sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
ca85fe778493bf01860a24111397090bd0ad7abebd4a0560a82971382bd23fb3 | Python | 541 | 27 | __all__ = [
"AbstractProvider",
"AbstractResolver",
"BaseReporter",
"InconsistentCandidate",
"RequirementsConflicted",
"ResolutionError",
"ResolutionImpossible",
"ResolutionTooDeep",
"Resolver",
"__version__",
]
__version__ = "1.2.1"
from .providers import AbstractProvider
fro... |
19172773c1b0263cec6c5c481d1f7b950b3de6bbb38f77b5980742bf8e2ee9e8 | Python | 543 | 20 | import os
data_file = 'wordlist.txt'
data_folder = '.'
input_encoding = 'cp1252' # latin-1 or utf-8 instead
output_encoding = 'utf-8'
if not os.path.exists(data_folder):
os.makedirs(data_folder)
with open(data_file, 'rb') as f:
for line in f:
line = line.decode(input_encoding)
name, value ... |
ef406dc1b8ef59517026b5a37bb1673da5051b05c0505cb82c70869aae638aae | Python | 544 | 21 | from __future__ import annotations
import pytest
from textstat.backend import metrics
from .. import resources
@pytest.mark.parametrize(
"text, expected",
[
(resources.EMPTY_STR, 0.0),
(resources.EASY_TEXT, 51.094),
(resources.SHORT_TEXT, 46.89),
(resources.PUNCT_TEXT, 49.945... |
bf4d9b2874c706045d33919e3a550fc76e5f64b01c99fa30576b1583b55a85ac | Python | 545 | 27 | import numpy as np
import pandas as pd
from tqdm import tqdm
from joblib import Parallel, delayed
import os
bitsize = 1024
total_sample = 110913349
data_save_folder = './data'
file = './data/%s_%s.npy' % (total_sample, bitsize)
f = np.memmap(file, dtype = np.bool, shape = (total_sample, bitsize))
def _sum(memmap... |
0153eb85f107aa384d41a6416e6fe7753051f86ce9b05702182bdee8f7af4835 | Python | 546 | 20 | from dataclasses import dataclass
from typing import Optional
@dataclass
class GrimaceConfig:
grimace_model: Optional[str] = "V1 - HohlBot"
frame_interval: float = 10.0
frame_quality_device: str = "cuda:0"
face_cropper_device: str = "cuda:0"
grimace_scoring_device: str = "cuda:0"
GRIMACE_MODE... |
2e7a4a9f37b79068f709d4d8d2897b4f543d0efb8b606d569faa1a6042051079 | Python | 548 | 23 | """Data classes used throughout cedalion."""
# FIXME for easier access classes are pulled from the sub-modules into this scope.
# Over time this may get crowded.
from .geometry import (
PointType,
Surface,
TrimeshSurface,
VTKSurface,
affine_transform_from_numpy,
Voxels,
)
from .schemas import ... |
d19338eaad7ebba50f01bba7a73e88b0be785bad23006ffb33983a3a61637897 | Python | 548 | 18 | import torch
from torch import nn
class GRN1d(nn.Module):
""" ConvNeXt v2 GRN (Global Response Normalization) layer, adapted for 1d
via facebookresearch/ConvNeXt-V2
"""
def __init__(self, dim):
super().__init__()
self.gamma = nn.Parameter(torch.zeros(1, 1, dim))
self.beta = nn... |
1ff0d3c0a5a5143778a9c54069e288a4310315eaf59445b09073924167c81e7b | Python | 549 | 19 | from app.dataflow.qqueue import QQueue, IQueue
from app.process.queue_process import QueueProcess
class QueuePacer(QueueProcess):
def __init__(self, queue_size: int, output_queue: IQueue, rate: float):
# TODO: find a better way to do pacing
super().__init__(queue_size, wait_time=1/rate*0.95-0.005,... |
7770628bbd6e67fc99e6f2101588eb811e10cfeed266f3130cf1f296830a72dc | Python | 549 | 18 | """
Probst, Daniel, and Jean-Louis Reymond. "A probabilistic molecular fingerprint for big data settings." Journal of cheminformatics 10.1 (2018): 66.'
