sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
c20be3c9f4b7bf70077e1dec11f6f90bcad2b8eca8dac6ada1ff044a28ccedbc | Python | 191 | 8 | from pandas.tests.extension.decimal.array import (
DecimalArray,
DecimalDtype,
make_data,
to_decimal,
)
__all__ = ["DecimalArray", "DecimalDtype", "to_decimal", "make_data"]
|
62702d09bd36093cb24e81aea4db023e51c1a27721a60450e0120d204335cf95 | Python | 193 | 6 | from escargot.operations.thought import Thought
from escargot.operations.graph_of_operations import GraphOfOperations
from escargot.operations.operations import (
Operation,
Generate
)
|
26bc58dc411314a1801f85d11f85b0b80c9f71bb93402eee397530572b1ea45e | Python | 194 | 9 | import numpy as np
def one_hot(value):
num = '12345'
letter = [0 for _ in range(len(num))]
letter[value-1] = 1
letter = np.array([letter])
# print(letter)
return letter
|
45b42e7cf8ac0ee4b9b74a7b42ed6ee31b4d6fc06f17025cc970443476f6e264 | Python | 195 | 9 | import unittest
from api_tests import *
from event_tests import *
from gradient_tests import *
from norm_tests import *
from odeint_tests import *
if __name__ == '__main__':
unittest.main()
|
243b932e13acb7827967324e60b4a78453dace5b74c9ef5d03577ea721df12bc | Python | 196 | 4 | from .equiformer_v2_oc20 import EquiformerV2_OC20, EquiformerV2_OC20_Lightning
from .lr_scheduler import CosineLRLambda
__all__ = [EquiformerV2_OC20_Lightning, EquiformerV2_OC20, CosineLRLambda]
|
51030289ffe93bcdd36a882990ade8583a6ec789dbe6fe744b33527e81429352 | Python | 196 | 8 | __all__ = ['NOmniglot', 'nomniglot_full', 'nomniglot_nw_ks','nomniglot_pair','utils']
from . import (
NOmniglot,
nomniglot_full,
nomniglot_nw_ks,
nomniglot_pair,
utils
) |
0be6c06108c103c147b98a50e4f8d1e4e44426dee68b79e32d6d035571c4134a | Python | 197 | 5 | from .ctable import CTable
from .energies import HydrogenOptimizer
from .topology import ProteinData, ProteinDataBatch
__all__ = ["CTable", "HydrogenOptimizer", "ProteinData", "ProteinDataBatch"]
|
94638229488d9829313250d2db17a8744c40430149e9306aca09ec01fb88b81b | Python | 197 | 6 | """Writer classes for saving data to various formats."""
from ._ome_tiff import _OMETiffWriter
from ._tiff_sequence import _TiffSequenceWriter
__all__ = ["_OMETiffWriter", "_TiffSequenceWriter"]
|
b809e2b81c92e8154dfe89bcb5c873ae4e63df3f80214a8d91808d28c641379d | Python | 198 | 5 | from yass.explore.explorers import SpikeTrainExplorer, RecordingExplorer
__all__ = ['SpikeTrainExplorer', 'RecordingExplorer']
# TODO: check if matplotlib is installed, if not, show error message
|
4ed42143bff1e351493e15b786b43b682829d140a3f955d6c6e77471a62b5d47 | Python | 201 | 7 | from qcportal import PortalClient
import sys
dataset_name = sys.argv[1]
client = PortalClient('https://ml.qcarchive.molssi.org')
ds = client.get_dataset('singlepoint', dataset_name)
ds.print_status()
|
a9954ff3a94bbbdeb08b72be6fbad9554e8e738d16dd00816caa4625aff3edf5 | Python | 201 | 6 | """Readers for different file formats."""
from ._ome_zarr_reader import OMEZarrReader
from ._tensorstore_zarr_reader import TensorstoreZarrReader
__all__ = ["OMEZarrReader", "TensorstoreZarrReader"]
|
8f7ea94e4d5b7e3479d4264dfa6646fba3eb21489d42ea5479a124be7a4d9021 | Python | 202 | 10 | """Molecular vibrational systems"""
# Don't import scripts automatically to avoid running them
# Users should import explicitly if needed
__all__ = [
'vib_ch3cn',
'vib_clo2',
'vib_h2co',
] |
9d7462fbe4b7675da4e1fb415806a4be5fad63750cf5d1a8d1d2bb67510aa318 | Python | 202 | 8 | """
Original authors: https://github.com/alimuldal/diptest
The code under this module is a fork from the original project.
