sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
f82f0e2bbaf19f7b0851d570c59041a5e1e12335f4788f9533731e9987da5e6d | Python | 351 | 16 | from typing import List, TypeVar
T = TypeVar("T")
class Stack(List[T]):
"""A small shim over builtin list."""
@property
def top(self) -> T:
"""Get top of stack."""
return self[-1]
def push(self, item: T) -> None:
"""Push an item on to the stack (append in stack nomenclature)... |
69fea3d5ba1d41881197e19b1b598f4848766c29661f64ab5b53bce04a075f84 | Python | 352 | 7 | from asap.models.vanilla_cnn import VanillaCNN
from asap.models.recurrent import CNN_LSTM
from asap.models.dilated_cnn import DilatedCNN
from asap.models.convnext_transformer import ConvNextTransformer
from asap.models.convnext_cnn import ConvNeXtCNN
from asap.models.convnext_lstm import ConvNeXtLSTM
from asap.models.c... |
c9651c17539a5d37c48d7a226d0b04f051fe38db93034a1d24657626c4d89c57 | Python | 352 | 12 | """Readers for different file formats."""
from ._ome_zarr_reader import OMEZarrReader
from ._tensorstore_zarr_reader import TensorstoreZarrReader
from ._tiff_collection_reader import TiffCollectionReader, TiffCollectionSettings
__all__ = [
"OMEZarrReader",
"TensorstoreZarrReader",
"TiffCollectionReader",
... |
5ab9dda527ba8b57245ff490d4a6b10fd093286cc3d04b82385c5c6f0169a0b5 | Python | 353 | 17 | """
pygments.__main__
~~~~~~~~~~~~~~~~~
Main entry point for ``python -m pygments``.
:copyright: Copyright 2006-2025 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... |
bd22eaa8927dd7ea973b3e6d5e368f9f08f94c3073f948e7f08ef298d99dbed0 | Python | 353 | 13 | from __future__ import annotations
__version__ = "25.3"
def main(args: list[str] | None = 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 _wr... |
176a970a22cf66ec561c4647da25a122a8d153d8e4019d596d57642e3f4be4dc | Python | 354 | 11 | from .transformer import GraphTransformer
from omegaconf import DictConfig
from .brainnetcnn import BrainNetCNN
from .fbnetgen import FBNETGEN
from .BNT import BrainNetworkTransformer
def model_factory(config: DictConfig):
if config.model.name in ["LogisticRegression", "SVC"]:
return None
return eval(... |
e88e08cbe1b679b9a357f7018add7cb0fe2cd1247b691ca38f030d205fc4d457 | Python | 355 | 16 | from pathlib import Path
conf_template = Path(__file__).with_name("conf.py.in")
namespace = {
"__file__": str(conf_template),
"__name__": "__main__",
}
rendered = conf_template.read_text(encoding="utf-8").replace(
"@PACKAGE_VERSION@",
"dev",
)
exec(compile(rendered, str(conf_template), "exec"), names... |
516c9dab4459982c3c65b52f13faab670ff158d2792819d0d42a8215c010b774 | Python | 356 | 14 | from __future__ import annotations
from typing import TYPE_CHECKING, Any
from pymmcore_widgets import InstallWidget
if TYPE_CHECKING:
from qtpy.QtWidgets import QWidget
class _InstallWidget(InstallWidget):
def __init__(self, parent: QWidget | None = None, **kwargs: Any) -> None:
super().__init__(pa... |
8b0bd5a9ad861bd4e362b775af10818dd2de19006846a50ed9f66720b1256d98 | Python | 356 | 19 | from pandas.core.arrays.sparse.accessor import (
SparseAccessor,
SparseFrameAccessor,
)
from pandas.core.arrays.sparse.array import (
BlockIndex,
IntIndex,
SparseArray,
make_sparse_index,
)
__all__ = [
"BlockIndex",
"IntIndex",
"make_sparse_index",
"SparseAccessor",
"SparseA... |
93c351881797681000547148dba53e613cb803fb42f089dc4de9c1380fd85fbb | Python | 356 | 11 | from .registry import model_entrypoint
from .graph_attention_transformer import *
# from .graph_attention_transformer_md17 import *
# from .graph_attention_transformer_oc20 import *
from .dp_attention_transformer import *
# from .dp_attention_transformer_md17 import *
# from .dp_attention_transformer_oc20 import *
#... |
90d6d9bfd9e36bd88b5661995360fac3676a0769ddb1ba937dcb19b06cff628d | Python | 357 | 17 | """
Public API for Rolling Window Indexers.