orignal code: https://github.com/reymond-group/mhfp
"""
from mhfp.encoder import MHFPEncoder
def GetMHFP6(mol, nBits=2048, radius = 3):
"""
MHFP6: radius=... |
dfa3cd3f133c1b0c6576f4eb5862444f8f101a456db3bb3cc3e39bd2e5d1817f | Python | 549 | 25 | from __future__ import annotations
import pytest
from textstat import textstat
from ..backend import resources
@pytest.mark.parametrize(
"lang,expected",
[
("en_US", 139),
("en_GB", 139),
("en", 139),
("de_DE", 145),
("de", 145),
("es_ES", 172),
("fr_FR... |
60660f614f51237b0b3965010e33c37c129ac7ea86a42a9b8a96763b7454a6ec | Python | 550 | 20 | 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", 4.0),
(resources.SHORT_TEXT, "en_US", 2.0),
(... |
ea68756e4d2ea7417fcc3edf3f840c70f26b5c30a3fd558c30f269b095be3229 | Python | 552 | 15 | import pandas as pd
def make_pcawg_df(snv_file: str):
vcf_columns = ['chr', 'pos', 'id', 'ref', 'alt', 'qual', 'filter', 'info']
df = pd.read_csv(snv_file, comment='#', names=vcf_columns, sep='\t', index_col=False)
df = df.sort_values(by=['chr', 'pos'])
df = df[
df.chr.isin([f'chr{chrom}' for c... |
45261d1161eb3bc913b2259f00c3c20d87ced2d2384b5c8ba2039d1e2b41afdc | Python | 553 | 26 | from __future__ import annotations
from functools import lru_cache
from typing import Callable, TYPE_CHECKING
from .constants import CACHE_SIZE
if TYPE_CHECKING:
from .constants import T, P
def typed_cache(func: Callable[P, T]) -> Callable[P, T]:
"""Decorator to cache function results without losing type i... |
8c1dd7081980b5ca9ff966fd3f0056eae23290fa4c3ed86e5cb2748224cacd91 | Python | 554 | 16 | import numpy as np
from numpy.testing import assert_, assert_equal, assert_array_equal
class TestView:
def test_type(self):
x = np.array([1, 2, 3])
assert_(isinstance(x.view(np.matrix), np.matrix))
def test_keywords(self):
x = np.array([(1, 2)], dtype=[('a', np.int8), ('b', np.int8)])
... |
2ae76bc67e4d49740b5c29334bdfae04b937a655f492bfe17e3e98504f3fd95e | Python | 555 | 25 | from setuptools import setup, find_packages
setup(
name="spinextract",
version="0.0",
packages=find_packages(),
install_requires=[
"setuptools>=62.0.0",
"pip>=22.0.0",
"pytest",
"yapf",
"tqdm",
"pyyaml",
"pandas",
"matplotlib",
"ti... |
d4182f96f3ad462700e025997413d1c08e2088d3f589b7d83ac3f99b33e878c9 | Python | 555 | 22 | from .cluster import Cluster
from .composerlifneuron import ComposerLIFNeuron
class ComposerCluster(Cluster):
'''
classdocs
'''
def __init__(self, neutype, neunum):
'''
Constructor
'''
Cluster.__init__(self, neutype, neunum)
def createClusterNetwork(self):
... |
fb2cd0fdef8cdedfcdbe2631ec8462b2f85a0a0f945018bcf1b4d63440631e40 | Python | 555 | 34 | """Enum for comparison types."""
# from python
from enum import Enum
class ALIGNMENT_MODE(Enum):
GLOBAL = "global"
GLOCAL = "glocal"
LOCAL = "local"
AUTO = "auto"
class EXTEND_STRATEGY(Enum):
LEGACY = "legacy"
GREEDY = "greedy"
SIMPLE_MATCH = "simple_match"
class COMPARISON_MODE(Enum)... |
021d6e262ad25aa6cd772c947d29c13ba6c1c71deef1aff701c2a4e207ab8951 | Python | 556 | 21 | from .legacy_output import (
legacy_prepare_output,
legacy_prepare_cutoff_output,
legacy_prepare_bin_output,
legacy_generate_bin_output,
write_record_annotations_file,
write_clustering_file,
write_cutoff_network_files,
write_full_network_file,
)
__all__ = [
"legacy_prepare_output",
... |
4c07375c16443e6fc5a98c2e80c8ca985e1beb82653351604258700a2df9765d | Python | 556 | 23 | from __future__ import annotations
from ..utils._typed_cache import typed_cache
from ..counts._count_chars import count_chars
@typed_cache
def reading_time(text: str, ms_per_char: float) -> float:
"""Calculate reading time (Demberg & Keller, 2008).
Parameters
----------
text : str
A text str... |
a31c7ecdb6b775a33afd6be70f4c76d9346e8397a7b59c882b0b56cedcbd4166 | Python | 556 | 20 | from __future__ import annotations
import pytest
from textstat.backend import counts
from .. import resources
@pytest.mark.parametrize(
"test, threshold, expected",
[
(resources.EASY_TEXT, 6, 13),
(resources.SHORT_TEXT, 6, 1),
(resources.SHORT_TEXT, 5, 1),
(resources.SHORT_TEX... |
afdd1648f12af9d0c72a5c5437d444a463d24a3553e61ffa78f11089a452ae2d | Python | 556 | 17 | from typing import Callable
import torch
def withCUDA(func: Callable) -> Callable:
r"""A decorator to test both on CPU and CUDA (if available).
Borrowed from https://github.com/pyg-team/pytorch_geometric/blob/0419f0f2d372056b0d7b939e15069b41b35a98a7/torch_geometric/testing/decorators.py
"""
import p... |
cb9fc8c81535c9d7474ac800306165404bb38124f6546cc38f95f7e7e9316c92 | Python | 556 | 15 | import pytest
import cedalion.utils as utils
def test_zero_padded_numbers():
assert utils.zero_padded_numbers([1, 2, 3]) == ["1", "2", "3"]
assert utils.zero_padded_numbers([1, 9, 30]) == ["01", "09", "30"]
assert utils.zero_padded_numbers([1, 19, 300]) == ["001", "019", "300"]
assert utils.zero_padd... |
30934fa5f23170ef85821c6905bc641b5ac58907fa1ce51b5785399aad07167b | Python | 557 | 21 | """This is a subpackage because the directory is on sys.path for _in_process.py
The subpackage should stay as empty as possible to avoid shadowing modules that
the backend might import.
"""
import importlib.resources as resources
try:
resources.files
except AttributeError:
# Python 3.8 compatibility
def ... |
c4c9b02e7a576868af4f0e39d170388ea204353719fae7c5ae7d107d1ef2d66f | Python | 558 | 20 | import subprocess
print("Running Codespell:\n")
codespell_command = (
"pipenv run codespell -L paket,nd --skip=./textstat/resources/**/"
"easy_words.txt,./build/*,./textstat.egg-info/*,./.git/*,./tests/* "
"--exclude-file=.codespellignorelines"
)
subprocess.run(codespell_command.split())
print("\n\nRunni... |
7b22d96b88a64f541d77b3c26c35fd97412d0eedfd4fcd1e0ab4ab7b6c264ee1 | Python | 559 | 26 | """
Tests for behavior if an author does *not* implement EA methods.
