sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
36d078557a171bcfd2e69dbdef3bc1a02573f0a965de24b07b25abc918daf86c | Python | 701 | 22 | import os
from setuptools import setup
from torch.utils.cpp_extension import CppExtension, CUDAExtension, BuildExtension
#ENV = os.environ["CONDA_PREFIX"] # Absolute path of active conda env root
#LIBRARY_DIRS = [os.path.join(ENV, "lib")] # .[so,dylib]
#INCLUDE_DIRS = [os.path.join(ENV, "include")]
#LIBRARIES = ["ma... |
68c21841395d961df86f9a10800a0cee1beff25220a9891f7907d1b7584479df | Python | 701 | 35 | from __future__ import annotations
import pytest
from textstat.backend import utils
@pytest.mark.parametrize(
"grade, expected",
[
(1, "st"),
(2, "nd"),
(3, "rd"),
(4, "th"),
(5, "th"),
(6, "th"),
(7, "th"),
(8, "th"),
(9, "th"),
... |
c7e8f470f2e08d7873714f3cc7da7d279c102998daa477ab414ba8aa10853785 | Python | 701 | 19 | from yass.explore import RecordingExplorer
def test_returns_empty_if_cannot_get_complete_wf(path_to_standardized_data):
e = RecordingExplorer(path_to_standardized_data,
spike_size=15, dtype='float32', n_channels=10,
data_order='channels', loader='array')
as... |
dfe5771088d4d7ea4cebd7b79d9ed8c6d012c5cf6e41212c06d0bcac6b0216a7 | Python | 701 | 26 | # License: GNU Affero General Public License v3 or later
# A copy of GNU AGPL v3 should have been included in this software package in LICENSE.txt.
""" A more accessible and defined set of data structures for interacting with
a sequence and its annotations.
Can convert to and from Biopython, but that use is i... |
3584fe9804f53bb03f4d26e971187e5fca0e370aab320755fea2c4083e4416eb | Python | 702 | 22 | from importlib import resources
from enum import Enum
class DefaultDataFile(Enum):
atac_ref_motifs = "ATAC.ref.motifs.txt"
dnase_ref_motifs = "DNASE.ref.motifs.txt"
motif_to_pwm_atac = "motif_to_pwm.ATAC.tsv"
motif_to_pwm_dnase = "motif_to_pwm.DNASE.tsv"
motif_to_pwm_tf = "motif_to_pwm.TF.tsv"
... |
c382cb012015a799fa55da316cee606b4ede0482d9f89eb94bc11219958a0dda | Python | 702 | 31 | import pytest
import cedalion.sigproc.physio as physio
import cedalion.data
from cedalion import units
import numpy as np
np.random.seed(42)
@pytest.fixture
def rec():
rec = cedalion.data.get_snirf_test_data()[0]
return rec
def test_global_component_subtract(rec):
ts = rec["amp"]
ts_weights = ts.s... |
b2f79defa9779ecb444a36489ec606ccfaf247870f21a7f74074c9b930d85cd3 | Python | 704 | 34 | # file generated by setuptools-scm
# don't change, don't track in version control
__all__ = [
"__version__",
"__version_tuple__",
"version",
"version_tuple",
"__commit_id__",
"commit_id",
]
TYPE_CHECKING = False
if TYPE_CHECKING:
from typing import Tuple
from typing import Union
V... |
a28badd0599da1d67a8499329b16307798c3ec9d0f7a255462415d75cf89a3e1 | Python | 708 | 26 | """Contains modules for dereplicate workflow"""
from .input_data_loading import load_input_folder, parse_gbk_files, gbk_factory, load_input_data, make_gbk_name
from .gbk_component_parsing import get_parser_functions
from .sourmash_utilities import (
make_sourmash_input,
run_sourmash_branchwater,
parse_sour... |
fad919ba9209aff8cba9e5fbc5b46113cf823971d12341a846900a72156d7b9e | Python | 709 | 22 | import os
import sys
if 'setuptools' in sys.modules:
from setuptools.command.bdist_rpm import bdist_rpm as old_bdist_rpm
else:
from distutils.command.bdist_rpm import bdist_rpm as old_bdist_rpm
class bdist_rpm(old_bdist_rpm):
def _make_spec_file(self):
spec_file = old_bdist_rpm._make_spec_file(sel... |
84f56e16f19f2e2ed726c51c7cd7dae57b29af08ba1d8b3f405da77c0eac368f | Python | 710 | 20 | import pandas as pd
import os
# Create consistency directory if it doesn't exist
os.makedirs('CT2_log/euclidean/final_candidate/consistency', exist_ok=True)
# Read the files
current_candidates_df = pd.read_csv('CT2_log/euclidean/final_candidate/candidate_genes.csv')
h9_df = pd.read_csv('consistency/H9_candidate_genes... |
c2db7ed8c2479561915cfbe39613151e177a71d81cbf5162fbddd24a343354fb | Python | 710 | 24 | from .layer import Layer
from .composercluster import ComposerCluster
class ComposerLayer(Layer):
'''
This layer defines the information of composer name. One neuron corresponds to a composer
'''
def __init__(self, neutype='LIF'):
self.neutype = neutype
self.groups = {}
def s... |
0000a14fdc9a2f6d9ad4755c0e08c08cc4bd053b8871aeffee93811ea5a50356 | Python | 711 | 21 | from typing import Optional
import tempfile
import shutil
import contextlib
@contextlib.contextmanager
def tmpdir_manager(base_dir: Optional[str] = None):
"""Context manager that deletes a temporary directory on exit."""
tmpdir = tempfile.mkdtemp(dir=base_dir)
try:
yield tmpdir
finally:
... |
fd0d7e75265829bad78d64ea5a78018ac9e75cdaba6a07457dac634e8a759837 | Python | 711 | 20 | import torch
from torch import Tensor
from torchmetrics.functional.regression.mae import _mean_absolute_error_update
from torchmetrics.regression import MeanAbsoluteError
class MaskedMeanAbsoluteError(MeanAbsoluteError):
"""Overloaded MAE for usage with block diagonal matrix.