"""
from pandas.core.indexers import check_array_indexer
from pandas.core.indexers.objects import (
BaseIndexer,
FixedForwardWindowIndexer,
VariableOffsetWindowIndexer,
)
__all__ = [
"check_array_indexer",
"BaseIndexer",
"FixedForwardWindowIndexer",
... |
2d2bb327d3ac434204a56dab2a5030baf372a597836740090e824eb7ddd707e9 | Python | 359 | 11 | def __getattr__(attr_name):
from numpy._core import numeric
from ._utils import _raise_warning
sentinel = object()
ret = getattr(numeric, attr_name, sentinel)
if ret is sentinel:
raise AttributeError(
f"module 'numpy.core.numeric' has no attribute {attr_name}")
_raise_warnin... |
ae64a672131f3a15fc48e99342a4283c842abfe76599d99c4bf422f1cc753350 | Python | 360 | 13 | from braincog.base.node.node import *
from braincog.base.connection.layer import *
from braincog.base.strategy.surrogate import *
class MyGrad(SurrogateFunctionBase):
def __init__(self, alpha=4., requires_grad=False):
super().__init__(alpha, requires_grad)
@staticmethod
def act_fun(x, alpha):
... |
068aeb2bcfd925b3791d67085fd7c23fe05b4c2689b20006522cdae48c2162be | Python | 361 | 13 | import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
@pytest.mark.parametrize("na", [None, np.nan, pd.NA])
def test_setitem_missing_values(na):
arr = pd.array([True, False, None], dtype="boolean")
expected = pd.array([True, None, None], dtype="boolean")
arr[1] = na
tm.ass... |
74d066e0c38cdc41d8bd5d5284b17a30ddfde00caa6613e93e581b92ec0de242 | Python | 366 | 14 | from .physunits import Quantity, units
import cedalion.dataclasses
import cedalion.dataclasses.accessors
from cedalion.bibliography import Bibliography
from ._version import __version__
# singleton container that collects references
bib = Bibliography()
def cite(key: str) -> None:
"""Record that a method with t... |
b7636a230ddd92c1bd5d90b3dfe423c2d1421c16c51485b64caa57119affe5b8 | Python | 368 | 19 | # YOLOv5 🚀 by Ultralytics, GPL-3.0 license
"""
Perform test request
"""
import pprint
import requests
DETECTION_URL = "http://localhost:5000/v1/object-detection/yolov5s"
IMAGE = "zidane.jpg"
# Read image
with open(IMAGE, "rb") as f:
image_data = f.read()
response = requests.post(DETECTION_URL, files={"image":... |
943c0762063cbd75772464c5e7c6fc6ac23bacf6c72e46f420bb985244280c24 | Python | 369 | 15 | # -*- coding: utf-8 -*-
import json
def save_dict(filename, dic):
'''save dict into json file'''
with open(filename, 'w') as json_file:
json.dump(dic, json_file, ensure_ascii=True)
def load_dict(filename):
'''load dict from json file'''
with open(filename, "r") as json_file:
... |
3f7d78d8019447d21f1b2beebb86e9fd18910710dd2f284c303f7868ed1fcaa2 | Python | 370 | 18 | '''
Created on 2016.7.6
@author: liangqian
'''
from Modal.pitch import Pitch
class Note():
'''
Because a chord consist of more than two pitches at the same time, so using
arrays to record the chord
'''
def __init__(self):
self.pitches = []
# self.startTime = []
# self.endTim... |
9645ebbb97e87715fccb33a6b8e2520dafcb24e750f4deda25332b71227c0860 | Python | 371 | 15 | import torch
from torch import nn
class SimilarityLoss(nn.Module):
""" Computes BYOL's simple similarity loss"""
def __init__(self):
super(SimilarityLoss, self).__init__()
def criterion(self, x, y):
x = nn.functional.normalize(x, dim=-1, p=2)
y = nn.functional.normalize(y, dim=-... |
ec06934ca2425bbb8d759b7a675275fd37a60de0d011ac8775328ce8d978bf7c | Python | 371 | 10 | from setuptools import setup, find_packages
setup(
name="rna3db",
version=1.1,
description="A dataset for training and benchmarking deep learning models for RNA structure prediction",
author="Marcell Szikszai",
packages=find_packages(exclude=["tests", "scripts", "data"]),
install_requires=["bio... |
bb7cfbd664ceb86b1c50ec91c0fa627bee9a23a1380e3a1a6ab72c2615d12517 | Python | 372 | 11 | # Yet another wild way to do this, but way easier than
# trying to configure things within each app/cli to find
# the test data... Plus it lets users play with it a bit more
import aims_immune
import os
import shutil
def getit():
aims_dir = aims_immune.__file__[:-11]
startDir = os.getcwd()
shutil.copytree(... |
307a321d6993d436762090b2b4494181a9ef0bb8293d6a67abe5cc138c08c84a | Python | 373 | 18 | from typing import TypeVar, List
from app.dataflow.qqueue import IQueue
T = TypeVar('T')
class QueueForker(IQueue):
def __init__(self, queues: List[IQueue]):
self.queues = queues
def enqueue(self, item):
for queue in self.queues:
queue.enqueue(item)
def close(self):
... |
2f99d9c32190bece6862c211388029a2fedf8517b5876d59e15886d092903e68 | Python | 376 | 14 | """
A quick script to output the top N words (500 for now) in each language.
You can send the output to a file and diff it to see changes between wordfreq
versions.
"""
import wordfreq
N = 500
if __name__ == '__main__':
for lang in sorted(wordfreq.available_languages()):
for word in wordfreq.top_n_list(l... |
1ff7531ef09acd103424e5489d185193060b459c532cc579cf1032199c4f5157 | Python | 378 | 9 | """Tools for plotting collective events."""
__author__ = """Benjamin Graedel"""
__email__ = "benjamin.graedel@unibe.ch"
__version__ = '0.3.3'
from ._plotting import LineagePlot, NoodlePlot, dataPlots, plotOriginalDetrended, save_animation_frames, statsPlots
__all__ = ["plotOriginalDetrended", "dataPlots", "statsPlot... |
83aca1002101873c5ab9312d54532bfca8f03b1e66d8cc4e7a58bb798369bdcd | Python | 379 | 12 |
import cedalion.io
import cedalion.data
from cedalion.dataclasses.schemas import validate_stim_schema
def test_read_events_from_tsv():
bids_top_level_directory = cedalion.data.get_multisubject_fingertapping_path()
for fname in bids_top_level_directory.glob("**/*_events.tsv"):
stim = cedalion.io.read_... |
ddd297ce3d96caf7bd219ae51a3c3b3a08445b37ac7c2e3cd87066c975427e82 | Python | 379 | 11 | from crystal_tracer.algorithm.tracking import independent_match
import pickle
import pandas as pd
from pathlib import Path
if __name__ == '__main__':
df_folder = '../data/detection'
frames = [pd.read_csv(p) for p in Path(df_folder).glob('*.csv')]
res = independent_match(frames)
with open('../../data/ca... |
26174d9e77acd4055fe24201723ffb0ffe81ed3a6ce0fc88efaa3a9532827627 | Python | 380 | 17 | from saveman import (connectivity, connectivity_umap, gradients)
from saveman.analyses import (reference, measures, eccentricity, adaptation,
seed, behaviour, rsa, fpca)
connectivity.main()
connectivity_umap()
gradients.main()
reference.main()
measures.main()
eccentricity.main()
adaptati... |
4dda33433c1367366c5e5cce30829a4144af9c14a2b3cfc5e4907d6f6a4d1341 | Python | 380 | 14 | from openai import AzureOpenAI
def get_embedding(api_key,api_base,api_version,deployment_name, text_to_embed):
client = AzureOpenAI(
api_key=api_key,
api_version=api_version,
azure_endpoint = api_base
)
response = client.embeddings.create(
model=deployment_name,
inpu... |
3c73371c0c41bf21552b781f2451653cbb1c693fd2a27105cda03ced237e650e | Python | 381 | 13 | from click.testing import CliRunner
from cardio_audio_sleep.commands.main import run
def test_main():
"""Test the main package entry-point."""
