from .heatmap import heatmap
from .gene_profile import gene_profile
from .n_es_genes import n_es_genes
from .save_as_pdf import save_as_pdf |
38af4f6481622751ab2e9a6528727a815e597e17b1db43ff6afbdd3b9657cdce | Python | 221 | 7 | from pandas.core.arrays.arrow.accessors import (
ListAccessor,
StructAccessor,
)
from pandas.core.arrays.arrow.array import ArrowExtensionArray
__all__ = ["ArrowExtensionArray", "ListAccessor", "StructAccessor"]
|
88c7f6f186f4d6440a8727d1e6331ce1c2644230320881d97bcf5194a8bb6b17 | Python | 222 | 8 | r"""
This package contains math utils for articulated body system including 3D rotation representation conversion,
spatial math, etc.
"""
from .general import *
from .angular import *
from .spatial import * |
1540accf5481c6d546964b63ea026e1c9ff3b66a0ae08a0dd0dbbc14eb435719 | Python | 225 | 7 | import sys
import pandas as pd
df = pd.read_csv(sys.stdin, sep=' ')
df['startofsentence'] = df.sentpos == 1
df['endofsentence'] = df.sentpos.shift(-1).fillna(1) == 1
df.to_csv(sys.stdout, sep=' ', index=False, na_rep='NaN')
|
fe6e7218cc6ed0136e9e93a13ea618ca2cea5f22a02b962ff4524cbc49e69897 | Python | 225 | 10 | """
This is a placeholder test to allow pytest to pass.
Without this pytest exits with non-zero exit code which fails the build.
"""
def test_always_pass():
"""A placeholder test that always passes."""
assert True
|
c02b8407a9c54cd8b234dfb421595183dd38e01c0d040a58b8ae4a857b2860c9 | Python | 226 | 6 | # License: see [LICENSE, LICENSES/legged_gym/LICENSE]
import os
LEGGED_GYM_ROOT_DIR = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
LEGGED_GYM_ENVS_DIR = os.path.join(LEGGED_GYM_ROOT_DIR, 'legged_gym', 'envs') |
52e29e4c5b2d7092014bad233df1aa4dd343bba84f1063574435b5cf4b544a22 | Python | 229 | 17 | import numpy as np
def linear(x):
return x
def linear_deriv(x):
return np.array([np.sum(np.eye(x.shape[0]), axis=0)]).reshape(2, )
def tanh(x):
return np.tanh(x)
def tanh_deriv(x):
return 1 - tanh(x) ** 2
|
f086547350cb747ee714749f80ae1cec4a1d6af86e2db2c89f519fbed5f31f9a | Python | 229 | 7 | from dataknead import Knead
# Convert from JSON to TOML
Knead("input/entity.json").write("output/entity.toml")
# Convert from TOML to JSON
Knead("input/example.toml").write("output/toml_example.json", indent = 4, default = str) |
0e82c5faab949d8d1a1db56086973b8d943d93ed13ad153fc56fedc3147a507e | Python | 230 | 4 | from .fully_connected import FullyConnected
from .resnet import ResNet, AntiSymmetricResNet, HamiltonianResNet
from .t_fully_connected import tFullyConnected
from .t_resnet import tResNet, tAntisymmetricResNet, tHamiltonianResNet
|
7ccdaafc400cc77f3b7d56840cd0ece09dd914129d1da940d020aad3659aedce | Python | 230 | 12 | from setuptools import setup
setup(
name='registration',
version='',
packages=['py-lddmm', 'py-lddmm.base', 'py-lddmm.Misc'],
url='',
license='',
author='younes',
author_email='',
description=''
)
|
e9bb6fa80f8713be7d545eec4cab77d4163e9975045952b2a9d889e9d6f2b415 | Python | 230 | 8 | """
Public API for DataFrame interchange protocol.