Mask calculated from target tenso... |
2a72440391f871783b48bacc8f05ad89d0f6e154af39dbbbd9dd7bbe8b6263d1 | Python | 713 | 21 | from distutils.unixccompiler import UnixCCompiler
class PathScaleCCompiler(UnixCCompiler):
"""
PathScale compiler compatible with an gcc built Python.
"""
compiler_type = 'pathcc'
cc_exe = 'pathcc'
cxx_exe = 'pathCC'
def __init__ (self, verbose=0, dry_run=0, force=0):
UnixCCompil... |
3e9753526ddc8d6594328c4ff652376028ef46ee777a336a4b3ae493fc8a531d | Python | 713 | 22 | from setuptools import setup, find_packages
setup(
name='modamix',
version='0.0.2',
description='A Unified Framework for Correcting Batch Effects and Integrating Multi-Omics Data',
author='miniymay',
author_email='joungmin@vt.edu',
url='https://github.com/cbi-bioinfo/MoDAmix',
install_requi... |
452dee15b65b0e2c56c78b5cc8380ae36bce3acb2efc78ef670bd23ba831bddb | Python | 713 | 21 | # -*- coding: utf-8 -*-
#
# __init__.py
#
# Copyright 2020 Amazon.com, Inc. or its affiliates. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.o... |
7f78c2f7bf50bb4da226180065736834728f6f8b0a98fa7b03753741be500eb3 | Python | 714 | 25 | # >>>
# https://gist.github.com/Cilyan/9424144
import base64
import struct
def fnv64(data):
hash_ = 0xcbf29ce484222325
for b in data:
hash_ *= 0x100000001b3
hash_ &= 0xffffffffffffffff
hash_ ^= b
return hash_
def hash_dn(dn: str, salt: str):
# Turn dn into bytes with a salt, d... |
a196f3f72a1a60d12f138ff069fc1f901b11c2de90d8376baf6f689be098022b | Python | 714 | 31 | import numpy as np
import pandas as pd
from tabulate import tabulate
from rdkit import Chem
def load_data(file_path):
df = pd.read_csv(
file_path,
sep=None,
engine="python"
)
smiles = df.iloc[:, 1].values
targets = df.iloc[:, 2:].values
return smiles, ... |
cfa5c8072401665627feeabafdd1754755c2f5ce323b7f55009a5eedfba4cf74 | Python | 715 | 28 | #!/usr/bin/env python3
import stsc.parser as parser
from stsc.run import run
from stsc.look import look
from stsc.progress import progress
from stsc.test import test
def main():
prs = parser.make_parser()
args = prs.parse_args()
if args.command == 'run':
run(prs,args)
elif args.command == 'lo... |
78e994bb8ab48a11936d8a4295ea029d8b6fc21d530421194108cb78969430d0 | Python | 717 | 20 | import pytest
from pandas.core.dtypes.cast import construct_1d_object_array_from_listlike
@pytest.mark.parametrize("datum1", [1, 2.0, "3", (4, 5), [6, 7], None])
@pytest.mark.parametrize("datum2", [8, 9.0, "10", (11, 12), [13, 14], None])
def test_cast_1d_array(datum1, datum2):
data = [datum1, datum2]
result... |
10a3e2963adf285f874c69b426e910c2fe9f8afd77c1eee8c40a40dba06837ad | Python | 718 | 28 | from __future__ import annotations
from ..utils._typed_cache import typed_cache
from ._list_difficult_words import list_difficult_words
@typed_cache
def set_difficult_words(text: str, syllable_threshold: int, lang: str) -> set[str]:
"""Get a set (no duplicates) of the difficult words in the text.
Parameter... |
b065d2e48a71d48a3174a07b54f287f9789a070f1a8f556795626a9a4c53e449 | Python | 718 | 17 | # License: GNU Affero General Public License v3 or later
# A copy of GNU AGPL v3 should have been included in this software package in LICENSE.txt.
""" Helpers for type hints.
"""
class ConfigType: # pylint: disable=too-few-public-methods
""" Exists only to allow mypy to use the stub by this name in custom_typi... |
e945a6236275e6add3a116be219715efc48746d6970140a603c27f394285f04a | Python | 722 | 31 | # run as: python make_video.py
import os
import matplotlib.pyplot as plt
import numpy as np
fiber = 0
model = 0
ve_path = os.path.join('..', 've_files', f'model{model}_fiber{fiber}.dat')
print(f've_path: {ve_path}')
ve = -1 * np.loadtxt(ve_path, skiprows=1)
coords_path = os.path.join('..', 'coords_files', f'{fiber... |
dc8a69c9df21737d3c531609ed84a522f25e81be9e8f272c04c8b7dddfe7954c | Python | 725 | 27 | from setuptools import setup, Extension
import numpy
setup(
ext_modules=[
Extension(
'crystal_tracer.algorithm.detection',
['crystal_tracer/algorithm/detection.pyx'],
language='c++',
include_dirs=[numpy.get_include()],
),
Extension(
... |
6f7af0d49fd5dccc14f8b65ff2e21244abdf5f315a0631470026e0c8ba3bf396 | Python | 727 | 29 | """
Compatibility module.