"""
from diptest._interface import dip, diptest
__all__ = ['dip', 'diptest']
|
a13b0dfe4ca1462ee11dd291ce2f4fcf04aeda01e213710fe0592e477d416453 | Python | 204 | 12 | import numpy as np
import pandas as pd
def test_contains_nan():
# GH#52840
arr = pd.array(range(5)) / 0
assert np.isnan(arr._data[0])
assert not arr.isna()[0]
assert np.nan in arr
|
ec12f1e249fdcb98a981f654599e32fcc2c450d817e8c4390f20f0b21849c553 | Python | 204 | 9 | from pandas.io.parsers.readers import (
TextFileReader,
TextParser,
read_csv,
read_fwf,
read_table,
)
__all__ = ["TextFileReader", "TextParser", "read_csv", "read_fwf", "read_table"]
|
669f37a3dd0fbd9e7a31b84d46bd4d6443d3a61a3b8d11dc2d888403d47f059c | Python | 205 | 9 | import pytest
@pytest.fixture(params=["split", "records", "index", "columns", "values"])
def orient(request):
"""
Fixture for orients excluding the table format.
"""
return request.param
|
78c8b12ebfc948fdd91f02422aa9449747d6c48303531591f6a296c5844131e9 | Python | 206 | 9 | #!/usr/bin/env python3
"""
Convenience wrapper to run antiSMASH directly from the source tree without installing.
"""
from antismash.__main__ import entrypoint
if __name__ == '__main__':
entrypoint()
|
d370bd69926223832f956b407b73e34b2994b47ae85ae5a0739881c8aa427c29 | Python | 208 | 9 | from hd5file import ascii_to_hd5
import sys
filename = sys.argv[1]
ascii_to_hd5 (filename,
add_reverse=False,
num_padding=0,
add_shape=False)
|
224624165d28d8b439aaeae86f0a0f829e23aa2dae294ee9868024de866d898a | Python | 209 | 7 | import numpy as np
class TestSeriesDtypes:
def test_dtype(self, datetime_series):
assert datetime_series.dtype == np.dtype("float64")
assert datetime_series.dtypes == np.dtype("float64")
|
8522ecf099b3e5aa9acae7a780927791d4f93f0369056a4aae6412762a67742f | Python | 210 | 8 | def _escape_inner(s: str, /) -> str:
return (
s.replace("&", "&")
.replace(">", ">")
.replace("<", "<")
.replace("'", "'")
.replace('"', """)
)
|
c77db9fc0c9fb823027489d029b83f88f439151fc434381d997f9d2111422a66 | Python | 210 | 7 | """Passive visualisation tools for browsing RELION cryo-ET data."""
from .tilt_series import view_tilt_series
from .tomograms import view_tomograms
from .particles import view_particles
from ._cli import cli
|
49c4a35e06f1ada356686f3b968793e68798b2624f3b7228f4f40643fbbcaea1 | Python | 211 | 2 | from .dataset import training_datasets, peak_dataset, wg_dataset, robustness_peak_dataset, robustness_wg_dataset
from .task import train_model, eval_model, eval_robustness, export_predictions, predict_snv_atac
|
bff00477f7aabde3eb1d0cb9fd9a0efc0d52275b259fe6b144bde70b388ceaec | Python | 211 | 9 | from monai.metrics import DiceMetric
import torch
def evaluation_metrics(config):
if config["metrics"] == "dice":
metrica = DiceMetric(include_background=True)#reduction="mean"
return metrica
|
c0bb5df434ac4f86fe88b6eeda853afe8608beb94468dc2fe089cac9f0c10e93 | Python | 215 | 8 | __version__ = "2.0.15"
import lib.tensor as tensor
import lib.mpcomplex as mpcomplex
import lib.smi as smi
from lib.mpunits import vectorize
from lib.designer_fit_wrappers import save_params
import lib.rpg as rpg
|
28d2cf7c16c864e3f12738626362aa7e274ab29dc9bc6afc95eefc13352d9726 | Python | 217 | 11 | # -*- coding: utf-8 -*-
'''
Python module to read common electrophysiology file formats.
'''
from .stfio import *
from . import stfio_plot as plot
try:
from . import stfio_neo as neo
except ImportError:
pass
|
c0d93b9be3e9b9fbb6baf4fe57134040757fec6b3926684c207e3f70785a7500 | Python | 218 | 14 | from numpy import argmax
import numpy as np
def one_hot(value):
num = '01'
letter = [0 for _ in range(len(num))]
letter[value] = 1
letter = np.array([letter])
return letter
# print(one_hot(4))
|
fe882560d891768ca2d655abe361ddc894cf75a79a7b2ee47de4365f6cb394fe | Python | 218 | 8 | from torchvision import transforms
def get_transforms():
return transforms.Compose([
transforms.Resize((224, 224)),
transforms.RandomHorizontalFlip(),
transforms.ToTensor(),
])
|
427a18556f36f13335eeeabedc42de7ad8599bc5cdd98d03904693737b0baf74 | Python | 219 | 16 | """ public toolkit API """
from pandas.api import (
extensions,
indexers,
interchange,
types,
typing,
)
__all__ = [
"interchange",
"extensions",
"indexers",
"types",
"typing",
]
|
690f141682b4ba229c35135bc37717e1ba71a8ea38e6625baa1b394a46748b33 | Python | 219 | 5 | from ._list_difficult_words import list_difficult_words
from ._set_difficult_words import set_difficult_words
from ._list_words import list_words
__all__ = ["list_difficult_words", "set_difficult_words", "list_words"]
|
2f79829d83d3a7302035f79d56eabd83bc4f59b7347353e8b7de24f6367d3692 | Python | 221 | 9 |
import collections
import numpy as np
def test_no_duplicates_in_np__all__():
