sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
2ea72ed35c28694eed05a93a045cbd8a0424802ebfbc6c8caa87bdad8399645a | Python | 632 | 21 | """Tools for visualizing data on brain and scalp surface representations."""
from .brain_and_scalp import plot_brain_in_axes, plot_brain_and_scalp
from .image_recon import image_recon, image_recon_multi_view, image_recon_view
from .montage import plot_montage3D
from .optode_selector import OptodeSelector
from .scalp_p... |
4ee61f051f889f978da011eb64d40c5007d7db5bb210b86a9e1768dcdd99141d | Python | 632 | 23 | #!/usr/bin/env python3.7
"""Defines the Saveable class.
The copyrights of this software are owned by Duke University.
Please refer to the LICENSE and README.md files for licensing instructions.
The source code can be found on the following GitHub repository: https://github.com/wmglab-duke/ascent
"""
import pickle
... |
b9e7d462791cf8e11a32d0e7cdc517f5cd44d09a23b7ed6946e3c9eafe9471bb | Python | 633 | 45 | """
Created on Jun 5, 2024
Not standard 10-20 EEG Montage. Duke just called it this.
@author: mning
"""
import logging
logger = logging.getLogger("root")
def get1020() -> list:
chns_10_20 = [
"Fp1",
"Fp2",
"F7",
"F3",
"Fz",
"F4",
"F8",
"FC5",
... |
940f343403a4bb4cf6f8be54f25ee7bdd6a1140070ec2d5b2788da63c18f96f8 | Python | 634 | 13 | def debug_vscode():
"""
Since this requires listening on a local port, this will only work when VSCode is connected to the same machine.
Before running, add the following to your launch.json:
{"version":"0.2.0","configurations":[{"name":"Python: Remote Attach","type":"python","request":"attach","con... |
b5ff5c14a869b869b053e08830b148da8859df7f7be8381a1fcf172146618858 | Python | 634 | 28 | from __future__ import annotations
from ..utils._typed_cache import typed_cache
from ..counts._count_sentences import count_sentences
from ..counts._count_words import count_words
@typed_cache
def sentences_per_word(text: str) -> float:
"""Get the number of sentences per word.
A combination of the functions... |
d7452ba25835683006d041d87dcbce6f33a0a915740118761a10e4944838bd2d | Python | 634 | 17 | # XXX: Handle setuptools ?
from distutils.core import Distribution
# This class is used because we add new files (sconscripts, and so on) with the
# scons command
class NumpyDistribution(Distribution):
def __init__(self, attrs = None):
# A list of (sconscripts, pre_hook, post_hook, src, parent_names)
... |
e57148afb1d5d4389ca21826d1926efba6ab827d907743b0112d9b0714300a3d | Python | 635 | 30 | """
Functions for defining unary operations.
"""
from __future__ import annotations
from typing import (
TYPE_CHECKING,
Any,
)
from pandas.core.dtypes.generic import ABCExtensionArray
if TYPE_CHECKING:
from pandas._typing import ArrayLike
def should_extension_dispatch(left: ArrayLike, right: Any) -> bo... |
05aff6d7b9a4f513d0cf495d334e93c1e7d5694584d2ce13480883c25f26b4a7 | Python | 637 | 28 | from __future__ import annotations
from ..utils._typed_cache import typed_cache
from ..counts._count_syllables import count_syllables
from ..counts._count_words import count_words
@typed_cache
def syllables_per_word(text: str, lang: str) -> float:
"""Get the average number of syllables per word.
Parameters
... |
2f77c48c04cfb00cb76baceb75025a5d7690ec5bd1d8b39e88f24c8c6364c0a4 | Python | 637 | 18 | from pandas import Index
import pandas._testing as tm
from pandas.core.construction import extract_array
def test_extract_array_rangeindex():
ri = Index(range(5))
expected = ri._values
res = extract_array(ri, extract_numpy=True, extract_range=True)
tm.assert_numpy_array_equal(res, expected)
res =... |
7e038a3f4cd2021c438bc6018d3a858430287d8474a7c06dd5e41414dbe70a42 | Python | 637 | 34 | project = "Textstat"
master_doc = 'index'
extensions = ['releases']
releases_github_path = 'textstat/textstat'
releases_unstable_prehistory = True
html_theme = 'alabaster'
templates_path = [
'_templates',
]
html_sidebars = {
'**': [
'about.html',
'navigation.html',
'relations.html'... |
64d4e9c12cd12efc4c33c0233703d152e61abe066c445e621a5fc4349b187453 | Python | 638 | 16 | import os
import sys
sys.path.append('/ImagePTE1/ajoshi/code_farm/bfp/src/stats')
from surfproc import view_patch_vtk, smooth_patch
from dfsio import readdfs,writedfs
bfp_path='/ImagePTE1/ajoshi/code_farm/bfp'
lsurf=''
smooth_iter=1000
lsurf = readdfs(os.path.join(bfp_path, 'supp_data/bci32kleft.dfs'))
lsurf = smooth_p... |
965f302782ae99ecf72033eb3ccfea17314138b7db2d5e7ca609410cb32c9988 | Python | 638 | 24 | import muon as mu
import scanpy as sc
mdata = mu.MuData(
{
'rna': sc.read_h5ad(snakemake.input.merged_rna_anndata), # type: ignore
'atac': sc.read_h5ad(snakemake.input.merged_atac_anndata) # type: ignore
}
)
mu.pp.neighbors(mdata, key_added='wnn', metric='cosine', low_memory=True)
mu.tl.um... |
d6753c06cd65858bd7e4f83c0177a06404647d19d40a5d84dd4d85c679f5755b | Python | 638 | 26 | from __future__ import annotations
import pytest
from textstat.backend import counts
from .. import resources
@pytest.mark.parametrize(
"text,expected",
[
("", 0),
("a", 1),
("a ", 1),
("a b", 2),
("They're here, and they're there.", 24),
(
"""Who's... |
dfb798c0c36a30bc1a9c85bdfbade1ae891a7274b3d8afeab4f52591da6c4e3a | Python | 640 | 47 | import numpy as np
nd1 = np.array([[1, 2], [3, 4]])
# reshape
nd1.reshape(4)
nd1.reshape(2, 2)
nd1.reshape((2, 2))
nd1.reshape((2, 2), order="C")
nd1.reshape(4, order="C")
# resize
nd1.resize()
nd1.resize(4)
nd1.resize(2, 2)
nd1.resize((2, 2))
nd1.resize((2, 2), refcheck=True)
nd1.resize(4, refcheck=True)
nd2 = n... |
ef6f0cdc4be69cf6d55d2ec4c5796fda432ee9bef012ca0fbad11f97eb9593f2 | Python | 640 | 27 | from ..structs import RequirementInformation
from .abstract import AbstractResolver, Result
from .criterion import Criterion
from .exceptions import (
InconsistentCandidate,
RequirementsConflicted,
ResolutionError,
ResolutionImpossible,
ResolutionTooDeep,
ResolverException,
)
from .resolution im... |
f69fd2466b718f6cdcd5da18f487b7772cb92735b2fad090585a1a8dc0095263 | Python | 640 | 20 | """Test deprecation and future warnings.