This module contains duplicated code from Python itself or 3rd party
extensions, which may be included for the following reasons:
* compatibility
* we may only need a small subset of the copied library/module
This module is deprecated since 1.26.0 and will be removed in future versions.... |
b8f6fe4f04f2a5972bbaf1ecadff40cff029e4feea826fabd80f0672995c7571 | Python | 727 | 18 | import pandas as pd
# Read the deletion distance file
distances_df = pd.read_csv('CT2_log/euclidean/high_variation_genes/deletion_distance.csv')
# Sort by difference in descending order and get top 200
top_200 = distances_df.sort_values('Difference', ascending=False).head(200)
# Save to a new file
top_200.to_csv('CT... |
36967e0a616fb6b6d2f485633acf147726c70cd99d9a5497359d376986b2232f | Python | 731 | 33 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Jul 1 13:49:20 2021
@author: wanxiang.shen@u.nus.edu
"""
import os
import pandas as pd
file_path = os.path.dirname(__file__)
class load_all:
@property
def data(self):
return pd.read_csv(os.path.join(file_path, 'result_data', 'all_d... |
8b73a2d426fc7fcf07d76f7bd5bac7cde1c2d68439a9f765ffe598ba2417632a | Python | 732 | 27 | from typing import Optional
from app.config.camera import CameraConfig
class CameraConfigValidator:
@classmethod
def _validate(cls, camera_config: CameraConfig) -> Optional[str]:
if camera_config is None:
return "Config is null"
if camera_config.fps is None:
return "F... |
0a2bb2b221c0dfd57951f702057148c7cdc8ac3a6ec1f37d45c4d482fdbc7ed4 | Python | 733 | 33 | """
requests.hooks
~~~~~~~~~~~~~~
This module provides the capabilities for the Requests hooks system.
Available hooks:
``response``:
The response generated from a Request.
"""
HOOKS = ["response"]
def default_hooks():
return {event: [] for event in HOOKS}
# TODO: response is the only one
def dispatch_... |
d26b56d8e099638e57f15c18ee3ef69cff2376f458f6c0b960670489d56cc2c9 | Python | 733 | 23 | from __future__ import annotations
import pytest
from textstat.backend import metrics
from .. import resources
@pytest.mark.parametrize(
"text, lang, expected",
[
(resources.EMPTY_STR, "en_US", 0.0),
(resources.EASY_TEXT, "en_US", 7.348),
(resources.SHORT_TEXT, "en_US", 8.842),
... |
f13b23bb54705cd6cfc90723bfc191305bde150a9895b35d4998765f5395f955 | Python | 733 | 27 | import sys
if 'setuptools' in sys.modules:
from setuptools.command.sdist import sdist as old_sdist
else:
from distutils.command.sdist import sdist as old_sdist
from numpy.distutils.misc_util import get_data_files
class sdist(old_sdist):
def add_defaults (self):
old_sdist.add_defaults(self)
... |
f8681da17db0a17acbdfebe7063aba10a893c933054365330cea59ef63abc108 | Python | 733 | 38 | from __future__ import annotations
from ._words_per_sentence import words_per_sentence
from ._chars_per_word import chars_per_word
from ..utils._typed_cache import typed_cache
@typed_cache
def automated_readability_index(text: str) -> float:
r"""Calculate the Automated Readability Index (ARI).
Parameters
... |
cc48243eedae89d2ccc473ffd6032deffeac5c7030b3ce5b8b88968e08c0c8be | Python | 734 | 25 | import pennylane as qml
import tensorflow as tf
nwires, nlayers, nbatch = 6, 3, 16
dev = qml.device("default.qubit.tf", wires=nwires)
@tf.function
@qml.qnode(dev, interface="tf")
def yp(inputs, params):
for i in range(nwires - 1):
qml.RX(inputs[i], wires=i)
for j in range(nlayers):
for i in r... |
3380b234b890a10e6886800c1f91c44bd461da5a6bc80335b682fe6f54c95e3d | Python | 736 | 31 | from pandas.core.indexers.utils import (
check_array_indexer,
check_key_length,
check_setitem_lengths,
disallow_ndim_indexing,
is_empty_indexer,
is_list_like_indexer,
is_scalar_indexer,
is_valid_positional_slice,
length_of_indexer,
maybe_convert_indices,
unpack_1tuple,
un... |
b2ff8f81a6a6bbeb8395cfa9848f783988c0a54c6803ee34596d34b23fbc58aa | Python | 736 | 25 | import tensorcircuit as tc
tc.set_backend("tensorflow")
nwires, nlayers = 6, 3
def vqe_forward(param):
c = tc.Circuit(nwires)
for i in range(nwires):
c.H(i)
for j in range(nlayers):
for i in range(nwires - 1):
c.exp1(i, i + 1, theta=param[2 * j, i], unitary=tc.gates._zz_matrix... |
e0bdbe9d691d018875d63962fa0144bb3e17abe8c876b4cae4a2e22825da04c8 | Python | 736 | 30 | import argparse
import logging
import os
from nmf_analysis import data
from nmf_analysis import settings as s
logger = logging.getLogger(__name__)
logging.getLogger().setLevel(logging.INFO)
def generate() -> None:
"""
Load the dataset store in HDF database.
"""
parser = argparse.ArgumentParser()
... |
eb5011bf0b4992c7aac039e749809493e5df079dc1b66859d46ec3e84411da23 | Python | 737 | 32 | from __future__ import annotations
from .constants import LANG_CONFIGS
from ._get_lang_root import get_lang_root
def get_lang_cfg(lang: str, key: str) -> float:
"""Get the config value specified by `key` for the given language `lang`.