runner = CliRunner()
result = runner.invoke(run)
assert result.exit_code == 0
assert "Entry point to start the tasks." in result.output
assert "Option... |
61298418d8c6fb6de2f82c58cbcc52211bb366dbba2a0da2ed0e78d1770bd102 | Python | 382 | 17 | """Usage: python run.py --config-name path-to-config"""
import hydra
from nablaDFT.pipelines import run
from nablaDFT.utils import init_wandb, load_envs
from omegaconf import DictConfig
@hydra.main(config_path="./config", config_name=None, version_base="1.2")
def main(config: DictConfig):
load_envs()
init_wa... |
6098a1672b6cb3e315369ae9e29e6900bfde99e0b9a5bde1070b5a4b7c8c09c5 | Python | 384 | 13 | import numpy as np
from pandas import date_range
import pandas._testing as tm
class TestSplit:
def test_split_non_utc(self):
# GH#14042
indices = date_range("2016-01-01 00:00:00+0200", freq="s", periods=10)
result = np.split(indices, indices_or_sections=[])[0]
expected = indices._... |
0a558ba6b30985fea891436ef405fa02bf485d980a918d2736e0f31d13bbd079 | Python | 385 | 14 | import numpy as np
from pandas import DataFrame
from pandas.tests.copy_view.util import get_array
def test_get_array_numpy():
df = DataFrame({"a": [1, 2, 3]})
assert np.shares_memory(get_array(df, "a"), get_array(df, "a"))
def test_get_array_masked():
df = DataFrame({"a": [1, 2, 3]}, dtype="Int64")
... |
f969cdd0796a886f513e07353ff2922d9bea810e301980dfd2515cc9f58e2dfb | Python | 385 | 15 | from . import util
import numpy as np
class TestF2Cmap(util.F2PyTest):
sources = [
util.getpath("tests", "src", "f2cmap", "isoFortranEnvMap.f90"),
util.getpath("tests", "src", "f2cmap", ".f2py_f2cmap")
]
# gh-15095
def test_gh15095(self):
inp = np.ones(3)
out = self.mod... |
4c92da30fda289eeac32ea96244ad7db8ede26096dcfaa5db78c254c3376ad76 | Python | 386 | 21 | from __future__ import annotations
from pyphen import Pyphen # type: ignore
import pytest
from textstat.backend import utils
@pytest.mark.parametrize(
"lang",
[
"en_US",
"en",
"es_ES",
"es",
"de_DE",
"de",
"fr_FR",
],
)
def test_get_pyphen(lang: st... |
22d79fafd729a40988a23919dc99dec7ee9b3da0a60deb009dcb865e4af88470 | Python | 388 | 14 | from setuptools import setup
from pip._internal.req import parse_requirements
requirements = parse_requirements('requirements.txt', session=False)
install_requires = [str(req.requirement) for req in requirements]
setup(
name='chronognosis',
version='0.1.0',
author='onnonuro',
packages=['chronognosis']... |
d27c02a94d7f61e0926520175aa6e73f1f6c2c9a1412fe7b2780baf18b1a213b | Python | 389 | 24 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sun Aug 25 20:29:36 2019
@author: charleshen
316 Estate Index descriptors
"""
from mordred import Calculator, descriptors
import numpy as np
_calc = Calculator(descriptors.EState)
_EstateNames = [str(i) for i in _calc.descriptors]
def GetEstate(mol):... |
8c8a1021c9b0d6ec98e57e8364422a2ee6aea0932be127396d76178ecbf12973 | Python | 390 | 17 | from bermol.trainer import BerMolPreTrainer
import numpy as np
path = ""
predictor = BerMolPreTrainer.load(path)
def smi_feature(smi: str) -> np.ndarray:
output = predictor.transform([smi])
pooled_output = output[0][1]
return pooled_output.cpu().detach().numpy().reshape(-1)
smi = "Cc1nc2c(c(-c3ccc(Cl)... |
6286b5e4f0c7e083f31408705b4e2b0b275eb958aedf6a858dfe82f22229b9d8 | Python | 391 | 18 | import wave
import struct
import os
import numpy as np
f = 440
framerate = 44100.0
fw = wave.open("sine.wav","wb")
fw.setnchannels(1)
fw.setframerate(framerate)
fw.setsampwidth(2)
tt = np.arange(0, 1, 1.0/framerate)
data = [2000*(np.sin(2*np.pi*f*t)+np.sin(2*np.pi*2*f*t)+np.sin(2*np.pi*3*f*t)) for t in tt]
print(data... |
43a9b2a891ea96938bef6a283bde44619ffd3f9a7c4448e4119bd18e94a0e7fe | Python | 392 | 19 | from __future__ import annotations
import pytest
from textstat.backend import utils
@pytest.mark.parametrize(
"lang, root",
[
("en_US", "en"),
("en", "en"),
("en_GB", "en"),
("de_DE", "de"),
("es_ES", "es"),
("fr_FR", "fr"),
],
)
def test_get_lang_root(lang... |
f1844b1a37fa8c2ab6f899dbfee49f723677aec5a0e3cca2249b94821f0cbb7e | Python | 392 | 11 | import torch.nn as nn
def count_params(model: nn.Module, only_requires_grad: bool = False):
"count number trainable parameters in a pytorch model"
if only_requires_grad:
total_params = sum(p.numel()
for p in model.parameters() if p.requires_grad)
else:
total_para... |
16a72929d510050d056b31c5c6bf4cb0b1191be8e725518a5995f6a3046be034 | Python | 393 | 27 |
from __future__ import annotations
from typing import Any
import numpy as np
AR_i8: np.ndarray[Any, np.dtype[np.int_]] = np.arange(10)
ar_iter = np.lib.Arrayterator(AR_i8)
ar_iter.var
ar_iter.buf_size
ar_iter.start
ar_iter.stop
ar_iter.step
ar_iter.shape
ar_iter.flat
ar_iter.__array__()
for i in ar_iter:
pass... |
9df1b2349bcdcbbfe399679b2a37af2ca87200c36f2398f2b64653365a440be8 | Python | 393 | 14 | from pandas import (
TimedeltaIndex,
timedelta_range,
)
import pandas._testing as tm
class TestTimedeltaIndexOps:
def test_infer_freq(self, freq_sample):
# GH#11018
idx = timedelta_range("1", freq=freq_sample, periods=10)
result = TimedeltaIndex(idx.asi8, freq="infer")
tm.a... |
22f80e4549a9d304e5044e7bcfcbcc3bb8367354feea44a28213c20d21b76179 | Python | 395 | 17 | from setuptools import setup, find_packages
setup(
name='saveman',
version='1.0',
packages=find_packages(exclude=["*.tests", "*.tests.*", "tests.*",
"tests"]),
license='MIT',
author='AliRezaei',
url='*',
install_requires=[],
tests_require=[
'p... |
6480d022cbba828267560f8a697fbcbba89329f680eb13aa2408f8aca4d0df80 | Python | 396 | 17 | import numpy as np
import os
def remove_small_units(templates, threshold=2.5, units_in=None):
print (" .....PTP threshold: ", threshold)
if units_in is None:
n_units = templates.shape[0]
units_in = np.arange(n_units)
# compute ptp
ptps = templates[units_in].ptp(1).max(1)
# un... |
541d39045672d774bd2e01938e0e459519d30c3002c670625292f88029bca870 | Python | 397 | 13 | from .channel_controls_widget import ChannelControlsWidget
from .channel_table_model import ChannelTableModel
from .channel_table_view import ChannelTableView
from .imc_file_tree_model import IMCFileTreeModel
from .imc_file_tree_view import IMCFileTreeView
__all__ = [
"ChannelControlsWidget",
"ChannelTableMode... |
c233a18b85bf2b3aa3563d6a22ddc44ef0b4ada4a78f60c1c69fcfbb0c7843c7 | Python | 398 | 15 | """A Micro-Manager GUI based on pymmcore-widgets and pymmcore-plus."""
from importlib.metadata import PackageNotFoundError, version
try:
__version__ = version("micromanager-gui")
except PackageNotFoundError:
__version__ = "uninstalled"
__author__ = "Federico Gasparoli"
__email__ = "federico.gasparoli@gmail.c... |
2f7a776888c94cd428b52b21067d7d6afd6a18a52e73ad277360248f5bc98a96 | Python | 399 | 16 | from setuptools import setup, Extension
from Cython.Build import cythonize
import numpy
extensions = [
Extension("image_loader", ["image_loader.pyx"], include_dirs=[numpy.get_include()]),
Extension("subsample_mean", ["subsample_mean.pyx"], include_dirs=[numpy.get_include()])
]
setup(
ext_modules=cython... |
3e3cf41def37d7f3e58994785c88e0192750d6f8fa1eca933e679fe1ae4e61a6 | Python | 401 | 16 | from . forward_model import ForwardModel
from .head_model import (
TwoSurfaceHeadModel,
get_standard_headmodel,
get_inflated_cortex_surface,
)
from . image_recon import (
ImageRecon,
OriginalGaussianSpatialBasisFunctions,
GaussianSpatialBasisFunctions,
REG_TIKHONOV_ONLY,
REG_PAPER_MUA_SB... |
f6d03adaa2f4b866d228c65dc4cc0d8c0369c5a341e1bb8474a7ea0107a3d074 | Python | 401 | 14 | import pandas as pd
import pandas._testing as tm
def test_read_gbq_deprecated():
with tm.assert_produces_warning(FutureWarning):
with tm.external_error_raised(Exception):
pd.read_gbq("fake")
def test_to_gbq_deprecated():
with tm.assert_produces_warning(FutureWarning):
with tm.ext... |
d108da4dd68eb9600850f8773c73334244f615f76d9da87b3bbc5756c72ed369 | Python | 402 | 27 | from . import (
ase_model,
dataset,
dimenetplusplus,
equiformer_v2,
escn,
gemnet_oc,
graphormer,
painn_pyg,
phisnet,
schedulers,
)
from .model_registry import model_registry
__all__ = [
ase_model,
dataset,
dimenetplusplus,
equiformer_v2,
escn,
gemnet_oc,
... |
7a656c5e42d81cb66a134660c52be01c04243e468a31a6ca6cf88f9795979b7a | Python | 404 | 17 | from rdkit.Chem import DataStructs
from rdkit.Avalon.pyAvalonTools import GetAvalonFP as GAFP
import numpy as np
_type = 'topological-based'
def GetAvalonFPs(mol, nBits=2048):
'''
Avalon_fingerprints: https://pubs.acs.org/doi/pdf/10.1021/ci050413p
'''
fp = GAFP(mol, nBits = nBits)
arr = np.zero... |
9c80557ca4ea29e59d9fa3a0b4d34bdc85144d096fd0a2b9ae098f8d94eaaf0f | Python | 405 | 9 | # This file contains paths to any included files in the big_scape package