"""
import numpy as np
import pytest
from pandas.core.arrays import ExtensionArray
class MyEA(ExtensionArray):
def __init__(self, values) -> None:
self._values = values
@pytest.fixture
def data():
arr = np.arange(10)
return My... |
c6cf9396f6d6a04b197c1263ed5e116113a0ef94587eb1b87bc6e2d48cf9f295 | Python | 559 | 20 | import sys, pandas
file_location = sys.argv[1]
sample_name = file_location.rsplit("/", 1)[1]
header_taxonomy = [
"Percent",
"RawNumber1",
"RawNumber2",
"Rank",
"NCBI_Taxon_Id",
"Name"
]
taxonomy = pandas.read_csv(file_location+"-kraken.txt", sep="\t", header=None, names=head... |
16ff531d074b6cd68b7d760610a389a8533d346f7bb9b3f55e90f8219d09cd23 | Python | 560 | 22 | import click
ch_name_ecg = click.option(
"--ch-name-ecg",
prompt="ECG channel name",
help="Name of the ECG channel in the stream.",
type=str,
)
stream = click.option(
"--stream",
prompt="LSL stream name",
help="Name of the stream to use for the synchronous task.",
type=str,
)
verbose = ... |
0b6eb6b340d767a750a53e5a36cb349f7bdd155a87903896273a218e1c5d1c3b | Python | 561 | 20 | import numpy as np
import os
def remove_off_centered_units(templates, threshold=5, units_in=None):
if units_in is None:
n_units = templates.shape[0]
units_in = np.arange(n_units)
# compute min points
mc = templates[units_in].ptp(1).argmax(1)
min_points = np.zeros(len(units_in))
fo... |
103b300cb30936e4e17a33f5332fb3146662056e9408233af7afb0ed5f5df645 | Python | 561 | 16 | import pandas as pd
# Read the files
candidates_df = pd.read_csv('CT2_log/euclidean/final_candidate/candidate_genes.csv')
dataset_df = pd.read_csv('results/dataset_method_comparison.csv')
# Find overlap
overlap_genes = candidates_df[candidates_df['Gene Name'].isin(dataset_df['Gene Name'])]
# Save overlap to file
ove... |
304970581d8ca139efc29f8e53b8c91f9d59cca454ca01bf63982ccbcb9b93c5 | Python | 563 | 22 | import torch
import torch.nn as nn
def l2loss_atomwise(pred, target, reduction="mean"):
dist = torch.linalg.vector_norm((pred - target), dim=-1)
if reduction == "mean":
return torch.mean(dist)
elif reduction == "sum":
return torch.sum(dist)
else:
return dist
class L2Loss(nn.M... |
9179c28ad6830cdd2e286aaa0c6964465a793c9119b8a530ec7333c0be092617 | Python | 563 | 14 | import json
import typing
def load_tokenizer(tokenizer_path: str) -> typing.Tuple[typing.Dict[str, int], int]:
with open(tokenizer_path, "r") as rf:
tokenizer = json.load(rf)
return tokenizer, len(tokenizer)
def tokenize_sequence(tokenizer: typing.Dict[str, int], seq: str) -> typing.List:
for na ... |
89c49e1fd83609d8b5226536ee28c73459d5ef872f1a6f6dce4622dc9ffbaa38 | Python | 565 | 20 | 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", 1.404),
(resources.SHORT_TEXT, "en_US", 1.4),
... |
5459bd41846913045ce78d3eb6a9de50da70d1648288d0bf2e93f8e6bde76abd | Python | 567 | 20 | 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", 3.585),
(resources.SHORT_TEXT, "en_US", 3.264),
... |
30c2679d03b2e1676900b14dce5c5e579d9d7f55a425f0fefeed23ec73ccdada | Python | 568 | 19 | """Contains errors raised for gene bank parsing"""
class InvalidGBKError(Exception):
"""Raised when a validation error occurs in parsing a GBK"""
def __init__(self) -> None:
super().__init__(
"Validation error occurred when parsing a GenBank file, see log for more info"
)
class ... |
7142a70b100222aed427b126ce9067f7fe9cee47409ea9d852f20115ad0ee502 | Python | 568 | 24 | import numpy as np
from omegaconf import DictConfig
class StandardScaler:
"""
Standard the input
"""
def __init__(self, mean: np.array, std: np.array):
self.mean = mean
self.std = std
def transform(self, data: np.array):
return (data - self.mean) / self.std
def inver... |
c414d7ee901e677a39c6c1a31c1450040464da30c4cab36fe037f0a6a98beee3 | Python | 568 | 19 | 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... |
46a204ac1a1f227e44c21f8ca2655e3c73a7d2156265b7b895a302daf87c9cfb | Python | 570 | 23 | import pytest
from pandas import PeriodIndex
def test_is_full():
index = PeriodIndex([2005, 2007, 2009], freq="Y")
assert not index.is_full