# Regression test for gh-10198.
dups = {k: v for k, v in collections.Counter(np.__all__).items() if v > 1}
assert len(dups) == 0
|
dd04f290b6be5dc13ac55ee64d50cda04b9425c7b9279f570cd15862ce75bdfc | Python | 221 | 3 | from AttentiveFP.AttentiveLayers import Fingerprint
from AttentiveFP.AttentiveLayers_viz import Fingerprint_viz
from AttentiveFP.getFeatures import save_smiles_dicts, get_smiles_dicts, get_smiles_array, moltosvg_highlight |
f842b0687c30fb2adb9bb67977700dfca1135a65d8819d9d5ba287684da288b2 | Python | 221 | 7 | from pandas.core.arrays.arrow.accessors import (
ListAccessor,
StructAccessor,
)
from pandas.core.arrays.arrow.array import ArrowExtensionArray
__all__ = ["ArrowExtensionArray", "StructAccessor", "ListAccessor"]
|
0c45919786e8d1f38575f47561aaf89d534a6d944b35d8bc75fcd33d631fd6ad | Python | 222 | 9 | from ._reader import napari_get_reader
from .imc_widget import IMCWidget
try:
from ._version import version as __version__
except ImportError:
__version__ = "unknown"
__all__ = ["IMCWidget", "napari_get_reader"]
|
8928e1cd8c619d124b492be8f75520f8bf1d66d5a6c66ad582219da2f13ed2b2 | Python | 223 | 9 | import typer
CLI_NAME = 'relion_tomo_derive_particle_positions'
cli = typer.Typer(
name=CLI_NAME,
add_completion=False,
no_args_is_help=True,
help='Derive particle poses from annotations for refinement.'
)
|
3cad28e4abfe35d4753f13789bd5ae914885021a6414cf3b0078f2aee3ce0ae4 | Python | 225 | 12 | from rdkit.Chem.EState import Fingerprinter
import numpy as np
_type = 'Estate-based'
def GetEstateFPs(mol):
'''
79 bits Estate fps
'''
x = Fingerprinter.FingerprintMol(mol)[0]
return x.astype(np.bool_) |
cd55ea1b10c843e79bc7171eb48f4a709f591077880b8d3ce82a03bf273c08d3 | Python | 225 | 7 | """
Test files dedicated to individual (stand-alone) Series methods
Ideally these files/tests should correspond 1-to-1 with tests.frame.methods
These may also present opportunities for sharing/de-duplicating test code.
"""
|
55bd58a8bab7f35fa7529f158e483ac9c24ec4fddd57668ef578f2335ba17b64 | Python | 226 | 8 | from __future__ import annotations
from pandas.compat._optional import import_optional_dependency
ne = import_optional_dependency("numexpr", errors="warn")
NUMEXPR_INSTALLED = ne is not None
__all__ = ["NUMEXPR_INSTALLED"]
|
5f03cbe885845139856279bf2d8ba9b827be59ff05dfbf398828dcada773ccf3 | Python | 226 | 11 | """Functionality to process NIRS data."""
from .common import (
get_extinction_coefficients,
channel_distances,
split_long_short_channels
)
import cedalion.nirs.cw
import cedalion.nirs.fd
import cedalion.nirs.td
|
f3f3aa0737779320dddbeb99844c8e72c6df13e240c6f349213efa3a980987fb | Python | 226 | 6 | import muon as mu
import scanpy as sc
mdata = mu.MuData({"RNA": sc.read_h5ad(snakemake.input.merged_rna_anndata), "ATAC": sc.read_h5ad(snakemake.input.merged_atac_anndata)})
mdata.write_h5mu(snakefile.output.merged_multiome) |
7d4ce576b9f1bc510d86476e1d14d350d9375a849ecd3441d373c2765a3b8191 | Python | 227 | 7 | #replace the dictionary definition with one containing upper and lower bounds for each bounded input feature.
boundslist = []
for i in range(2401):
boundslist += [(0,2)] #each pixel has same limits
#boundsdict[0] = (0,1)
|
1b69d265a803b38fe1442cd26288c604e172534f362bb9235feb1fc70361bbeb | Python | 229 | 14 | from . import counts
from . import metrics
from . import selections
from . import transformations
from . import validations
__all__ = [
"counts",
"metrics",
"selections",
"transformations",
"validations",
]
|
33a7424b977be741737fd197ef1c8d91af92676c091422faeb2e63fa6a07870a | Python | 229 | 7 | """
Test files dedicated to individual (stand-alone) DataFrame methods
Ideally these files/tests should correspond 1-to-1 with tests.series.methods
These may also present opportunities for sharing/de-duplicating test code.