import importlib_resources
DB_SCHEMA_FILE = importlib_resources.files("big_scape") / "data/schema.sql"
TEMPLATES_OUTPUT_DIR = importlib_resources.files("big_scape") / "output"
# config is in base directory, not in module
# get path to package d... |
d5996c2592a452f099da5a08538c8760862c9bad22123c6f0c41350ef4a02515 | Python | 405 | 13 | #!/usr/bin/env python3
import boto3 # type: ignore[import]
def main() -> None:
creds_dict = boto3.Session().get_credentials().get_frozen_credentials()._asdict()
print(f"export AWS_ACCESS_KEY_ID={creds_dict['access_key']}")
print(f"export AWS_SECRET_ACCESS_KEY={creds_dict['secret_key']}")
print(f"expo... |
fd3a081a3f8ccc859edef0050f91c5bc3216a82f8adcbf5658d7cd12bdac7f7c | Python | 405 | 21 | import numpy as np
fname_template = 'im%07d.png'
zero_buffer_length = 150
framelist = [fname_template % 0] * zero_buffer_length
start_frame = 1801
end_frame = 2701
framelist = framelist + [fname_template % i for i in range(start_frame, end_frame)] + framelist
print framelist
print '\n'.join(framelist)
out_file_... |
545398d6f97507e72217b381fd460837de7a044376de75e9b700a95fdb86acec | Python | 406 | 19 | """Contains enums relating to genbank files"""
from enum import Enum
class RECORD_TYPE(Enum):
REGION = "region"
CAND_CLUSTER = "cand_cluster"
PROTO_CLUSTER = "protocluster"
PROTO_CORE = "proto_core"
class FEATURE_TYPE(Enum):
REGION = "region"
PROTOCLUSTER = "protocluster"
PROTO_CORE = "... |
20acb64c7c26bb9520063b556f06c3f47f80a7cb9a509a0f2766ed43825ab5da | Python | 407 | 15 | """ Distributor init file
Distributors: you can add custom code here to support particular distributions
of numpy.
For example, this is a good place to put any BLAS/LAPACK initialization code.
The numpy standard source distribution will not put code in this file, so you
can safely replace this file with your own ver... |
f182e53ba4f2b043f196d7db34a746f4c9555de0cb7d3206368da7511f99c25d | Python | 408 | 9 | """
core.array_algos is for algorithms that operate on ndarray and ExtensionArray.
These should:
- Assume that any Index, Series, or DataFrame objects have already been unwrapped.
- Assume that any list arguments have already been cast to ndarray/EA.
- Not depend on Index, Series, or DataFrame, nor import any of these... |
a17a429e53cb218f6a9c7cbdf3d5eae6929431650e714d5bf1a7febf2a2db0e3 | Python | 409 | 21 | import functools
from typing import Callable
task_registry = {}
def task(f: Callable):
name = f.__name__
if name in task_registry:
raise ValueError(
f"there is already a function with name '{name}' " "in the registry."
)
@functools.wraps(f)
def wrapper(*args, **kwargs):
... |
3e284f7f67b648b9cca719fffd53a1c7c1f2a727b502c856b559fb6416f847a0 | Python | 410 | 16 | import time
from contextlib import contextmanager
@contextmanager
def timer_context(label, verbose=True):
if verbose:
print(label)
start_time = time.time()
try:
yield
finally:
end_time = time.time()
elapsed_time = end_time - start_time
if verbose: # Print elaps... |
c5527f03e07095786357f9ddadf9d5c535e24d7e88bd6fa467a53ba9dd33275a | Python | 412 | 13 | """Builds on pint_xarray's unit registry."""
import pint_xarray
units = pint_xarray.unit_registry
Quantity = units.Quantity
# Aliases that we want to provide. FIXME: maybe a definition file is more convenient?
units.define("@alias deg = o")
units.define("@alias degC = oC")
units.define("@alias ohm = Ohm")
# FIXME te... |
e5f7bd63b0c3cce6e47a1b1bbe4f676271baa5100a25e3c6315a4c974081f358 | Python | 413 | 10 | """
Provides:
- Routines for interacting with, evaluating, and training word embeddings as used in Van Paridon & Thompson (2020).
- Routines for extending lexical norms to unnormed words.
- Routines for retrieving word, bigram, and trigram frequencies.
- Command line tools to conveniently do any of the above, i... |
e51c88c37d6291146aa4a9846c6d55e7b96e3246f6ba0dc225862e589c6cf52e | Python | 414 | 22 | """Contains database functionality modules"""
from .sqlite import DB
from .partial_task import (
find_minimum_task,
get_input_data_state,
get_missing_gbks,
get_hmm_data_state,
get_cds_to_scan,
get_hsp_to_align,
)
__all__ = [
"DB",
"find_minimum_task",
"get_input_data_state",
"... |
cde9716d3ea83c566736bc163e973592d51e013f957387ee15c4592d018bb4c2 | Python | 417 | 19 | """
Timer context manager, only used in debug.