index = PeriodIndex([2005, 2006, 2007], freq="Y")
assert index.is_full
index = PeriodIndex([2005, 2005, 2007], freq="Y")
assert not index.is_full
... |
4b89314d4c76496cea85d24f35c52216b2548f8ccf4d7ee2394435898d8a0105 | Python | 570 | 22 | from __future__ import annotations
import pytest
from textstat.backend import metrics
from .. import resources
@pytest.mark.parametrize(
"text, expected",
[
(resources.EMPTY_STR, 0.0),
(resources.EASY_TEXT, 83.208),
(resources.SHORT_TEXT, 84.483),
(resources.PUNCT_TEXT, 76.42... |
c59e74c3382ba72a936ea9410479a678500b6d6938962c5be68fe4a1c2c64edf | Python | 570 | 25 | from __future__ import annotations
import pytest
from textstat.backend import utils
@pytest.mark.parametrize(
"lang, expected",
[
("en_US", dict),
("en_GB", dict),
("en", dict),
("es", None),
("es_ES", None),
("de", None),
("de_DE", None),
("fr"... |
1fc81da3481f2d62be336454b16698e81455b2e543dbb60774da3fbd03654d70 | Python | 571 | 15 | from .bernstein_radial_basis_functions import *
from .clebsch_gordan import *
from .energy_layer import *
from .exponential_bernstein_radial_basis_functions import *
from .exponential_gaussian_radial_basis_functions import *
from .gaussian_radial_basis_functions import *
from .interaction_block import *
from .modular_b... |
814925a86544a894ad9fecdd021ad06946b8bfcd926997ed9f7eb08a9b6a01aa | Python | 571 | 20 | 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", 4.488),
(resources.SHORT_TEXT, "en_US", 2.88),
... |
cc5cd54af3a98c7900f7fb4407698f9dfabd3c9201b816b89428ba06f5db0431 | Python | 571 | 21 | import numpy as np
import pytest
from pandas import DataFrame
@pytest.mark.parametrize(
"data, index, expected",
[
({"col1": [1], "col2": [3]}, None, 2),
({}, None, 0),
({"col1": [1, np.nan], "col2": [3, 4]}, None, 4),
({"col1": [1, 2], "col2": [3, 4]}, [["a", "b"], [1, 2]], 4... |
d139a725e64239a4d69de79603ae839712a06946494df3f48ca80b018d638b28 | Python | 571 | 23 | import pytest
import pandas as pd
class TestResolution:
@pytest.mark.parametrize(
"freq,expected",
[
("Y", "year"),
("Q", "quarter"),
("M", "month"),
("D", "day"),
("h", "hour"),
("min", "minute"),
("s", "second")... |
63467a5a15ca63a3ee4db1643a478407321f8430e0e457aa560f1a269ea52190 | Python | 572 | 14 | #
# This file is part of gunicorn released under the MIT license.
# See the NOTICE for more information.
# supported gunicorn workers.
SUPPORTED_WORKERS = {
"sync": "gunicorn.workers.sync.SyncWorker",
"eventlet": "gunicorn.workers.geventlet.EventletWorker",
"gevent": "gunicorn.workers.ggevent.GeventWorker"... |
f913bea7045163ddc54273a304bb357cc55feee042a0419190658f01d5fc96d5 | Python | 573 | 20 | import pytest
import pandas as pd
import pandas._testing as tm
@pytest.mark.parametrize(
"to_concat_dtypes, result_dtype",
[
(["Float64", "Float64"], "Float64"),
(["Float32", "Float64"], "Float64"),
(["Float32", "Float32"], "Float32"),
],
)
def test_concat_series(to_concat_dtypes,... |
3da9261c93377bc38e592645b5fcf5033edfd6678e3499e41ae431165b77c011 | Python | 575 | 25 | """
For types associated with installation schemes.
For a general overview of available schemes and their context, see
https://docs.python.org/3/install/index.html#alternate-installation.
"""
from dataclasses import dataclass
SCHEME_KEYS = ["platlib", "purelib", "headers", "scripts", "data"]
@dataclass(frozen=True... |
f526db9c59d56d22556714c5a15f69c2539c3350f7d069ce5a6d90a27403bc72 | Python | 575 | 15 | """ Override the develop command from setuptools so we can ensure that our
generated files (from build_src or build_scripts) are properly converted to real
files with filenames.
"""
from setuptools.command.develop import develop as old_develop
class develop(old_develop):
__doc__ = old_develop.__doc__
def inst... |
eb60caa33ce66bc07f294a1dfab74a0eb352c6ca507e7cbaf838a20de5afa248 | Python | 576 | 14 | # 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.
""" antiSMASH (antibiotics & Secondary Metabolite Analysis Shell):
Genome mining and secondary metabolite biosynthetic gene cluster detection
and analysis.