"""
|
27685021802f2fb83287c846f6bdd760f5faf652bb9c94b72081d99781444a3c | 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__ = ["from_dataframe", "DataFrame"]
|
3a03f20b5839591b2d5f43cb084980aac901954371388035c3a1cf2122095458 | Python | 230 | 7 | #replace the dictionary definition with one containing upper and lower bounds for each bounded input feature.
boundslist = []
for i in range(128*128):
boundslist += [(0,1)] #each pixel has same limits
#boundsdict[0] = (0,1)
|
7d8d6a8ba5031633d6d5be066b185c27db51010bba4972d920d77f572eb45d26 | Python | 231 | 7 | from collections.abc import Sequence
from typing import SupportsIndex, TypeAlias
_Shape: TypeAlias = tuple[int, ...]
# Anything that can be coerced to a shape tuple
_ShapeLike: TypeAlias = SupportsIndex | Sequence[SupportsIndex]
|
9a3590fc7afed60766b9b0d77d824b2331c2c2587d921b43bffa678509019ca6 | Python | 232 | 8 | ## python setup.py build_ext --inplace
from distutils.core import setup, Extension
from Cython.Build import cythonize
import numpy as np
setup(ext_modules=cythonize(["cyPoisson_sim.pyx"]),
include_dirs = [np.get_include()])
|
e02b66ce9af1269a9ac077ae71eca8bf7efb46c74a6e6e776a3356091aff49c6 | Python | 232 | 7 | #replace the dictionary definition with one containing upper and lower bounds for each bounded input feature.
boundslist = []
for i in range(128*128):
boundslist += [(0,255)] #each pixel has same limits
#boundsdict[0] = (0,1)
|
4114b951cb5560720d68b3fc55affed378d3039eaf539f073d82c9873cf7790f | Python | 234 | 10 | # Tests for MDAnalysis-calculated properties
# Properties to test: COM, position of ions/DNA/mRNA - make this general
#import pandas
#import numpy
#import pytest
#import sbmlcore
#def test_MDAnalysis_import():
#def test_pncA_COM():
|
ed5fcda3330032cf4c5735e6bfb24c155b64b66bf740a6940bab9f6f49abbd08 | Python | 235 | 9 | """Stub alternative CLI command for import_tilt_series job."""
from ._cli import cli
@cli.command(name='alternative', hidden=True)
def stub():
"""Stub for an alternative to SerialEM tomo metadata import_tilt_series."""
pass
|
0b390d9fab0093d8245d86b421e9abb0849722a71a22a336516bc68b6bb60b7f | Python | 237 | 11 | from . import ansatz
from . import blocks
from . import chems
from . import dataset
from . import graphs
from . import measurements
from . import conversions
from . import lattice
from . import hamiltonians
costfunctions = measurements
|
30684f6f245c8ab15783fb801b1c90feaf01932e99529059d271d741ae4b61df | Python | 238 | 9 | # ruff: noqa: TCH004
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"]
|
4ab1afda8799c5b2520143fea7dbca8555b2ce17e8c2317aab5fdcae99499c5d | Python | 238 | 8 | """kani-utils package."""
import importlib_metadata
try:
__version__ = importlib_metadata.version(__name__)
except importlib_metadata.PackageNotFoundError:
# package is not installed
__version__ = "0.0.0" # pragma: no cover
|
1d416fe2e9b28a9ef97a0b9bad5b9a1b9e8f17cf7b3a4e7e8d0fb29a79651d9f | Python | 240 | 14 | """
Created on Nov 22, 2024
@author: mning
"""
import pandas as pd
def fSum(df: pd.DataFrame, chnName: str, numEl: int):
tmpDF = df.filter(regex="(chnName)|*_Scale_*", axis="columns")
colNames = tmpDF.columns.values
return
|
664490d2429ff07aa0449791cf2876b1e3cbaa664916b5416fd41fa309cd13a0 | Python | 240 | 10 | import os
__version__ = "1.0.2.3-alpha.0"
DATA_DIR = os.path.dirname(os.path.realpath(__file__)) + "/data/"
STATIC_FILE = DATA_DIR + "waltzdb_export.csv"
SEQ_FILE = DATA_DIR + "Atomic.csv"
SEQ_MODEL_DIR = DATA_DIR + "models/sequential"
|
ad4c50c71cdb3e22a9df20c6c9ae83db1280ee5ba71922263859969a851c7b12 | Python | 240 | 14 | """
Created on Jun 5, 2024
@author: mning
"""
import logging
class logFilter(logging.Filter):
def __init__(self, level):
self.__level = level
def filter(self, logRecord):
return logRecord.levelno >= self.__level
|
1addbd325e13a0f48cf3c8f9e22bb8dd62adad4f40fa6a0fe1098c8a2ab379d5 | Python | 241 | 10 | """For when pip wants to check the date or time."""