Parameters
----------
lang : str
The language of the text... |
f53539310ac9eb1ad02b8300ec4c90f91e85d557a263c2076b5f6a33a25bcb92 | Python | 737 | 34 | '''
Created on 2016.7.7
@author: liangqian
'''
from Modal.note import Note
from Modal.cluster import Cluster
from conf.conf import configs
from Modal.pitch import Pitch
class APAC():
'''
anterior primary auditory cortex,encoding the musical notes
'''
def __init__(self):
'''
Constructo... |
81dfa70572def8373956873f2ac826abd98e53a4bf239659aa55dc6a980acdf1 | Python | 738 | 30 | from datetime import timedelta
from pandas import (
Index,
Timestamp,
date_range,
isna,
)
class TestAsOf:
def test_asof_partial(self):
index = date_range("2010-01-01", periods=2, freq="ME")
expected = Timestamp("2010-02-28")
result = index.asof("2010-02")
assert re... |
ecbc2a8bd2caa7193800be418281d6532be27a2aa0f6f083002f3fe93a8ad2c0 | Python | 739 | 19 | # License: GNU Affero General Public License v3 or later
# A copy of GNU AGPL v3 should have been included in this software package in LICENSE.txt.
""" Representations of features within secmet """
from .antismash_domain import AntismashDomain
from .antismash_feature import AntismashFeature
from .candidate_cluster im... |
feda2cf68177e7f66cf279e2a310aaf351d91fb0f2f2b44b562138d7c537c665 | Python | 739 | 25 |
import sys
sys.path.append('.')
from plotting.utils import load_results, mesh_name, sim_name, set_plotting_defaults, efcolor, pvscolor, ecscolor
import matplotlib.pyplot as plt
if __name__ == '__main__':
sim_name = sys.argv[1]
mesh_name = sys.argv[2]
results = load_results(mesh_name, sim_name)
times = resu... |
d3c77ea09407002c91f88e684dea06d699a57a2090f2f3bb9d54ceee02f4eb74 | Python | 741 | 23 | # License: GNU Affero General Public License v3 or later
# A copy of GNU AGPL v3 should have been included in this software package in LICENSE.txt.
""" A collection of functions for running prodigal.
"""
from .base import execute, get_config
def run_prodigal_version() -> str:
""" Get the version of the prodigal... |
94ae5f5efe1c448bbaf6872f3877ca2f96e378ad230dd5b7a6cbebaecb230e80 | Python | 742 | 25 | import numpy as np
from pandas import (
Categorical,
Series,
)
import pandas._testing as tm
class TestCategoricalComparisons:
def test_categorical_nan_equality(self):
cat = Series(Categorical(["a", "b", "c", np.nan]))
expected = Series([True, True, True, False])
result = cat == ca... |
aaeb29d88511360da6fd50c3988bdaa74ecadc189871e4ba5d840e40bf33b0a1 | Python | 743 | 26 | # Create 'crime.pickle'
import pickle
import lightgbm as lgb
from sklearn.model_selection import train_test_split
import shap
random_state = 1203344
# Load data and train model
X, y = shap.datasets.communitiesandcrime()
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, random_state=random_s... |
db6622c6969b2008d4cb0062ebdb5ae54eb182a07336d4676b6fd6960132d6b0 | Python | 743 | 25 | """
General DL functions
"""
import torch
import warnings
def get_device(device_str):
"""
This function gets the desired device
"""
if device_str == 'cpu':
device = torch.device(device_str)
elif device_str.startswith('cuda'):
if torch.cuda.is_available():
device = torc... |
da8f0178cc63018df1ba5d6d91fd3f3e2c35883bab18f1d58923738b2d5b3f04 | Python | 744 | 23 | import mido
import time
from midi_functions import create_chord_from_number, send_chord_on, clear_all_notes, send_chord_off
TR = 1.5 # in seconds
chord = [60 - 12, 60, 60 + 7]
# MIDI output
midi_music_out = mido.open_output('IAC Driver Music Port')
CHANGE_CHORD = True
#base_note_prog = [1, 0, 1, 2, 3, 4, 5, 6, 7, 8... |
553773fd53ad6284c2d57309a7397a6c3e6f44edf39e4657b14e7524cbfd73cd | Python | 745 | 27 | # -*- coding: utf-8 -*-
import numpy as np
import os
import pandas as pd
import sys
sys.path.append(os.path.dirname(os.path.abspath(__file__)))
def read_data(file_path):
df = pd.read_csv(file_path, index_col='time', parse_dates=['time'], date_format="%Y-%m-%d %H:%M:%S").dropna().astype(float)
return df
def... |
7aa56b15607d7c0b472bb5c5dfbd34e23ae4785243e30206dccdca0406cef14f | Python | 748 | 28 | """
Created on Jan 6, 2026
@author: mning
"""
import statsmodels.api as sm
from sklearn.base import BaseEstimator
from sklearn.base import RegressorMixin
class SMWrapper(BaseEstimator, RegressorMixin):
"""A universal sklearn-style wrapper for statsmodels regressors"""
def __init__(self, model_class, fit_int... |
2c3d8133810f027a3bb1608f0b25d52b4312ad7ea6b1546095cce0cc544dc9d2 | Python | 750 | 40 | import numpy as np
show_hz = 15
num_seconds = 120
num_repeats = 4
num_junk_seconds = 10
num_blank_seconds = 10
img_template = "im%07d.png"
blank_img = img_template % 0
stimlist = []
blank = [blank_img] * (num_blank_seconds * show_hz)
stimlist = stimlist + blank
junk_offset = num_seconds * show_hz + 1
junk = [... |
57b94c530c3b0aa809d93854067d4f89ab59b506a73b2b7b399a6ed86648fb7e | Python | 750 | 17 | from __future__ import annotations