T... |
448b2a48fefda253dd3a0b4f296fa8390dfae08095a297a103a45f1a445f7b6b | Python | 577 | 20 | from typing import Callable, Optional
from pip._internal.req.req_install import InstallRequirement
from pip._internal.req.req_set import RequirementSet
InstallRequirementProvider = Callable[
[str, Optional[InstallRequirement]], InstallRequirement
]
class BaseResolver:
def resolve(
self, root_reqs: l... |
ecd643451cd1680f52de65c808fcc8f8c06724708daf09ff310599c5bc10e7a9 | Python | 577 | 25 | import torch
from .rk_common import _ButcherTableau, RKAdaptiveStepsizeODESolver
_ADAPTIVE_HEUN_TABLEAU = _ButcherTableau(
alpha=torch.tensor([1.], dtype=torch.float64),
beta=[
torch.tensor([1.], dtype=torch.float64),
],
c_sol=torch.tensor([0.5, 0.5], dtype=torch.float64),
c_error=torch.te... |
d96182b0d071b47e7b063018c8f033519822051616010a42f733833f4d8e65e7 | Python | 582 | 18 | import sys
import pytest
from . import util
from numpy.testing import IS_PYPY
@pytest.mark.slow
class TestBlockDocString(util.F2PyTest):
sources = [util.getpath("tests", "src", "block_docstring", "foo.f")]
@pytest.mark.skipif(sys.platform == "win32",
reason="Fails with MinGW64 Gfortr... |
25059c12f8d8fdb8e168c1d7639bc393af4e2283335f946f6e7d5e196d850af1 | Python | 584 | 16 | def __getattr__(attr_name):
import warnings
from numpy.linalg import _linalg
ret = getattr(_linalg, attr_name, None)
if ret is None:
raise AttributeError(
f"module 'numpy.linalg.linalg' has no attribute {attr_name}")
warnings.warn(
"The numpy.linalg.linalg has been made p... |
4dc956f4ff8bf6fe2a1b21fa537f84b7bcb334519c7dfc8928d6853168d99c4d | Python | 584 | 19 | import viz
def flipImage(axis):
#Flip rendered image horizontally
if axis != False:
flipWindow = viz.addWindow(size=(1,1),pos=(0,1),clearMask=0,order=100)
flipWindow.setView(viz.addView(scene=viz.addScene()))
import vizfx.postprocess.manager as pp
from vizfx.postprocess.transform import FlipEffect
pp.g... |
c6cfd0e898eee2b464bd15fa879e170f2cb809df9eabfbef3222b5dc62db3f9d | Python | 585 | 20 | # -*- coding: utf-8 -*-
import os
import sys
from pathlib import Path
sys.path.append(os.path.dirname(os.path.abspath(__file__)))
class Config:
def __init__(self):
self.project_dir = str(Path(__file__).parent.parent.parent.absolute())
self.data_dir = os.path.join(self.project_dir, 'dataset', 'REP... |
e022ee4b25f3ac2266d549e46f4cde122b288f73e7998f71ee6c41cd6193b12d | Python | 586 | 20 | 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", 7.592),
(resources.SHORT_TEXT, "en_US", 13.358),
... |
eaec8424d7a39826f4e1b92d2c974cec70b735fb5d3b7deeefa51acc60b07163 | Python | 587 | 24 | from __future__ import annotations
from ..utils._typed_cache import typed_cache
from ._count_syllables import count_syllables
from ..selections._list_words import list_words
@typed_cache
def count_monosyllable_words(text: str, lang: str) -> int:
"""Counts words with only one syllable in a text.
Parameters
... |
5a5fa3fd7a661020d48e6bcd5f85fb120e77ffc7bc39f7e8defd6ea777ff24ef | Python | 590 | 20 | from omegaconf import DictConfig, open_dict
from .abcd import load_abcd_data
from .abide import load_abide_data
from .dataloader import init_dataloader, init_stratified_dataloader
from typing import List
import torch.utils as utils
def dataset_factory(cfg: DictConfig) -> List[utils.data.DataLoader]:
assert cfg.d... |
65afe7f389ac5ad57c76a41984c86f87b973bb9599bcef22c533e412a3b61e6b | Python | 590 | 22 | """Based on the `if __name__ == "__main__"` test code in `lib/_user_array_impl.py`."""
from __future__ import annotations
import numpy as np
from numpy.lib.user_array import container
N = 10_000
W = H = int(N**0.5)
a: np.ndarray[tuple[int, int], np.dtype[np.int32]]
ua: container[tuple[int, int], np.dtype[np.int32]]... |
0385a23c1300a4886fbea48ec39b3f3a61813681faa4c29454e4c7c37e530804 | Python | 593 | 19 | import tensorflow as tf
from tensorflow.keras.callbacks import Callback
from .metrics import calculate_metrics
class TBMetricCallback(Callback):
def __init__(self, log_dir, x, y):
super().__init__()
self.x = x
self.y = y
self.writer = tf.summary.create_file_writer(log_dir + "/metr... |
8a587f222f576b47cdd5ef50e2cf4c8e58e039c5c05074e78cf02fe7f87686c7 | Python | 593 | 20 | 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", 6.794),
(resources.SHORT_TEXT, "en_US", 7.043),
... |
227a552a80c0ccc28efe5fc735c6adce25bfbb593dfc96737bffedda7c9bacbd | Python | 595 | 22 | """Common test support for all numpy test scripts.
This single module should provide all the common functionality for numpy tests
in a single location, so that test scripts can just import it and work right
away.