import datetime
def today_is_later_than(year: int, month: int, day: int) -> bool:
today = datetime.date.today()
given = datetime.date(year, month, day)
return today > given
|
995c78e64683ee77e2239934db3e5633dd4ea447e15173acea0d734b45e00957 | Python | 241 | 9 | import numpy as np
import reza
fs = 100.0
t = np.arange(0, 10, 1/fs)
x = np.sin(2*np.pi*1.2*t) + 0.3*np.sin(2*np.pi*20*t) + 0.05*np.random.randn(t.size)
y = reza.bandpass(x, fs, 0.5, 5.0)
print("done", y.shape, "has_cpp=", reza.has_cpp())
|
e426e596df0f56266caa2a987cc752cfa6bf6c1501bb3b9743a17cb01b4a10c7 | Python | 241 | 10 | """module containing a test for testing"""
from unittest import TestCase
class TestTests(TestCase):
"""Test class for... tests..."""
def test_if_tests_work_ok(self):
"""you know the drill"""
self.assertEqual(1, 1)
|
04706940aa10bf81234f452958103e0a4e0be4eb0ca9323622e636e29fae7179 | Python | 242 | 11 | """Sub-package containing the matrix class and related functions.
"""
from . import defmatrix
from .defmatrix import *
__all__ = defmatrix.__all__
from numpy._pytesttester import PytestTester
test = PytestTester(__name__)
del PytestTester
|
307d8f6a1a5d8cb151faaddc63e0d4167dc1133cdc46434e6893cb382b18b0c3 | Python | 242 | 18 | '''
Created on 2018.8.29
@author: liangqian
'''
class Pitch():
'''
classdocs
'''
def __init__(self):
'''
Constructor
'''
self.name = ''
self.frequence = 0 #midi index number just now |
3e5d1e09baa1b69b69728736e08cd3e06c99fa31d034a28b15bdbe69289aed0f | Python | 243 | 4 | from .accuracy import accuracy, isfloat
from .meter import WeightedMeter, AverageMeter, TotalMeter
from .count_params import count_params
from .prepossess import mixup_criterion, continus_mixup_data, mixup_cluster_loss, intra_loss, inner_loss
|
5458e4eca6f4dc3f92cbd6525d41be3d4ca54d0f4531ed6c2e6527f297267ff8 | Python | 245 | 13 | # Re-export the tau-fitting API from internal module(s)
from .scripts.calculate_tau import (
fit_single_exp,
fit_single_exp_2d,
func_single_exp,
)
__all__ = [
"fit_single_exp",
"fit_single_exp_2d",
"func_single_exp",
]
|
9c05fe026e89a0bf64e77889fc28d927635c8c8a5acf6d47f3b9eb5b83a9d379 | Python | 246 | 5 | """
The application codebase is related to research and previous version of tensorcircuit,
the code inside is subject to change, be caution to use.
Most of the useful code is and will be refactored and copied to other parts of tensorcircuit.
"""
|
5d6df93b68f3ae4d4332ed17018ad988a6e30dcfcb0db42b92aacd10fb796f52 | Python | 247 | 10 | import torch
class ModuleListInfo(torch.nn.ModuleList):
def __init__(self, info_str, modules=None) -> None:
super().__init__(modules)
self.info_str = str(info_str)
def __repr__(self) -> str:
return self.info_str
|
a8243772c04107639121e25298b68408fefa6410dbe03189269c8dce592b7c99 | Python | 247 | 7 | """Passive visualisation tools for browsing RELION cryo-ET data."""
from .particles import combine_particle_annotations
from .spheres import derive_poses_on_spheres
from .filaments import get_poses_along_filament_backbones
from ._cli import cli
|
4a9d213f5adb46b2aced2e51977cb008f949b45fcc422f5b8645bc8ecc64673c | Python | 249 | 7 | """Example of how to save labeled images."""