"""
from pandas.core.interchange.dataframe_protocol import DataFrame
from pandas.core.interchange.from_dataframe import from_dataframe
__all__ = ["DataFrame", "from_dataframe"]
|
e6dd08d9772d2dede155da1e26342446d029157fd3b3cd57bc303a4a43cfd492 | Python | 231 | 6 | from evcouplings.fold.tools import *
from evcouplings.fold.cns import *
from evcouplings.fold.filter import *
from evcouplings.fold.restraints import *
from evcouplings.fold.protocol import *
from evcouplings.fold.ranking import *
|
2f49cc37a8d98ea4c16ee9711986464325b2e1769a01665bdd2bb6d80da4bdb5 | Python | 232 | 4 | if __name__ == '__main__':
from .estimate_nexi_noiseless import estimate_nexi_noiseless
from .estimate_nexi import estimate_nexi
from .powderaverage.powderaverage import powder_average, save_data_as_npz, normalize_sigma
|
62fe1e5bc3ddd5e4b2d2f97b65ea6726d44d97d1021e37db5de1a3254bca34ec | Python | 233 | 13 | import sys
sentid=0
print('word sentid sentpos')
for line in sys.stdin:
sentpos=1
line = line.split()
for word in line:
print(word + ' ' + str(sentid) + ' ' + str(sentpos))
sentpos += 1
sentid += 1
|
ef76a404b5616dc79107341e8ca339c904735a40c362082cfbc431ea2ad3e6fa | Python | 234 | 10 | """
Timeseries API
"""
from pandas._libs.tslibs.parsing import guess_datetime_format
from pandas.tseries import offsets
from pandas.tseries.frequencies import infer_freq
__all__ = ["guess_datetime_format", "infer_freq", "offsets"]
|
94225f3292c4c6c7ad59b58b54fb004e9f108815ee872b25df5fe4764d05f7ec | Python | 235 | 7 | """Report generator for qc command.
"""
import os
from atropos.commands.legacy_report import LegacyReportGenerator
class ReportGenerator(LegacyReportGenerator):
template_path = os.path.join(os.path.dirname(__file__), 'templates')
|
e59f3c6ad10e5a7d1dee34f12f14bd3fec7d72d7e06150594c62a2bc51a4fec3 | Python | 235 | 9 | import sys
for line in sys.stdin.readlines():
sline = line.split()
for i in xrange(len(sline)):
if sline[i][0].isalnum():
sline[i] = sline[i].lower()
sys.stdout.write(' '.join(sline)+'\n')
|
b303432573df4365427cdcc65ba7bcb6b42b1ce176378d1ae993eba8555b41b1 | Python | 236 | 5 | from .log import auto_log
from .configs import PROJ_DIR, OUTPUT_DIR, MODEL_DIR, DATA_DIR, FIG_DIR, SAVE_DIR
from .cache import obj_to_version, load_cache, save_cache, cache_return
from .data import load_data, load_model, augmente_data
|
0bd65766297124b889f7003c2a95406e9d39e866123eec61489f8ae479dd5e0a | Python | 237 | 7 | from trainers.cnn_trainer import CNNTrainer
from models.cnn.model import CNN
from models.neural_main import neural_main
from models.cnn.args import get_args
if __name__ == '__main__':
neural_main("CNN", CNN, CNNTrainer, get_args())
|
592d05615bd7a71524449c6d3d9af0dbdfa8e06aace81a3c2e9a928c411874c2 | Python | 237 | 7 | """Report generator for trim command.
"""
import os
from atropos.commands.legacy_report import LegacyReportGenerator
class ReportGenerator(LegacyReportGenerator):
template_path = os.path.join(os.path.dirname(__file__), 'templates')
|
721508df388bfc8c6499255325aa7da267b7a5d2e0374dfcc5e782009ec72d57 | Python | 237 | 9 | # ruff: noqa: TC004
from typing import TYPE_CHECKING
if TYPE_CHECKING:
# import modules that have public classes/functions
from pandas.io.formats import style
# and mark only those modules as public
__all__ = ["style"]
|
d4ee5a730b59d6198fb659c46e63f6eba7fa22ded987ab6f402174a48386236e | Python | 238 | 17 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Nov 2 17:02:44 2021
@author: jeanbaptiste
"""
VALID_TRANS_CHANNELS = ['Trans']
VALID_FLUO_CHANNELS = [
'CFP',
'DAPI',
'GFP',
'RFP',
'YFP'
] |
32151123b9f567bebe873a86103d2c578eeba315e70522fab2bc00e867ca2ca3 | Python | 240 | 9 | """
ScanOMetrics: python package for personalized brain image analysis
"""
_version_major = 0
_version_minor = 1
_version_micro = 1
_version_pre = ''
__version__ = '%d.%d.%d%s' % (_version_major,_version_minor,_version_micro,_version_pre)
|
35877f120164cb0dbe89e2e21e81e39ad61488b5c1b19760157cf099b245329f | Python | 240 | 10 | # flake8: noqa
from .alpha import estimate_alpha, read_alpha
from .p_c import estimate_p_c, read_p_c
from .p_e import (
estimate_p_e,
estimate_p_e_control,
estimate_p_e_nasc,
read_p_e,
)
from .pi import estimate_pi, read_pi
|
165f9d4976e0d8129987fe5edc5a2f84c4c5b76a588c291c0827cb8e8724d6e1 | Python | 242 | 5 | # MOFTransformer version 2.0.0
from moftransformer.utils.prepare_data import prepare_data
from moftransformer.utils.install_griday import install_griday, uninstall_griday
__all__ = ["prepare_data", "install_griday", "uninstall_griday"]
|
5594d93d978b73a19e51834a7251ab6a86c70267322b3a02291244115e029357 | Python | 242 | 12 | # AUTOGENERATED! DO NOT EDIT! File to edit: nbs/00_core.ipynb (unless otherwise specified).