"""
from unittest import TestCase
from . import _private
from ._private.utils import *
from ._private.ut... |
17b7c1a041be9a7bb5eb2a566262b9c1b228bd024a2f487ce82d4ccc69213e81 | Python | 597 | 22 | from pandas import (
Index,
NaT,
Timedelta,
TimedeltaIndex,
)
import pandas._testing as tm
class TestFillNA:
def test_fillna_timedelta(self):
# GH#11343
idx = TimedeltaIndex(["1 day", NaT, "3 day"])
exp = TimedeltaIndex(["1 day", "2 day", "3 day"])
tm.assert_index_... |
508e7efcb8ae2886cf2581f12e09373a8e8e3389e9f1f9992ddf1543592cf23b | Python | 597 | 15 | import matplotlib as mpl
mpl.use("pgf")
import matplotlib.pyplot as plt
plt.rcParams.update({
"font.family": "serif", # use serif/main font for text elements
"text.usetex": True, # use inline math for ticks
"pgf.rcfonts": False, # don't setup fonts from rc parameters
"pgf.preamble": [
"... |
0fe1c4b220012a7deb799c15bf3902b8d3a8e7945e5155d59003cc71cc47772c | Python | 598 | 23 | """
Detecting spikes
"""
import logging
import yass
from yass import preprocess
from yass import detect
# configure logging module to get useful information
logging.basicConfig(level=logging.INFO)
# set yass configuration parameters
yass.set_config('config.yaml', 'example-detect')
# run preprocessor
standardized_pa... |
436e7aa63b66498b3a8ed5bb0f64cf05fb3a4d42ce80f7adfa7c5ed411444a4a | Python | 599 | 35 | from sqlalchemy_data_model_visualizer import generate_data_model_diagram
from cali.sqlmodel._model import (
FOV,
ROI,
AnalysisSettings,
CaliResult,
Condition,
DataAnalysis,
DetectionSettings,
Experiment,
Mask,
Plate,
Traces,
Well,
WellCondition,
)
models = [
Cal... |
02ada7af3f9757fe3bd8ed2720733459520933e37ad7c2bd4f2a1e3d73d0e418 | Python | 602 | 21 | # Copyright (C) 2008-2011,2013 Bernd Feige
# This file is part of avg_q and released under the GPL v3 (see avg_q/COPYING).
"""
avg_q module root directory.
"""
__all__=[
'avg_q',
'Script',
'Epochsource',
'avg_q_file',
'escape_filename',
'escape_channelname',
'unescape_channelname',
'channel_list2arg',
'channe... |
eafa2bfdea846cc29c04b1247dac97cd5cf0c1fe4165c0af421159baa86fc8a5 | Python | 603 | 28 | import numpy as np
import pytest
from pandas import (
DataFrame,
NaT,
Series,
Timestamp,
)
@pytest.mark.parametrize(
"data,exp_size",
[
# see gh-16362.
([[NaT, "a", "b", 0], [NaT, "b", "c", 1]], 8),
([[NaT, "a", 0], [NaT, "b", 1]], 6),
],
)
def test_maybe_infer_to_... |
fec6c386eab9dea6105472c0c0a70b7c9b7fbea10a9c2eb8ec41f1fa07000991 | Python | 603 | 21 | 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", 1.195),
(resources.SHORT_TEXT, "en_US", -0.647),
... |
ee58450c188f8a325d8cd7da3f7a844fd46d063507fedbd30915452eb425fd39 | Python | 605 | 25 | import time
import numpy as np
def get_mean_roi(n_rois, tbvNetInt, time_point):
"""
Retrieves Mean ROI Activation for all ROIs.
Args:
n_rois: int - number of ROIs
tbvNetInt: TBVNetworkInterface instance
time_point: int - time point to retrieve (0-based)
Returns:
tuple:... |
05a7fb9b47f80f0ed219fcb531a71f5240c121d34304dd4326bccbe6aa9da026 | Python | 607 | 19 | """Burst activity plotting functions."""
from ._plot_burst_activity import (
_plot_calcium_burst_activity,
_plot_calcium_normalized_with_bursts,
_plot_calcium_raster_with_bursts,
_plot_inferred_spike_burst_activity,
_plot_inferred_spike_raster_with_bursts,
_plot_inferred_spikes_normalized_with_... |
0349cd537ce75eceb8589a102bc87e06d5d595cd4bb8d489a26696960acfcca6 | Python | 608 | 28 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sun Aug 25 20:29:36 2019
@author: charleshen
@note: calculation of AdjacencyMatrix, BaryszMatrix, DetourMatrix, DistanceMatrix descriptors
"""
from mordred import Calculator, descriptors
import numpy as np
_calc = Calculator([descriptors.AdjacencyMatrix... |
833fc09489a752500171c3778f041d03ac4bf0f301c52cdc8142c221cef6cfe4 | Python | 608 | 16 | from cardio_audio_sleep.utils.blocks import _BLOCKS, generate_blocks_sequence
def test_generate_blocks_sequence():
"""Test generation of a random block sequence."""
blocks = list()
for _ in range(22):
blocks.append(generate_blocks_sequence(blocks))
assert blocks[0] == "baseline"
assert blo... |
b2daf4349d6fa4b3650bfdef31fba54eef43f7f713871286db391a1ae6793536 | Python | 610 | 16 | def __getattr__(attr_name):
import warnings
from numpy.fft import _helper
ret = getattr(_helper, attr_name, None)
if ret is None:
raise AttributeError(
f"module 'numpy.fft.helper' has no attribute {attr_name}")
warnings.warn(
"The numpy.fft.helper has been made private an... |
ec5c0a4772de18e0ae69c304f72ebf7bba65ee5bcf8ede21b49cb1d3ac6ec56c | Python | 610 | 19 | from weasyprint import HTML, CSS
import argparse
def main(input_html,output_pdf):
css = CSS(string='''
@page {
size: 1800mm 1300mm;
margin: 0in 0in 0in 0in;
}
''')
HTML(input_html).write_pdf(output_pdf, stylesheets=[css])
if __name__=="__main__":
parser = argparse.ArgumentParser(description='Conve... |
25405af7a2d7e0d9978605cdca8f39f48c0c5c4976f44ca199174ca10a359fbf | Python | 611 | 29 | from __future__ import annotations
from typing import TYPE_CHECKING
import numba
if TYPE_CHECKING:
import numpy as np
@numba.jit(
# error: Any? not callable
numba.boolean(numba.int64[:]), # type: ignore[misc]
nopython=True,
nogil=True,
parallel=False,
)
def is_monotonic_increasing(bounds: ... |
b114acddd2ea2559d2b4291362f930a1fa1ef1f3c6e973a29ac6162a812bb3b8 | Python | 611 | 17 | """
Neuropixel spike sorting: http://data.cortexlab.net/singlePhase3/
"""
import os.path as path
import numpy as np
# download rawDataSample.bin, channel_map.npy and channel_positions.npy
# from here: http://data.cortexlab.net/singlePhase3/data/
ROOT = '/Users/Edu/data/ucl-neuropixel/'
channel_map = np.load(path.join... |
38d22b413a7e85e895b57dc76440290200bf873af80321aec561592f91631e1e | Python | 612 | 20 | ##########################################################################