from cali.util import save_labeled_images
db_path = "tests/test_data/data_and_db_for_tests/test_db.cali"
out = "/Users/fdrgsp/Desktop/cali_test/labels"
save_labeled_images(db_path, out, overwrite=True)
|
0b7385bb4346c03cd0e0b3a69923853ec452be46c19fe99d7788ffe58a89c3eb | Python | 250 | 13 | from ._implementation import (
CyclicDependencyError,
DependencyGroupInclude,
DependencyGroupResolver,
resolve,
)
__all__ = (
"CyclicDependencyError",
"DependencyGroupInclude",
"DependencyGroupResolver",
"resolve",
)
|
7b485ccea0a33218592e8303051440b8a34310c2967dd0820cc3263d4caf0fea | Python | 250 | 10 | """Randomized Watson Hamiltonian experiments"""
# Don't import scripts automatically to avoid running them
# Users should import explicitly if needed
__all__ = [
'fnn_compare',
'anharmonic_correction_sample',
'vib_random_hamiltonian',
] |
74d072d80d6300954df768d2e82154b1c29286273f0e565c38c08bdbdbd020d2 | Python | 253 | 9 | import mido
from midi_functions import clear_all_notes
# MIDI Output
midi_music_out = mido.open_output('IAC Driver Music Port')
midi_noise_out = mido.open_output('IAC Driver Noise Port')
clear_all_notes(midi_music_out)
clear_all_notes(midi_noise_out)
|
e2ab739cea0c99fecde2dfc527800d5fb2b0b539bf9f927cf188d4ec5c0d9843 | Python | 254 | 7 | """Contains benchmarking functionality"""
from .benchmark_data_loader import BenchmarkData
from .benchmark_metrics import BenchmarkMetrics
from .benchmark_output import OutputGenerator
__all__ = ["BenchmarkData", "BenchmarkMetrics", "OutputGenerator"]
|
f864c6d9552a929c7032ace654ee05ef26ca75d21b027b801d77e65907138b74 | Python | 254 | 10 | # SPDX-License-Identifier: MIT
# SPDX-FileCopyrightText: 2021 Taneli Hukkinen
# Licensed to PSF under a Contributor Agreement.
from typing import Any, Callable, Tuple
# Type annotations
ParseFloat = Callable[[str], Any]
Key = Tuple[str, ...]
Pos = int
|
feafce79671e734496d54ab61427f9a70fce71fd9d4cee9f77616830ba6309f5 | Python | 254 | 9 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Mar 28 22:52:40 2019
@author: sychoi
"""
vis_grayord_sigcorr(pval, rval, cf.outname, cf.out_dir, int(cf.smooth_iter), cf.save_surfaces, cf.save_figures, 'True', cf.bfp_path, cf.fsl_path) |
d64fd65af8d3f5e0c34433aeb735c279bbd82a6feacda400dc6b8b9345646c92 | Python | 255 | 8 | #
# This file is part of gunicorn released under the MIT license.
# See the NOTICE for more information.
from gunicorn.http.message import Message, Request
from gunicorn.http.parser import RequestParser
__all__ = ['Message', 'Request', 'RequestParser']
|
0f64697e48789a70190a45e0fc07872a4a8c3e62cd37ef6990c9ddbe7fa649e9 | Python | 256 | 12 | from dataclasses import dataclass
from typing import Optional
@dataclass
class RecordingConfig:
mode: Optional[str] = "Manual"
duration: float = 600.0
codec: str = "FMP4"
MODES = ["Manual", "Timed"]
CODECS = ["FMP4", "FFV1", "H264"]
|
0616b17f57d170301393e33def5261332a8ba1b1b7f6a2d35985e9f398f6bd20 | Python | 257 | 5 |
import os
ROOT_DIR = os.path.realpath(os.path.join(os.path.dirname(__file__), '../../../'))
DIAGNOSES = ["Pain", "Nausea/Diarrhea/Vomiting/Dehydration", "Anemia", "Neutropenia/Fever/Sepsis/Pneumonia"]
CLASSES = ["CLASS_1", "CLASS_2", "CLASS_3", "CLASS_4"] |
35a2d6fc94e228b82a3178a98eacf1167fb5c1d8a9b653b65b1381fca2b0c7de | Python | 257 | 8 | #