"""
from time import time
import contextlib
from typing import Generator
@contextlib.contextmanager
def timer(subject: str = "time") -> Generator[None, None, None]:
"""print the elapsed time. (only used in debugging)"""
start = time()
yield
elapsed = t... |
e8b8a6f2dfc0e25ec760e207cc6048323752b227c37fa82a45ba038505636712 | Python | 418 | 22 | '''
Created on 2018.8.31
@author: liangqian
'''
from OpenGL.GL import *
from OpenGL.GLU import *
from OpenGL.GLUT import *
def drawFunc():
glClear(GL_COLOR_BUFFER_BIT)
#glRotatef(1, 0, 1, 0)
glutWireTeapot(0.5)
glFlush()
glutInit()
glutInitDisplayMode(GLUT_SINGLE | GLUT_RGBA)
glutInitWindowSize(400... |
3f0d2170560d7acb8f13cb8d0e6f4ff0355320509206a51c224afab26418cee3 | Python | 419 | 14 | from . import qem_methods
apply_zne = qem_methods.apply_zne
zne_option = qem_methods.zne_option # type: ignore
apply_dd = qem_methods.apply_dd
dd_option = qem_methods.dd_option # type: ignore
used_qubits = qem_methods.used_qubits
prune_ddcircuit = qem_methods.prune_ddcircuit
add_dd = qem_methods.add_dd
apply_rc = ... |
58227ae503228f5fc5dbb5190a1070c55151250da7e794fae5d495614f3715d2 | Python | 420 | 20 | import h5py
import numpy as np
from collections import OrderedDict
import sys
import os
def YRcoding(s):
encoded = ''.join([{'A':'R', 'T':'Y', 'C':'Y','G':'R', 'n':'n'}[B] for B in s])
return encoded
input_file = sys.argv[1]
out_file = sys.argv[2]
out = open(out_file, "w")
for line in open(input_... |
0ad7b389602c3cfdb60da158d0d309aeb4d48b63b6afe789b756d8143973fc59 | Python | 421 | 22 | from __future__ import annotations
from pyphen import Pyphen # type: ignore
from ._typed_cache import typed_cache
@typed_cache
def get_pyphen(lang: str) -> Pyphen:
"""Get a pyphen object for the given language.
Parameters
----------
lang : str
The language of the text.
Returns
---... |
94e11e79272262e84466d58e51c8c42aed973ad2f2711391980385710e7e30ac | Python | 422 | 11 | ##########################################################################
# NSAp - Copyright (C) CEA, 2016
# Distributed under the terms of the CeCILL-B license, as published by
# the CEA-CNRS-INRIA. Refer to the LICENSE file or to
# http://www.cecill.info/licences/Licence_CeCILL-B_V1-en.html
# for details.
##########... |
d517a6fe07849b8ab20f75da440d4d00f2b0af762346aebccdb2250bf5e18bd3 | Python | 422 | 16 | import numpy as np
np.sin(1)
np.sin([1, 2, 3])
np.sin(1, out=np.empty(1))
np.matmul(np.ones((2, 2, 2)), np.ones((2, 2, 2)), axes=[(0, 1), (0, 1), (0, 1)])
np.sin(1, signature="D->D")
# NOTE: `np.generic` subclasses are not guaranteed to support addition;
# re-enable this we can infer the exact return type of `np.sin(.... |
7881d30fba9d387439b77e1d836872b27107a3b29d9dcff9b3c12bc7f02a40dd | Python | 423 | 20 | from yass.batch import vectorize_parameter
# create a function that adds up three numbers, vectorize over parameter a
@vectorize_parameter('a')
def add(a, b, c):
return a + b + c
# same as above, but this time decorate an instance method
class Object(object):
@vectorize_parameter('a')
def add(self, a, b... |
7af0edf10378945e428b0ad421794e2429ed8ad0423ac23764b3c42005512c95 | Python | 423 | 17 | from typing import Optional
def pick_bool(*values: Optional[bool]) -> bool:
"""Pick the first non-none bool or return the last value.
Args:
*values (bool): Any number of boolean or None values.
Returns:
bool: First non-none boolean.
"""
assert values, "1 or more values required"
... |
2ce88ae106ad74ff9f4a837f3cd2b28040fd0de45e4e28acec1dc7f4101edb6d | Python | 424 | 13 | from PyQt5.QtWidgets import QWidget, QHBoxLayout, QPushButton
class SelectionButtons(QWidget):
def __init__(self):
super().__init__()
self.setLayout(QHBoxLayout())
self.deselect_all_button = QPushButton('deselect all')
self.select_all_button = QPushButton('select all')
se... |
d29f3317d4d9ce101cdc27fbfda8108a3306ba2cc9f7955017c6625e22432534 | Python | 426 | 28 |
amino_acid_3to1letter = {
"CYS": "C",
"ASP": "D",
"SER": "S",
"GLN": "Q",
"LYS": "K",
"ILE": "I",
"PRO": "P",
"THR": "T",
"PHE": "F",
"ASN": "N",
"GLY": "G",
"HIS": "H",
"LEU": "L",
"ARG": "R",
"TRP": "W",
"ALA": "A",
"VAL": "V",
"GLU": "E",
... |
347096aba11699dade21825730653e83f16dd58f8adbdff156b57de008b44c3b | Python | 427 | 15 | """
Checking results from threshold detector
"""
import matplotlib.pyplot as plt
from yass.explore import SpikeTrainExplorer, RecordingExplorer
path_to_data = '/Users/Edu/data/yass/tmp/standardized.bin'
path_to_spike_train = '/Users/Edu/data/yass/tmp/spike_train.npy'
exp = RecordingExplorer(path_to_data, spike_size=... |
d9ae7afdf0b7ce4bf598dc07e348aabee48be46aaafaf48914d5b8c1a2754079 | Python | 428 | 14 | import pandas as pd
# Read the comma-separated string from file
with open('CT2_log/euclidean/final_candidate/cluster.csv', 'r') as f:
content = f.read()
# Split by commas and clean up whitespace
genes = [gene.strip() for gene in content.split(',')]
# Create DataFrame
df = pd.DataFrame(genes, columns=['Gene Name'... |
831b7babdf55ceb9baea9482318212c56314433ea54fb88aea55fec40d312b2a | Python | 429 | 14 | #!/usr/bin/env python
from setuptools import setup
setup(name='ibc_public',
version='0.1',
description='Public code for IBC data analysis',
url='https://github.com/hbp-brain-charting/public_analysis_code',
author='Bertrand Thirion',
author_email='bertrand.thirion@inria.fr',
package... |
a4afe43ff0d94859c0bfff2be19a243cdda8c6eefd0412b5f0930ec2a9927a9a | Python | 429 | 15 | """Tools for validating detected collective events."""