# 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.
##########... |
bcef2dc3ff22ced450082394a076543eec0b1f3e7da725fc9040b3c837d8f3a0 | Python | 612 | 22 | from __future__ import annotations
import pytest
from textstat.backend import counts
from .. import resources
@pytest.mark.parametrize(
"text,expected",
[
(resources.EMPTY_STR, 0),
(resources.EASY_TEXT, 11),
(resources.SHORT_TEXT, 1),
(resources.PUNCT_TEXT, 5),
(resour... |
a157f8661a4450c4b4434a0337b46723ff1ecd18e350ab63c3e0f3f86ae41163 | Python | 613 | 23 | from __future__ import annotations
from ..utils._typed_cache import typed_cache
from ..selections._list_words import list_words
@typed_cache
def count_long_words(text: str, threshold: int = 6) -> int:
"""Counts words with more than `threshold` letters.
Parameters
----------
text : str
A text... |
f3fe11c80392d9d607444227088d151668bfabccc5ddb07ac8b869846d35a7ba | Python | 613 | 23 | import tensorcircuit as tc
K = tc.set_backend("tensorflow")
nwires, nlayer, nbatch = 6, 3, 16
def yp(img, params):
c = tc.Circuit(nwires)
for i in range(nwires - 1):
c.rx(i, theta=img[i])
for j in range(nlayer):
for i in range(nwires - 1):
c.rzz(i, nwires - 1, theta=params[i +... |
022aca9fc6daeb189261312cc7192e1b3da0546c68c018bde645d50629960cc1 | Python | 614 | 17 | import torch
import torch.nn as nn
class Discriminator(nn.Module):
"""PatchGAN-based Discriminator"""
def __init__(self, in_channels=3):
super().__init__()
self.model = nn.Sequential(
nn.Conv2d(in_channels, 64, 4, stride=2, padding=1),
nn.LeakyReLU(0.2),
... |
641e5795c09aadcd1d89fa7d885d831f442c461aa0edfd137794d4438967d36d | Python | 614 | 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.
""" Contains various error classes for use throughout antiSMASH """
class AntismashError(Exception):
""" A general catch-all for errors within antiSMASH """
pass... |
b1e27f1ee1ecd4af0771441f52ee4e90eca2e6ea71592a3b60228136f3516cb2 | Python | 614 | 26 | from __future__ import annotations
from ..utils._typed_cache import typed_cache
from ..selections._list_words import list_words
@typed_cache
def count_miniwords(text: str, max_size: int = 3) -> int:
"""Count common words with `max_size` letters or less in a text.
Parameters
----------
text : str
... |
c8e87cc5a077ff266ed69840d9095e1723af497117f744fb38b73d1068b74952 | Python | 614 | 22 | from skimage.measure import regionprops
from functools import cached_property
import numpy as np
class SegmentationAnalyzer:
def __init__(self, labels, res):
self._labels = labels
self._regions = regionprops(labels, spacing=res)
@cached_property
def volume(self):
area = [i.area fo... |
ed4116ebac59d864820d8e935354d90fd4e7cf445fe69e9787c88f81ecd145f8 | Python | 614 | 21 | from __future__ import annotations
from typing import Iterator, Dict, Optional
import itertools
class Thought:
"""
Represents an LLM thought with its state, constructed by the parser, and various flags.
"""
_ids: Iterator[int] = itertools.count(0)
def __init__(self, state: Optional[Dict] = None)... |
9ec78fe9e0e42e388d20e4b19b610315391e993a8d15436abef349a4c88d6556 | Python | 615 | 24 | import numpy as np
from pandas import (
DataFrame,
Index,
Series,
)
import pandas._testing as tm
def test_corrwith_with_1_axis():
# GH 47723
df = DataFrame({"a": [1, 1, 2], "b": [3, 7, 4]})
gb = df.groupby("a")
msg = "DataFrameGroupBy.corrwith with axis=1 is deprecated"
with tm.asser... |
ccfe8aeb7a49f2e325c43707d79c8392b76704caa75a3144daffccdb8d780393 | Python | 619 | 21 | import numpy as np
def fba(imgs, p="infinity"):
# images to Fourier domain
vs_hat = [np.fft.rfftn(img) for img in imgs]
if p == "infinity" or p == "inf":
out_img = np.max(vs_hat, axis=0)
else:
p = float(p)
# calculate fourier magnitude weights
denominator = np.sum([np.... |
32a6a6ebb58ef4891399417223aeaf4ba2284974e9f46dfcf0369d1f62c230b6 | Python | 620 | 24 | # -*- coding: utf-8 -*-
import sys
try:
from ._version import version as __version__
except ImportError:
__version__ = 'unknown'
__all__ = ['easter', 'parser', 'relativedelta', 'rrule', 'tz',
'utils', 'zoneinfo']
def __getattr__(name):
import importlib
if name in __all__:
return i... |
e51075ef70332aa84742cea8e8c27a6cf2fce5f50738ce7a390a10e0db0db7ef | Python | 620 | 24 | import io
import os
import sys
import cairosvg
from PIL import Image
def load_svg_image(filename, width=None, height=None):
if getattr(sys, 'frozen', False):
base_path = sys._MEIPASS
else:
base_path = os.path.abspath(".")