from blinker import Namespace
# This namespace is only for signals provided by Flask itself.
_signals = Namespace()
template_rendered = _signals.signal("template-rendered")
before_render_template = _signals.signal("before-render-template")
request_started = _signals.signal("request... |
3802763df28ea431ef2ebc331ac776dcccdc9a4be3cc7ddc2d8c7e19dd811d3f | Python | 751 | 22 | import torch
from .rk_common import _ButcherTableau, RKAdaptiveStepsizeODESolver
_BOGACKI_SHAMPINE_TABLEAU = _ButcherTableau(
alpha=torch.tensor([1 / 2, 3 / 4, 1.], dtype=torch.float64),
beta=[
torch.tensor([1 / 2], dtype=torch.float64),
torch.tensor([0., 3 / 4], dtype=torch.float64),
... |
c061e1ad4d923ee3da27bbbabc3dbaf7eb8f74fc65d2040eb6fc1a7f2fdf4a0e | Python | 751 | 20 | import pytest
from click.testing import CliRunner
from cardio_audio_sleep.commands.sys_info import run
@pytest.mark.parametrize("developer", [False, True])
def test_sys_info(developer: bool):
"""Test the system information entry-point."""
runner = CliRunner()
result = runner.invoke(run, ["--developer"] i... |
a9b3457ee161ee012ec6666816f29f4ed8316d12498993b307787b6525cc682d | Python | 753 | 26 | # Tests for the '.AminoAcidMWChange' defs
import pandas
import numpy
import pytest
import sbmlcore
def test_amino_acid_MW_change_value():
a = {'mutation': ['A1D', 'E2K']}
df = pandas.DataFrame(a)
a = sbmlcore.AminoAcidMWChange()
df = a._add_feature(df)
assert 'd_MW' in df.columns
assert df.... |
cf380546ec3f9163e32a91b0ecb0b4654303d8243611b7ab50862cf22ce37420 | Python | 753 | 25 | from dataclasses import dataclass
from pip._vendor.packaging.version import Version
from pip._vendor.packaging.version import parse as parse_version
from pip._internal.models.link import Link
@dataclass(frozen=True)
class InstallationCandidate:
"""Represents a potential "candidate" for installation."""
__s... |
404c852e79a6c4a922dc4082a8c0c72ebb2b6d7e1a1925723c97f831bc397197 | Python | 754 | 29 | '''
Created on 2016.6.8
@author: liangqian
'''
import time
import sys
import stomp
class MyListener(object):
def on_error(self, headers, message):
print('received an error : %s' % message)
def on_message(self, headers, message):
print('%s' % message)
conn = stomp.Connection([('159.226.19.16',6... |
9332b42a79f1b865bfa050543badd56fa9f81f610b84a52f321f5f65fccb730d | Python | 754 | 23 | # License: GNU Affero General Public License v3 or later
# A copy of GNU AGPL v3 should have been included in this software package in LICENSE.txt.
""" A collection of functions for running java.
"""
from .base import execute, get_config
def run_java_version() -> str:
""" Get the version of the java binary """
... |
d1b716c9065401ad700d9648fa43ca97695419d0001f312b35f63b0ba50c04e1 | Python | 754 | 26 | from pathlib import Path
import nrrd
import matplotlib.pyplot as plt
from tqdm.contrib.concurrent import process_map
def main(i):
img, _ = nrrd.read(str(i))
img = img.max(axis=0)
height, width = img.shape[:2]
dpi = 300
figsize = (width / dpi, height / dpi)
fig, ax = plt.subplots(facecolor='bla... |
914f97aed2edb99820fea1c9a0df2e3f5cb742e2dee91220cf7c41ecdc55d0f2 | Python | 755 | 33 | from io import StringIO
from cardio_audio_sleep.utils.config import sys_info
def test_sys_info():
"""Test info-showing utility."""
out = StringIO()
sys_info(fid=out)
value = out.getvalue()
out.close()
assert "Platform:" in value
assert "Executable:" in value
assert "CPU:" in value
... |
ecc9bb4fdabbbdf34ec893f08619526aecc703b1d759f11f4fc5ac3de5372084 | Python | 755 | 25 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# setup.py
#
# Copyright 2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# ... |
29c3f5192df4f8ddb6b97394d6688ab5a7b1240b4be448c8dabf90b74ac399c5 | Python | 757 | 27 | """Utilities for phyid."""
import numpy as np
PhiID_atoms_abbr = [
"rtr", "rtx", "rty", "rts",
"xtr", "xtx", "xty", "xts",
"ytr", "ytx", "yty", "yts",
"str", "stx", "sty", "sts",
]
PhiID_atoms_full = [
("Red", "Red"), ("Red", "Un1"), ("Red", "Un2"), ("Red", "Syn"),
("Un1", "Red"), ("Un1", "Un1... |
75027b54542e2619bb57f93cdfb6484cba75b6de2a141e10b06f38fddaf320b1 | Python | 757 | 26 | # Tests for the '.AminoAcidPiChange' defs
import pandas
import numpy
import pytest
import sbmlcore
def test_amino_acid_Pi_change_value():
a = {'mutation': ['A1D', 'E2K']}
df = pandas.DataFrame(a)
a = sbmlcore.AminoAcidPiChange()
df = a._add_feature(df)
assert 'd_Pi' in df.columns
assert df.... |
436dc2cbfe10d2f510b3c2b1c1880d3305dc2612caefee3640f3d3a20bbf8d6c | Python | 758 | 20 | import pandas as pd
import os
# Create consistency directory if it doesn't exist
os.makedirs('CT2_log/euclidean/final_candidate/consistency', exist_ok=True)
# Read the files
current_candidates_df = pd.read_csv('CT2_log/euclidean/final_candidate/candidate_genes.csv')
small_deletion_df = pd.read_csv('consistency/small_... |
e915f65fe995d47ba12599d57d098398b5612145ac7884f83f9c1fdeb74babd6 | Python | 758 | 28 | from numpy.distutils.fcompiler import FCompiler
from numpy.distutils import customized_fcompiler
compilers = ['NoneFCompiler']
class NoneFCompiler(FCompiler):
compiler_type = 'none'
description = 'Fake Fortran compiler'
executables = {'compiler_f77': None,
'compiler_f90': None,
... |
03175f43c40739f293f816c3994d762221ab3b57048084574ef13350e676a946 | Python | 759 | 30 | """module containing integration tests for the family calling workflows"""
# from python
from unittest import TestCase
# from dependencies
# from other modules
import big_scape.data as bs_data
# from this module
class TestComparison(TestCase):
"""Test class for hmm search/scan workflow"""
def clean_db(se... |
bebcd9e13b285221677ced3b0d3a424867abc54be8b7b5a02619423f22c6f0d7 | Python | 759 | 27 | from __future__ import annotations
import pytest
from textstat.backend import counts
from .. import resources
@pytest.mark.parametrize(
"text,ignore_spaces,expected",
[
("", True, 0),
("", False, 0),
("a", True, 1),
("a ", True, 1),
("a ", False, 2),
("a b", Tr... |
db8e0be148c23db28730fab1168670dea002df5aa2696f44a4fb85da192002a4 | Python | 759 | 39 | import argparse
import logging
from nmf_analysis.nmf import train_model
logger = logging.getLogger(__name__)
logging.getLogger().setLevel(logging.INFO)
def train() -> None:
"""
Train a NMF model.