__author__ = """Benjamin Graedel"""
__email__ = "benjamin.graedel@unibe.ch"
__version__ = '0.3.3'
from arcos4py.validation._bootstrapping import bootstrap_arcos, calculate_arcos_stats, calculate_pvalue
from arcos4py.validation._resampling import resample_data
__... |
680b7ffe6f3f24362125f84c7acb4d239f0c4696a298f380036ff170be7b52f8 | Python | 430 | 12 | from keras.models import Model
class GraphModel(Model):
""" This is a simple modification of the Keras `Model` class to avoid
checking each input for a consistent batch_size dimension. Should work as
of keras-team/keras#11548.
"""
def _standardize_user_data(self, *args, **kwargs):
kwargs[... |
2f2362c37d3132ec4ff786634f3f2a2a143b88a7ad25ffa681c1b092caeba494 | Python | 432 | 15 | import torch
from abc import ABC, abstractmethod
class BaseEvaluator(ABC):
@abstractmethod
def evaluate(self, x: torch.FloatTensor, y: torch.LongTensor, split: dict) -> dict:
pass
def __call__(self, x: torch.FloatTensor, y: torch.LongTensor, split: dict) -> dict:
for key in ['train', 'tes... |
67e0261229369b8179345246b5dd16ee56463741564daef1f5e19e4d0ea661be | Python | 432 | 11 | ##########################################################################
# NSAp - Copyright (C) CEA, 2019
# Distributed under the terms of the CeCILL-B license, as published by
# the CEA-CNRS-INRIA. Refer to the LICENSE file or to
# http://www.cecill.info/licences/Licence_CeCILL-B_V1-en.html
# for details.
##########... |
5d883c7d7fe264dfb7b6e054d886e32d94a6e301abb9886ff75d2ad0cbb996dc | Python | 433 | 14 | """Arcos4py top level module.
This package is a python package for the detection
and tracking of collective events intime-series data and raster images.
"""
__author__ = """Benjamin Graedel"""
__email__ = "benjamin.graedel@unibe.ch"
__version__ = '0.3.3'
from ._arcos4py import ARCOS
from .tools._detect_events import... |
649b08f1fb4226065498f7bf5c50221bd5c2a0a0f1c34502215edc397339e061 | Python | 434 | 14 | import jupyterlab
# Kind of a wild thing but this will be a nice way
# to be able to launch the notebook automatically without
# our users having to search for it... maybe.
from jupyterlab import labapp
import aims_immune
import os
import shutil
def launchit():
aims_dir = aims_immune.__file__[:-11]
startDir =... |
26c9a6fe9dffa90a5f27d3aa0a90f7b8b333064a6cc6e7e3d70ea2528ad8aa69 | Python | 435 | 13 | import pytest
from pandas import IntervalIndex
import pandas._testing as tm
class TestPickle:
@pytest.mark.parametrize("closed", ["left", "right", "both"])
def test_pickle_round_trip_closed(self, closed):
# https://github.com/pandas-dev/pandas/issues/35658
idx = IntervalIndex.from_tuples([(1,... |
40a0dc78af0afee8eac030dcde862b474a1d381620295390439bc56a9fc6fdc8 | Python | 435 | 14 | # .-. .-. .-. . . .-. .-. .-. .-.
# |( |- |.| | | |- `-. | `-.
# ' ' `-' `-`.`-' `-' `-' ' `-'
__title__ = "requests"
__description__ = "Python HTTP for Humans."
__url__ = "https://requests.readthedocs.io"
__version__ = "2.32.5"
__build__ = 0x023205
__author__ = "Kenneth Reitz"
__author_email__ = "me@kennethrei... |
a76c3b1756ab762fc64574ab9cd211f16d68787fe9826c3fd4fdb04b403623a3 | Python | 435 | 22 | """
Build an example package using the limited Python C API.