svg_path = os.path.join(base_path, filename)
# Read SVG file... |
375eee1bb19f8942375d1afeee92e4e74b93c728f18fe2690e545e61ffb0072f | Python | 623 | 34 | """
Created on Jun 5, 2024
@author: mning
"""
import logging
from typing import Callable
from src.features import getSpecStatsMd
# import getMin
# import getSTD
logger = logging.getLogger("root")
typeFnList = list[Callable]
def getPSDFnSbj() -> typeFnList:
featFnList = []
featFnList.append(getSpecStatsMd... |
9711c371459aadec215f46c6462589c9a650fcd7c87a5b9210699f2911da8e0f | Python | 623 | 21 | 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", 110.363),
(resources.SHORT_TEXT, "en_US", 114.615),
... |
0dea37ba8f7c694c887dd28936aa1f7921055b00f3ad5d907862d72ec82ad008 | Python | 625 | 33 | # -*- coding: utf-8 -*-
#
# Copyright (C) 2012-2024 Vinay Sajip.
# Licensed to the Python Software Foundation under a contributor agreement.
# See LICENSE.txt and CONTRIBUTORS.txt.
#
import logging
__version__ = '0.4.0'
class DistlibException(Exception):
pass
try:
from logging import NullHandler
except Imp... |
83d3e1c8b3baadf9581d9b66af2c755564ee6e984de1300f5127e8898ae24ea1 | Python | 625 | 45 | import numpy as np
from numpy import f2py
np.char
np.ctypeslib
np.emath
np.fft
np.lib
np.linalg
np.ma
np.matrixlib
np.polynomial
np.random
np.rec
np.strings
np.testing
np.version
np.lib.format
np.lib.mixins
np.lib.scimath
np.lib.stride_tricks
np.lib.array_utils
np.ma.extras
np.polynomial.chebyshev
np.polynomial.hermi... |
20873d1ef9a12937b27d9f07f3c857a5788972a610c15d74b72091604dc901f7 | Python | 626 | 18 | from qtpy.QtWidgets import QDialog, QDialogButtonBox, QVBoxLayout, QLabel
class SaveDialog(QDialog):
def __init__(self, parent):
super().__init__(parent=parent)
QBtn = QDialogButtonBox.Yes | QDialogButtonBox.No
self.buttonBox = QDialogButtonBox(QBtn)
# self.buttonBox.accepted.con... |
3758183cfa796969cd169e350e174816ae60cba3942cad38daa0fe5f9604c184 | Python | 626 | 15 | from plot_statistics import StatsPlotter
main_path = 'Path/To/Your/Data/' # Update this to your actual data path. Needs to lead to the folder containing the statistical data.
# create list of participants to be processed
# also works for subsample of participants
participants = [f'P{str(p).zfill(2)}' for p in range... |
c9ef29c298e89691bf9142921530bc66845d8f7cdef2ab495ef0d46798296a9e | Python | 627 | 17 | from pandas import Series
import pandas._testing as tm
class TestCombine:
def test_combine_scalar(self):
# GH#21248
# Note - combine() with another Series is tested elsewhere because
# it is used when testing operators
ser = Series([i * 10 for i in range(5)])
result = ser.c... |
02776dc1e18749e6aedc31cdab51a8052838848508fa7e7cf6c764591a6e1c4b | Python | 629 | 27 | """Plotting functions for calcium imaging data."""
from ._main_plot import (
ANALYSIS_PRODUCTS,
MULTI_WELL_COMBO_OPTIONS_DICT,
SINGLE_WELL_COMBO_OPTIONS_DICT,
AnalysisGroup,
AnalysisProduct,
PipelineStage,
get_available_plots,
plot_multi_well_data,
plot_single_well_data,
require... |
1aeb947f224f6eca7cb2e6baed73766f9c50dcfb93b92baff0a3f7cf126348f3 | Python | 630 | 22 | from pathlib import Path
import numpy as np
from lil_aretomo.utils import read_aln
def get_specimen_shifts(aln_file: Path) -> np.ndarray:
"""Get specimen shifts from AreTomo alignments file."""
df = read_aln(aln_file)
return np.array(df[['TX', 'TY']])
def get_xyz_extrinsic_euler_angles(aln_file: Path)... |
e725197f87d19c591b6a5a5caea50da77123acb18991b2e87a4ecba827ddf452 | Python | 631 | 23 | import random
import torch
class RandomChoice(torch.nn.Module):
def __init__(self, transforms, weights):
super().__init__()
self.transforms = transforms
self.weights = weights
def forward(self, img):
t = random.choices(self.transforms, weights=self.weights, k=1)[0]
re... |
2e200fb8c3dd749f428d24adc3ccef5d0d66fc56cd23397f88cca03bce753348 | Python | 632 | 19 | """A module with the precisions of platform-specific `~numpy.number`s."""
from typing import TypeAlias
from ._nbit_base import _8Bit, _16Bit, _32Bit, _64Bit, _96Bit, _128Bit
# To-be replaced with a `npt.NBitBase` subclass by numpy's mypy plugin
_NBitByte: TypeAlias = _8Bit
_NBitShort: TypeAlias = _16Bit
_NBitIntC: T... |
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