"""
parser = argparse.ArgumentParser()
parser.add_argument(
"--behavior",
default="T... |
310c1c1660b91b7d6266b789ea71ed2e7123e0923e10b32faa4e9c2c542c76b9 | Python | 760 | 29 | """
Created on Jun 5, 2024
@author: mning
"""
import logging
import os
from src.utils import logFilter
def setup_custom_logger(name: str, loglevel: int = logging.INFO) -> logging.Logger:
log_Dir = (
r"C:\Users\mning\Documents\CNBS_Projects\SAGES I and II"
r"\Data\Baseline_rsEEG_preprocessing\csv... |
6f6ab8ffee0b2269b5e7c80a2ffda31e807ceaaaa3e0cfa38ba7082e6a0b44b5 | Python | 760 | 15 | import pandas, sys
threshold_file = sys.argv[1]
regions_file = sys.argv[2]
thresholds = pandas.read_csv(threshold_file, sep="\t", compression="gzip", header=0)
regions = pandas.read_csv(regions_file, sep="\t", compression="gzip", header=None, names=["Chrom", "Start", "End", "Region", "AverageCov"], index_col=... |
3f7f5826f226efcc85117b9bb3fc6e2e4895ab7ba112fe333553bac927d7205c | Python | 763 | 19 | """ Keras loss functions will choke on NaN inputs, which we'll often have for
unspecified inputs. These are just a couple simple loss functions that mask NaN
values in both the test and predicted tensors when computing the cost. """
import keras.backend as K
import tensorflow as tf
def masked_mean_squared_error(y_tru... |
821dde182e4312f34828502dbb3cd73df89b8f5a91c4cbbf94d89e7e9496e4c9 | Python | 763 | 31 | """Smoke test TensorCircuit after installing only its required dependencies."""
import importlib.util
import numpy as np
import tensorcircuit as tc
OPTIONAL_MODULES = ("tensorflow", "jax", "torch", "cupy", "qiskit", "cirq", "stim")
def main() -> None:
installed_optional_modules = [
name for name in OP... |
e84942e9d065ff58a617852565515eafa5ad6f0ca960bd04862b9cd18c0990fa | Python | 763 | 23 | import numpy as np
def tile_images(img_nhwc):
"""
Tile N images into one big PxQ image
(P,Q) are chosen to be as close as possible, and if N
is square, then P=Q.
input: img_nhwc, list or array of images, ndim=4 once turned into array
n = batch index, h = height, w = width, c = channel
... |
46f49d37b08bf533b7c6fd9e0635a35a22e1b1143b5f8b17e5d7171fd5b1c1f5 | Python | 764 | 25 | import numpy as np
import torch
from torch_geometric.data import Batch, Data
def np_scatter_add(updates, indices, shape):
target = np.zeros(shape, dtype=updates.dtype)
np.add.at(target, indices, updates)
return target
def atoms_list_to_PYG(ase_atoms_list, device):
"""Function to convert ase.Atoms ob... |
4e2c6c9bba46763593d702f349969ca5cb02565915b5181409059c76565aaef4 | Python | 764 | 24 | import scvelo as scv
from scvelo.tools import SecondOrderSteadyStateModel, SteadyStateModel
# TODO: Add test to check equivalence with original implementation
def test_first_order_model_run():
adata = scv.datasets.simulation(random_seed=0, n_vars=10)
scv.pp.filter_and_normalize(adata)
scv.pp.moments(adata... |
92bdca2a73295822b2ac1166939cfc9805a6259b20cdf5eea61c31053b0553a9 | Python | 766 | 20 | import pandas as pd
import os
# Create consistency directory if it doesn't exist
os.makedirs('CT2_log/euclidean/final_candidate/consistency', exist_ok=True)
# Read the files
current_candidates_df = pd.read_csv('CT2_log/euclidean/final_candidate/candidate_genes.csv')
original_dataset_df = pd.read_csv('consistency/orig... |
cbf2a4b8bcf5b8cee9bf9dea7eaec640ebae7782e85c4ddaa4ad70b4045d5723 | Python | 766 | 37 | import numpy as np
AR = np.arange(10)
AR.setflags(write=False)
with np.printoptions():
np.set_printoptions(
precision=1,
threshold=2,
edgeitems=3,
linewidth=4,
suppress=False,
nanstr="Bob",
infstr="Bill",
formatter={},
sign="+",
float... |
e485791a73361570732d6cf073af13d10b908ebfbb3ff55f1abca2fb15011422 | Python | 768 | 30 | import numpy as np
def get_pads(target_dim, d):
if target_dim <= d:
return 0, 0
p = (target_dim - d) // 2
if (p * 2 + d) % 2 != 0:
return p, p + 1
return p, p
def target_pad(img, target_dims, mode="zero"):
pads = tuple(get_pads(t, d) for t, d in zip(target_dims, img.shape))
... |
e9c1610c5a57ed32797cb9fc3cf0ba766fb8d98d5aea350aa4121413b2d2024f | Python | 770 | 25 | from __future__ import annotations