"""
import numpy as np
from setuptools import setup, Extension
import os
macros = [("NPY_NO_DEPRECATED_API", 0), ("Py_LIMITED_API", "0x03060000")]
limited_api = Extension(
"limited_api",
sources=[os.path.join('.', "limited_api.c")],
include_dir... |
4f8582b9e672f5649053111585b46c74a5de23c57987a8f0e42c9570853c7eca | Python | 436 | 18 | """ Configures cli """
import click
class CommandOrder(click.Group):
"""Modification of click Group to conserve command order"""
def list_commands(self, ctx: click.Context) -> list[str]:
"""list all sub-commands in the order they were supplied
Args:
ctx (click.Context): Click co... |
810c33f286f02ac9153851badab618b5c34ad7c5871930ec9d7bf5d1035ab07b | Python | 436 | 19 | import re
from pathlib import Path
from typing import Union
def get_directory(
transformed_data_loc: Path,
experiment_id: Union[int, str],
machine_name: str,
region_id: int,
) -> Path:
if isinstance(experiment_id, str):
experiment_id = int(re.sub("\D", "", experiment_id))
return (
... |
c8e4984eba9c3758564ddb5fcfe7207287e43e95d9a7aad82af20848adda63e9 | Python | 436 | 20 | import re
import os
import sys
folder = sys.argv[1]
infile = open(folder + "/progress.txt", "r")
data = infile.readlines()
infile.close()
finalline = ""
for line in data:
if line[-1] == "\n":
line = line[:-1]
if line != "":
finalline = line
linelist = finalline.split(",")
assert(linelist[-1] ... |
182673dc8af981c8f1c2c73792df89d121207155a23d3531dc7821589a01a69c | Python | 437 | 18 | import sys
log_file_path = sys.argv[1]
with open(log_file_path) as f:
lines = f.readlines()
for line in lines:
# Ignore errors from CPU instruction set, symbol existing testing,
# or compilation error formatting
ignored_keywords = [
"src.c",
"CheckSymbolExists.c",
"test_compi... |
201a40a3a3194d54c8435b401b8c221da5f5bb7e6e802225bd64bbe81dce670d | Python | 437 | 14 | from setuptools import setup, Extension
from Cython.Build import cythonize
import numpy as np
extensions = [
Extension("distance3d", ["distance3d.pyx"], include_dirs=[np.get_include()]),
Extension("bikernel", ["bikernel.pyx"], include_dirs=[np.get_include()])
]
setup(
name="cython_geometry_kernels",
e... |
4519633c80e2ea30cd85475b8ca31cef932cb7ec26f7697e1fa6f963e9420890 | Python | 437 | 13 | import pandas as pd
def test_repr():
df = pd.DataFrame({"A": pd.array([True, False, None], dtype="boolean")})
expected = " A\n0 True\n1 False\n2 <NA>"
assert repr(df) == expected
expected = "0 True\n1 False\n2 <NA>\nName: A, dtype: boolean"
assert repr(df.A) == expected
... |
a5ace073960c5cf04069f14e84bddac9045bdf9ba7a9e9f0ec81dde475f22bb4 | Python | 437 | 14 | """Contains custom error classes"""
from .data import DBAlreadyOpenError, DBClosedError, TableNotFoundError
from .genbank import InvalidGBKError, InvalidGBKRegionChildError
from .input_args import InvalidArgumentError, ArgumentParseError
__all__ = [
"DBAlreadyOpenError",
"DBClosedError",
"TableNotFoundErro... |
0b855df5470b690741590794352b1b37063a6508335d9eadbe5be70d6047fc60 | Python | 439 | 16 | import torch
import torch.nn as nn
class HamiltonianLoss(nn.Module):
def __init__(self) -> None:
super(HamiltonianLoss, self).__init__()
def forward(self, pred, target, mask):
diff = pred - target
mse = torch.mean(diff**2)
mae = torch.mean(torch.abs(diff))
mse *= pred.... |
1b8ab186d032c5a80c099ab0838e5ca12f336efccc4fb54aadf0e93527f1ffaf | Python | 439 | 22 | __version__ = '4.1'
## to custom map object
from molmap.agg import AggMolMap
## cpds feature map
from molmap.map import MolMap
from molmap.cpd import GlobCpdMolMap
## pdb feature map
from molmap.pdb import PDB2Fmap, PDB2Img
## aa sequence feature map
from molmap.seq import LocalAASeqMolMap
from molmap.seq import Gl... |
a8d582232be8725b30e5a39000094653910213de4e8368337fdd18c80e9bb346 | Python | 439 | 22 | from typing import Optional
import numpy as np
from pydantic import BaseModel
class LazyTiltSeriesData(BaseModel):
name: str
data: np.ndarray
last_loaded_index: Optional[int]
n_images_loaded: int = 0
class Config:
arbitrary_types_allowed = True
@property
def n_images(self):
... |
d88be7f80a52ec2fb0de5a7e29647f51205b1ffccc3dad55850b6189d0b17ba0 | Python | 439 | 18 | import pytest
import yaml
def pytest_addoption(parser):
parser.addoption(
"--no-cleanup",
action="store_true",
default=False,
help="Skip cleanup of DESIGNER's scratch (processing) directory and TMI's params directory.",
)
@pytest.fixture(scope="session")
def tolerance_config()... |
9cf384e17e035d3852dc0810f3b22038099cd5a29192bb81ab500c1af2ae6954 | Python | 440 | 23 | '''
Created on 2016.5.13
@author: liangqian
'''
from modal.lifneuron import LIFNeuron
from modal.cluster import Cluster
from modal.synapse import Synapse
c = Cluster('LIF')
c.createClusterNetwork()
c.setInhibitoryNeurons(0.2)
for i in range(0,c.neunum):
for j in range(0,c.neunum):
if(i != j):
... |
196a172ad5708d092a50d6b7ee1b7549d26375d16d358cfbee70e8ece2e5dd5e | Python | 441 | 19 | #!/usr/bin/env python
from parser import *
# bytes_to_int(fh_in.read(8), signed=True)
# int_to_bytes
with open("GSM6379997_203927450093_R01C01_Grn.idat", "rb") as fh_1:
with open("test.idat", "rb") as fh_2:
for i in range(13676211):
c1 = fh_1.read(1)
c2 = fh_2.r... |
30fef4a94c20b214ed4e12996990e9effe94f99eba34857581e5616ac1977a34 | Python | 441 | 17 | import numpy as np
from numpy.testing import assert_equal
class TestDot:
def test_matscalar(self):
b1 = np.matrix(np.ones((3, 3), dtype=complex))
assert_equal(b1*1.0, b1)
def test_diagonal():
b1 = np.matrix([[1,2],[3,4]])
diag_b1 = np.matrix([[1, 4]])
array_b1 = np.array([1, 4])
... |
9070e590afdb7ae1d778c3dce63b5adb0825f2074a7945ade5fda74c356bbedf | Python | 441 | 17 | #!/usr/bin/env python
"""
requests.certs
~~~~~~~~~~~~~~
This module returns the preferred default CA certificate bundle. There is
only one — the one from the certifi package.
If you are packaging Requests, e.g., for a Linux distribution or a managed
environment, you can change the definition of where() to return a s... |
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