# This file is part of gunicorn released under the MIT license.
# See the NOTICE for more information.
version_info = (23, 0, 0)
__version__ = ".".join([str(v) for v in version_info])
SERVER = "gunicorn"
SERVER_SOFTWARE = "%s/%s" % (SERVER, __version__)
|
4a4560f9d12038316452a80cd23dcaddfd4870bfdb60b8b049d0fc226654f9a2 | Python | 257 | 17 | '''
Created on 2014.11.25
@author: Liang Qian
'''
#from tools import dbconnection as DB
from tools import exdata as Data
data = Data.EXDATA()
curneuronindex = 0
SynapseNumberPerDendrite = 40
ProximalDendriteNumerPerNeuron = 1
f = open('fire.csv','w')
|
a923f10fc72c8a663d5f6053578c721a45e37aaacb6e56e6c909c40632e70b1e | Python | 257 | 9 | from setuptools import setup
from Cython.Build import cythonize
import numpy
setup(
name="get_distances_utils",
ext_modules=cythonize("get_distances_utils.pyx", compiler_directives={'language_level': "3"}),
include_dirs=[numpy.get_include()]
)
|
029a7df0112b50c36b394308e0d89d0c0d5e254087ad8fa1985beed70e5ed9eb | Python | 259 | 11 | from dataclasses import dataclass
from typing import Optional
@dataclass
class CameraConfig:
camera_type: str = "Pylon"
camera_id: Optional[str] = None
config_file: Optional[str] = None
fps: float = 30.0
video_file: Optional[str] = None
|
649559a340dc5c3b55e81014b8f00a6f0315f1a19f6b324b53b2f0ea546605cc | Python | 259 | 10 | import pytest
from pandas import MultiIndex
def test_pickle_compat_construction():
# this is testing for pickle compat
# need an object to create with
with pytest.raises(TypeError, match="Must pass both levels and codes"):
MultiIndex()
|
c6808be525f29bcf69db22f3a529e565fd29cec992079ffbe4df6d82c5a7f220 | Python | 260 | 15 | """NQS for Vibrational Systems"""
from . import opt_tools
from . import nqs_vib
from . import Selected_Configs
from . import driver_ex
from . import vib_ham
__all__ = [
'opt_tools',
'nqs_vib',
'Selected_Configs',
'driver_ex',
'vib_ham',
] |
4d7dc691016df03dbf6fc06e61de8591e417b01ac5e47a84fa42fa97bbbdbb1b | Python | 262 | 8 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from smac.env.multiagentenv import MultiAgentEnv
from smac.env.starcraft2.starcraft2 import StarCraft2Env
__all__ = ["MultiAgentEnv", "StarCraft2Env"]
|
db9ca1bfa146f922947293d845d982edb4efc52f07992bb7e1a8be49d8caf190 | Python | 263 | 11 | from dataclasses import dataclass
from typing import Optional
@dataclass
class PoseConfig:
enabled: bool = False
pose_model: Optional[str] = "V1 - SuperScorer"
pose_device: str = "cpu"
GRIMACE_MODELS = ["V1 - SuperScorer", "Demo (Fake Mouse)"]
|
11c67baf8e84af4a0b96359245f51dae14331e3d957ecf3cb41adffaba9088f5 | Python | 265 | 7 | from __future__ import annotations
# the peak detection is based on scipy.signal.find_peaks
# https://docs.scipy.org/doc/scipy/reference/generated/scipy.signal.find_peaks.html
ECG_HEIGHT: float = 0.975
ECG_DISTANCE: float = 0.5
ECG_PROMINENCE: float | None = None
|
2b16c063ebecf8b0a1171b20ea5f0cc420ecedca321d3d19d992023458af73eb | Python | 265 | 9 | import torch
from models.UnetModel4 import UNet3D
def LoadModel(model_config, modelPath=None):
model = UNet3D(**model_config)
if not modelPath is None:
ckpt = torch.load(modelPath)
model.load_state_dict(ckpt['state_dict'])
return model
|
5ede3b41a7022b062bbb38c38be80e06aef6e0945e0e3f429bdc548b97ebfb7e | Python | 265 | 10 | from typing import Any
def load_ipython_extension(ip: Any) -> None: # pragma: no cover
# prevent circular import
from pip._vendor.rich.pretty import install
from pip._vendor.rich.traceback import install as tr_install
install()
tr_install()
|
f9c2d7be1cee422d1731f53e35da934008abb8dd0c53d03d1c4da0a28ed9cc94 | Python | 266 | 9 | from typing import Any
from pandas import Index
def allow_na_ops(obj: Any) -> bool:
"""Whether to skip test cases including NaN"""
is_bool_index = isinstance(obj, Index) and obj.inferred_type == "boolean"
return not is_bool_index and obj._can_hold_na
|
124c09b3c4b827703a3f18d9dc8706ed7e0f6ee8b840d2a9ef063fb424a65646 | Python | 267 | 11 | from .jaccard import calc_jaccard_pair, calc_jaccard_sets
from .adjacency import calc_ai_pair, calc_ai_lists
from .dss import calc_dss_pair
__all__ = [
"calc_jaccard_pair",
"calc_jaccard_sets",
"calc_ai_pair",
"calc_ai_lists",
"calc_dss_pair",
]
|
0db88494e21a35b6716c767a356e164178d6b5943316b28885403af27fc04919 | Python | 268 | 14 | """
Logger Utility helpers for CLI tasks.