import pytest
from textstat.backend import metrics
from .. import resources
@pytest.mark.parametrize(
"text, ms_per_char, expected",
[
(resources.EMPTY_STR, 0.0, 0.0),
(resources.EMPTY_STR, 1.0, 0.0),
(resources.EMPTY_STR, 5.3, 0.0),
(resour... |
d4dc27f9e3d80445d663837da457476aa719a0a856ba29ca74527e12366d1656 | Python | 772 | 26 | import numpy as np
import pytest
from pandas import (
PeriodIndex,
period_range,
)
import pandas._testing as tm
class TestRepeat:
@pytest.mark.parametrize("use_numpy", [True, False])
@pytest.mark.parametrize(
"index",
[
period_range("2000-01-01", periods=3, freq="D"),
... |
6fca452a634452837994050260177c108c2300a98bee4872b79fc238adceea41 | Python | 775 | 29 | """
Depracated, using ``vectorized_value_and_grad`` instead for batched optimization
"""
import tensorcircuit as tc
from tensorcircuit.applications.dqas import (
parallel_qaoa_train,
single_generator,
set_op_pool,
)
from tensorcircuit.applications.layers import * # pylint: disable=wildcard-import
from ten... |
f2b6fbaecb2abc8a12cedcc27c56f9a58e28207fc68c34ad2ab5e40ba6e75199 | Python | 776 | 28 | import pytest
from pandas import (
Categorical,
CategoricalDtype,
Index,
IntervalIndex,
)
import pandas._testing as tm
class TestAstype:
@pytest.mark.parametrize("ordered", [True, False])
def test_astype_categorical_retains_ordered(self, ordered):
index = IntervalIndex.from_breaks(ran... |
fb98d18de32171b53599b768d1964e33dc87354004b3f5d062a81a762418b09b | Python | 776 | 30 | #!/usr/bin/env python3
import os
import re
def set_output(name: str, val: str) -> None:
print(f"Setting output {name}={val}")
if os.getenv("GITHUB_OUTPUT"):
with open(str(os.getenv("GITHUB_OUTPUT")), "a") as env:
print(f"{name}={val}", file=env)
else:
print(f"::set-output name... |
7468a8b3ed64f900467b0ed817338d653cd55b1cfe69801aaa571c976fe1e41a | Python | 777 | 27 | """A module with platform-specific extended precision
`numpy.number` subclasses.
The subclasses are defined here (instead of ``__init__.pyi``) such
that they can be imported conditionally via the numpy's mypy plugin.
"""
import numpy as np
from . import (
_80Bit,
_96Bit,
_128Bit,
_256Bit,
)
uint128 =... |
196329b3e2b384a4b579267d13fe1807303e02800f803b861428a74802a4a195 | Python | 779 | 26 | """Cere-MEG-Bellum (CMB)."""
import os as _os
from ._version import __version__
from .functions import get_cerebellum_data, get_plot_data_from_stc
from .segmentation import segment_cerebellum
from .source_space import create_cerebellar_surface, setup_full_source_space
# Deprecated, will just instruct users to use th... |
7bb179327aaa231ad3088053c904e230ef9ff225e9656b03af1a9a3d615cc224 | Python | 779 | 24 | import torch
import torch.nn as nn
"""
Learnable swish activation
"""
class Swish(nn.Module):
def __init__(self, num_features, initial_alpha=1.0, initial_beta=1.702):
super(Swish, self).__init__()
self.num_features = num_features
self.initial_alpha = initial_alpha
self.initial_bet... |
87e0233b8a380e0beb4f3b59677cc46ce9386657c222dd4ef77068b6d665afa6 | Python | 779 | 30 | import numpy as np
import logging
import yass
from yass import preprocess
from yass import detect
from yass import cluster
from yass import templates
np.random.seed(0)
# configure logging module to get useful information
logging.basicConfig(level=logging.INFO)
# set yass configuration parameters
yass.set_config('co... |
8ec2d62c77f33b6a51ba83edf4b69d4df2adde8d3ddef438a040c30e5392724f | Python | 779 | 20 | import sys
import numpy as np
import pandas as pd
import polars as pl
import pyranges as pr
pseudo_fragment = pl.read_csv(snakemake.input.pseudo_fragment_file, separator='\t', comment_prefix='#', n_threads=8)
pseudo_fragment.columns = ['chrom', 'chromStart', 'chromEnd', 'name', 'score']
# Filter for only the main 23... |
a743e8c088755cbff5791f2ca6cd55d71c7775d6f0dadf41a55b8fd35bb7126f | Python | 779 | 32 | """
The calculation of molecular connectivity indices based on its topological
structure(Chi). You can get molecular connectivity descriptors.