__all__ = []
# Cell
import os
import numpy as np
import torch
import random
import pkg_resources
from rxnfp.models import SmilesClassificationModel |
8d75095c8ec1b5640434bb4a6a08986797f8ee58c2099c1fa10edf961b0b05eb | Python | 243 | 13 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Apr 13 12:19:36 2020
@author: reisertm
"""
from .model import *
from .crop_generator import *
from .improc_utils import *
from .customLayers import *
from .Augmenter import *
|
c60252e80582b65e8c1b321a0f59d5bbce6229d1ea705122d1963f3c4101838d | Python | 245 | 7 | from trainers.lstm_trainer import LSTMTrainer
from models.lstm.model import LSTM
from models.neural_main import neural_main
from models.lstm.args import get_args
if __name__ == '__main__':
neural_main("LSTM", LSTM, LSTMTrainer, get_args())
|
de0db4264ec31bb499ed6990d80d68362ad5e4122f100dbef60856ebaa59622b | Python | 247 | 17 | #! /usr/bin/env python
import random
from sys import argv
infile=argv[1]
k=int(argv[2])
L = []
with open(infile,"r") as f:
for line in f:
L.append(line.rstrip())
L1 = random.sample(L,k)
for item in L1:
print(item)
|
529ae9b23b46ed1c62293c72ca0cdb829f6463fe7abe12e34884504352ddc494 | Python | 248 | 11 | from setuptools import setup, find_packages
setup(
name="sbrnet_core",
version="0.1",
packages=find_packages(),
install_requires=[],
author="Jeffrey Alido",
author_email="jalido@bu.edu",
description="Sbrnet project",
)
|
727517cd657cbcacb63d43cd7a204a6d3ae25b491202189830d7963180c3fa44 | Python | 248 | 13 | import sys
sys.path.append('.')
from CommonSystem.Config import Config
from UICreator.UIFactory import UIFactory
config = Config()
config.stiLEN=1
factory = UIFactory(config)
frames = factory.getFrames()
factory.saveFrames(frames)
|
f6666719b999400f395ce9f530a07e8572d955a3ba84d87b33435a3ce79ec7b1 | Python | 249 | 9 | __all__ = [
'HDF5Dataset', 'interpolation', 'generate_turbulence', 'process_dataset', 'utils'
]
from .generate_turbulence import *
from .HDF5Dataset import *
from .interpolation import *
from .process_datasets import *
from .utils import *
|
e66c194f47b9ae8638a40b62786ac63dd000464ee8eedd695511a728b8281702 | Python | 250 | 7 | import matplotlib as mpl
from .cumulative import plot_cumulative_events
from .raster import plot_event_raster
# set some matplotlib parameters
mpl.rcParams['pdf.fonttype'] = 42 # turn on true-type fonts, provides better editing of PDF/Illustrator
|
066ddbbc00cbd5e43aabc0a7c381fe7936e4433bad6a27645d143a1ffa829699 | Python | 251 | 7 | from models.bert.args import get_args
from models.bert.model import BERT
from datasets.scar_bert import SCARBERT
from models.transformer_main import transformer_main
if __name__ == '__main__':
transformer_main("BERT", BERT, SCARBERT, get_args())
|
67ba0ac1c08550017f8f7a5f7616d3a7f71789bebe093fa8e31baddc6cd499ab | Python | 251 | 10 | import sys
import pandas as pd
df = pd.read_csv(sys.stdin, sep=' ')
gb = df.groupby("docid")
for _, df_doc in gb:
print("!ARTICLE")
gb_sent = df_doc.groupby("sentid")
for _, df_sent in gb_sent:
print(' '.join(list(df_sent.word)))
|
aaf9ff883265b6f525b0ebdbf44a1bef80c48f5365b1d169b613fda0b0e76aa9 | Python | 251 | 8 | from dataknead import Knead
def parse(data):
books = data["catalog"]["book"]
data["catalog"]["book"] = [b for b in books if b["author"] == "O'Brien, Tim"]
return data
Knead("input/books.xml").apply(parse).write("output/obrien-books.xml") |
ef0c355c80de9a5a31fe80328d6cac03fa448178fc0a3570177ee8a297a9e1df | Python | 251 | 7 | from biophysics_fitting.setup_stim import setup_BAC
def BAC_injection(cell, dist = None):
'''
This injects the BAC stimulus as defined in Hay et. al. 2011 at a specified distance.