"""
import logging
import sys
def setup_logging(level: int = logging.INFO):
logging.basicConfig(
level=level,
format="%(asctime)s [%(levelname)s] %(name)s: %(message)s",
stream=sys.stdout,
)
|
02b59342720a8710d568c2358f45a1829934722e9d3f49a95221b0311a8476d6 | Python | 270 | 15 | from pandas.io.json._json import (
read_json,
to_json,
ujson_dumps,
ujson_loads,
)
from pandas.io.json._table_schema import build_table_schema
__all__ = [
"ujson_dumps",
"ujson_loads",
"read_json",
"to_json",
"build_table_schema",
]
|
fe88fbe39278202b666d6664e90406548a7cbcbd93073a7e543936203a4ec6e8 | Python | 271 | 14 | from __future__ import annotations
import pytest
from textstat.backend import counts
@pytest.mark.parametrize(
"text,expected",
[
# TODO
],
)
def test_count_faseeh(text: str, expected: int) -> None:
assert counts.count_faseeh(text) == expected
|
4cae8e9ccae82e825fd4512a01cd6a56b6ac68a1d1c498deb7b34208d7454460 | Python | 272 | 13 | import random
import numpy as np
import torch
def setup(seed: int):
torch.backends.cudnn.deterministic = True
torch.backends.cudnn.benchmark = False
np.random.seed(seed)
torch.cuda.manual_seed_all(seed)
torch.manual_seed(seed)
random.seed(seed)
|
9c21ac62af491ba8f3a6f009dff47cffd369fcc2da4dff5146fdf4d422175bdc | Python | 272 | 10 | from typing import Optional
from app.config.video_files import VideoFilesConfig
class VideoFilesConfigValidator:
@classmethod
def validate(cls, video_files: VideoFilesConfig) -> Optional[str]:
if video_files is None:
return "Config is null"
|
b7d77b3d66d011c8ef6fc52d6295e3b90a0dc5add4a91113e0da06b1d5b8afbf | Python | 273 | 12 | """Contains modules for diagnostics"""
from .logger import init_logger, init_logger_file, DisableLogger
from .profiler import Profiler, calc_cpu_percent
__all__ = [
"init_logger",
"init_logger_file",
"DisableLogger",
"Profiler",
"calc_cpu_percent",
]
|
365bb10a2e6beb5ee7461bb235e36267d2fc3d4e2e0e88b5ecb8c4f2ecb4a634 | Python | 275 | 9 | # the dense layers for these multi outputs tasks
dense_layers_config = {
'ChEMBL': [1563], # 1310 outputs
'ToxCast': [1024], # 617 outputs
'PCBA': [256], #128 outputs
'MUV':[512], #17 outputs
'SIDER': [128], # 27 outputs
'Tox21':[256], # 12 outputs} |
53d855cf495383a5da4d11786d432062781ba7aa887b46c2b26717fe64ef90b7 | Python | 275 | 7 | #!/usr/bin/env python3.7
"""The copyrights of this software are owned by Duke University.
Please refer to the LICENSE and README.md files for licensing instructions.
The source code can be found on the following GitHub repository: https://github.com/wmglab-duke/ascent
"""
|
e3ceb9fadfbf50626a27170d9f7708484cbebd017cabb27e40ceb5cde512e02f | Python | 277 | 15 | from .scripts.spike_train_utils import (
bin_spike_train_fixed_len,
simulate_hawkes_thinning,
get_lv,
get_trials,
bin_trials,
)
__all__ = [
"bin_spike_train_fixed_len",
"simulate_hawkes_thinning",
"get_lv",
"get_trials",
"bin_trials",
] |
2b6ea1f798b67c0c91628aaa4b16fc11102973eaee26a8a6d3b923497e7c2529 | Python | 279 | 11 | from dataclasses import dataclass
from typing import Optional
@dataclass
class PoseTopConfig:
show_preview: bool = False
pose_model: Optional[str] = "V1 - GrimaceBoxTop"
pose_device: str = "cuda:0"
POSE_TOP_MODELS = ["V1 - GrimaceBoxTop", "Demo (Fake Mouse)"]
|
eca13d98b25ff53c7dd0631d2a3c47bb23abc5d672bd040a949876ff414bd7f5 | Python | 280 | 16 | """Contains enums for input parameters."""
# from python
from enum import Enum
class INPUT_MODE(Enum):
FLAT = "flat"
RECURSIVE = "recursive"
class RUN_MODE(Enum):
CLUSTER = "cluster"
QUERY = "query"
BENCHMARK = "benchmark"
DEREPLICATE = "dereplicate"
|
d6d95fb22dda35d22ee6b34bbb131db90e1ebf06ef1b8c2ca52ae59530985d48 | Python | 281 | 12 | """
Created on Oct 1, 2024
@author: mning
"""
from src.features.extract_entropy import extract_Entropy
# extract_Entropy(op_Band="alpha")
# extract_Entropy(op_Band="beta")
extract_Entropy(op_Band="broadband")
# extract_Entropy(op_Band="delta")
# extract_Entropy(op_Band="theta")
|
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.