"""
from mordred import Calculator, descriptors
import numpy as np
_calc = Calculator(descriptors.Chi)
_ConnectivityNames = [str(i) for i in _calc.descriptors]
def GetCon... |
d5392ddf94ad64f1991c69cff741029387fe4bacca04e3e4f12acb96a62fb13e | Python | 779 | 27 | from __future__ import annotations
import pytest
from textstat.backend import metrics
from .. import resources
@pytest.mark.parametrize(
"text, lang, expected",
[
(resources.EMPTY_STR, "en_US", 0.0),
(resources.EASY_TEXT, "en_US", 4.004),
(resources.SHORT_TEXT, "en_US", 10.0),
... |
d437a76d287d9c44e3a82bc34b384b17bfe128a1aa5ab6ade150e7c1de4bb102 | Python | 781 | 25 | from Bio.Data import PDBData
from pathlib import Path
import unittest
from rna3db.parser import ModificationHandler
class TestModifications(unittest.TestCase):
modification_handler = ModificationHandler(
Path(__file__).parent / "test_data" / "modifications_cache.json"
)
def test_biopython_covera... |
530ae8de579330f43c9bc74c05be1cf80d1c3010cd32adef3a76e8fa5e55ef8b | Python | 782 | 37 | """Tests for fooof.plts.fm."""
from py.test import raises
from fooof import FOOOFGroup
from fooof.plts.fg import *
from fooof.tests.utils import plot_test
###################################################################################################
##############################################################... |
489e2beda7a9ec74ab4a03e1c74dac9a62dd38c651c14b96dea2d2e3abcf45b7 | Python | 784 | 36 | """
Command Line Interface (CLI). Easy to use + accessible remotely
Sources:
- Nice instructional video: https://www.youtube.com/watch?v=FWacanslfFM
- https://dojofive.com/blog/3-steps-to-make-a-professional-cli-tool-using-pythons-click/
"""
import os
import click
from FLightcase.server import server
from FLightcase... |
4739082fc217eb75f57e0c2bf28e3fc6e2af74eb4f1dda1d3dbb12ef9bbd0513 | Python | 785 | 31 | from dateutil.tz import tzlocal
import pytest
from pandas.compat import IS64
from pandas import date_range
@pytest.mark.parametrize(
"freq,expected",
[
("YE", "day"),
("QE", "day"),
("ME", "day"),
("D", "day"),
("h", "hour"),
("min", "minute"),
("s", "... |
e1b39cac9260927aa1900fcfbbf6a3f74ad4549a5b5f6e542f9efd862b2a62d5 | Python | 785 | 26 | from rna3db.utils import write_json
from rna3db.parser import parse_fasta
from collections import defaultdict
from pathlib import Path
import argparse
if __name__ == "__main__":
parser = argparse.ArgumentParser(
description="Converts a FASTA to an RNA3DB-style JSON."
)
parser.add_argument("input_... |
67192a5e6a0516380d0dc9e2371e533bb6bd1d6085e4c27511cd9aa331eddb12 | Python | 786 | 26 | # Tests for .AminoAcidVolumeChange
import pandas
import numpy
import pytest
import sbmlcore
def test_amino_acid_volume_change_value():
a = {'mutation': ['A1D', 'E2K']}
df = pandas.DataFrame.from_dict(a)
a = sbmlcore.AminoAcidVolumeChange()
df = a._add_feature(df)
assert 'd_volume' in df.columns
... |
6d8e73e41709e23ec6af73877c05407b01910996a99c46b792e4a238326fbd69 | Python | 787 | 37 | from PySide6.QtCore import QObject, Signal
from app.dataflow.qqueue import IQueue
class QListMeta(type(QObject), type(IQueue)):
pass
class QList(QObject, IQueue, metaclass=QListMeta):
"""
A thread-safe list with signals for changes
"""
list_changed = Signal()
list_cleared = Signal()
d... |
f10bbdfeea6df42d9a7b7bf7de8d02b0501bcef7b92618cca2c3d38fc221c783 | Python | 787 | 32 | """
Produce image with grey mask
author: Ana Luisa Pinho
date: July 2019
"""
import os
import numpy as np
import ibc_public.utils_data
from nilearn import plotting
import matplotlib
# Get grey matter mask
_package_directory = os.path.dirname(
os.path.abspath(ibc_public.utils_data.__file__))
mask = os.path.join... |
3c91c289b79c2655783cfb913d8c356069659822ce1f315bf2755be963fe0f4b | Python | 788 | 22 | import pytest
from cardio_audio_sleep.utils._imports import import_optional_dependency
def test_import_optional_dependency():
"""Test the import of optional dependencies."""
# Test import of present package
numpy = import_optional_dependency("numpy")
assert isinstance(numpy.__version__, str)
# T... |
5b88acc0077b9b23a708b2a7b2299f23c96335010b516292da98252b5fcf4fb5 | Python | 790 | 28 | from __future__ import annotations
import nltk
from ._typed_cache import typed_cache
from ._get_lang_root import get_lang_root
@typed_cache
def get_cmudict(lang: str) -> dict[str, list[list[str]]] | None:
"""Get a cmudict object for the given language. Currently only English is supported.
Parameters
----... |
c012df0cd2b75686e1666033de5e041012fda19d9a2d6670bc556465a7286e4a | Python | 790 | 25 | """
Functions for threshold detection
"""
import os
import logging
import numpy as np
from scipy.signal import argrelmin
def voltage_threshold(recording, threshold, order=5):
T, C = recording.shape
spike_index = np.zeros((0, 2), 'int32')
energy = np.zeros(0, 'float32')
for c in range(C):
sing... |
1d852799c877feff3de394d7f6af484fd46b1bbcd280a221b60da27b15694f15 | Python | 792 | 32 |
'''
====CAML v0.1====
cschwal's assisted machine learning suite for RODEO
'''
print(__doc__)
import svm_sample
import svm_optimize
invalidinp = True
def main():
print('Indicate which stage of SVM classification to perform:\n 1...splitting data set into training and fitting\n 2...optimizing hyperparameters\n 0.... |
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