'''
setup_BAC(cell, dist = dist)
return cell |
ac244c7534baceeb429b8b953778bebae100766b83151f0c1b18902ff22285fe | Python | 253 | 4 | from .mouse_ens_to_human_ens import mouse_ens_to_human_ens
from .mouse_symbol_to_mouse_ens import mouse_symbol_to_mouse_ens
from .human_ens_to_human_symbol import human_ens_to_human_symbol
from .human_symbol_to_human_ens import human_symbol_to_human_ens |
e3bad2e1dea523857c63965684c61c478890570697dfe2ca54385123ab13ea05 | Python | 253 | 11 | """Smoke tests for the multimodal_ad package foundation."""
import multimodal_ad
def test_version_is_set() -> None:
assert multimodal_ad.__version__ == "0.1.0"
def test_package_importable() -> None:
assert multimodal_ad.__doc__ is not None
|
6e56db2ff0edf049802108cd679af9442c7c5af7aaed4c822d4aaa3a8d4b93f8 | Python | 254 | 14 | #!/usr/bin/env python
"""
File: __init__.py
Date: 5/1/18
Author: Jon Deaton (jdeaton@stanford.edu)
Brain Tumor Segmentation 2018 Data Set
"""
import warnings
warnings.simplefilter(action='ignore', category=FutureWarning)
from BraTS.DataSet import *
|
451cbfb0d086c9d6c3d80600bdb18560679139da97fa772608c3684fa078aaae | Python | 255 | 9 | import numpy as np
from .meshes import Mesh
class ImageVarifold():
def __init__(self, source=None, weights=None, image=None):
super(ImageVarifold, self).__init__(mesh=mesh, weights=weights)
if image is not None:
self.ima
|
68564b0ee7636207d19ade0cc82d3de72d6dc8599107ab9fce1b2b4f1141cf42 | Python | 256 | 9 | """
Copyright (c) Facebook, Inc. and its affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""
from .mri_data import SliceDataset
from .volume_sampler import VolumeSampler
|
4ed618e46dbb38bdef1d76669e1429ca82790c4a763be6a8bb4d6de96dd53577 | Python | 258 | 9 | from os.path import dirname, basename, isfile, join
import glob
from .MFGEcoliDataset import MFGEcoli
modules = glob.glob(join(dirname(__file__), "*.py"))
__all__ = [
basename(f)[:-3] for f in modules
if isfile(f) and not f.endswith('__init__.py')
] |
5601cbd8983eec9434e4a49ccae7ca3edd02c97802125a8c60051539d13cc2a8 | Python | 258 | 9 | from .helper import (
relative_image_difference,
dotproduct_adjointness_test,
operator_isometry_test,
linear_operator_unitary_test,
autodiff_test,
gradient_of_linear_operator_test,
forward_mode_autodiff_of_linear_operator_test,
)
|
7cf69becc50a56368ff8c485745ee92f6376e892c0bedf4fd5bb196015297b2c | Python | 258 | 7 | from shapeout2 import util
def test_get_valid_filename():
assert util.get_valid_filename("KLµ123$)]") == "KLu123-))"
assert util.get_valid_filename("..KLµ123$)].") == "KLu123-))"
assert util.get_valid_filename(". KLµ123$)]") == "_KLu123-))"
|
fdbf480b7c0789f1c4b553e61232c8e98c9a2cc0c3371a1760dc10aeb4566fc3 | Python | 258 | 11 | from setuptools import find_packages, setup
REQUIREMENTS = [i.strip() for i in open("requirements.txt").readlines()]
setup(
name="src",
packages=find_packages(),
version="0.1.0",
python_requires=">=3.9",
install_requires=REQUIREMENTS
)
|
53e091a1656721d12a872bb479c9ed64e58ab349a2f6cace9ce25e33912002a0 | Python | 260 | 14 | __all__ = ['save_json', 'load_json']
import json
def save_json(data, file, **kwargs):
with open(file, "w") as f:
json.dump(data, f, **kwargs)
def load_json(file, **kwargs):
with open(file, "r") as f:
return json.load(f, **kwargs)
|
d3cdce19dbee40a997281033f137bc69ee1c7fdfb0e8cdfc0d62fb9b02c96c65 | Python | 262 | 15 | """
.. module:: tool_common
:platform: Linux, Windows
:synopsis: Common constants used by tools
.. moduleauthor:: Fredrik Nysjo
"""
TOOL_PLANE_X = 0
TOOL_PLANE_Y = 1
TOOL_PLANE_Z = 2
TOOL_MODE_2D = 0
TOOL_MODE_3D = 1
TOOL_OP_ADD = 0
TOOL_OP_SUBTRACT = 1
|
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