"""
import numpy as np
from numpy.testing import assert_warns
def test_qr_mode_full_future_warning():
"""Check mode='full' FutureWarning.
In numpy 1.8 the mode options 'full' and 'economic' in linalg.qr were
deprecated. The release date will probably be sometime ... |
046685fb6bef1d1a62a7a61dee34778ef02735154a3bb91b67dfae74ab5e339d | Python | 641 | 24 | import inharmonicon
import numpy as np
import antropy
jitters = np.geomspace(0.005, .5, 10)[:7]
f0 = 440
f_max = 20000
n_runs=100
entropies = np.zeros((n_runs,7))
for i in range(n_runs):
sounds = []
for jitter in jitters:
this_series = inharmonicon.Harmonics(f0=f0, fmax=20000, jitter_rate=jitter)
... |
54fb32d122ea6ca6941a00ea7ac6179a362e2e99cf2be5f2cec7aa995e509e13 | Python | 641 | 20 | import pytest
import numpy as np
from . import util
@pytest.mark.slow
class TestCommonBlock(util.F2PyTest):
sources = [util.getpath("tests", "src", "common", "block.f")]
def test_common_block(self):
self.module.initcb()
assert self.module.block.long_bn == np.array(1.0, dtype=np.float64)
... |
5012837e745e2506b54eb13719809db4cf92068e48ddec9e9a5c217f7e4d9dd0 | Python | 642 | 22 | import csv
import os
def write_csv(foldername, sess, prot, fname, liste):
"""
Define the output pathway and create the corresponding csv files
"""
path_output = os.path.join(foldername, sess, prot, fname)
with open(path_output, 'w') as fp:
a = csv.writer(fp, delimiter=',')
a.writer... |
9a3f8e81fe53adb1a6f7845db06f0a23941d6186de69b60e38ff0ccd66eec812 | Python | 642 | 20 | from __future__ import annotations
from typing import TYPE_CHECKING
from micromanager_gui._widgets._stage_control import StagesControlWidget
if TYPE_CHECKING:
from pymmcore_plus import CMMCorePlus
from pytestqt.qtbot import QtBot
def test_stage_widget(qtbot: QtBot, global_mmcore: CMMCorePlus, _run_after_ea... |
a691a354bbc178df21c2b556e24bd5f62bd573c9a6728b0c52fd28ece26cd0d1 | Python | 642 | 18 | import setuptools
with open("README.md", "r") as fh:
long_description = fh.read()
setuptools.setup(
name = "scrublet",
packages = ['scrublet'],
package_dir={'': 'src'},
version = '0.2.2',
description = 'Doublet prediction in single-cell RNA-sequencing data',
long_description=long_descripti... |
e693f729ce5de1027f734285b31adfca18e23d57bb275ccea9215b140cdc57e6 | Python | 642 | 34 | class ConsoleError(Exception):
"""An error in console operation."""
class StyleError(Exception):
"""An error in styles."""
class StyleSyntaxError(ConsoleError):
"""Style was badly formatted."""
class MissingStyle(StyleError):
"""No such style."""
class StyleStackError(ConsoleError):
"""Style... |
0f474534acb0592fc6d71b2647a306172215b1e093663013b3df5f2f67b97e54 | Python | 643 | 23 | #replace this code with code to read inputs from file, normalize, and sort into lists
import tensorflow as tf
import numpy as np
# import pulse2percept as p2p
import random
def parse_inputs(inputsfile):
inputlist = []
infile = open(inputsfile, "r")
data = infile.readlines()
infile.close()
for line ... |
54bfb151fe670f9d9a611a3ad2a9970cb30eb4d8c25d22ef76950116ecb3bf57 | Python | 643 | 25 | from protgps.utils.registry import register_object
import pytorch_lightning as pl
import os
from protgps.utils.classes import ProtGPS
@register_object("tensorboard", "logger")
class PLTensorBoardLogger(pl.loggers.TensorBoardLogger, ProtGPS):
def __init__(self, args) -> None:
super().__init__(args.logger_d... |
1462649ed30facdf229b0be7087561995b2b38bbb043bc6030857c80ca7a7bd0 | Python | 645 | 32 | from abc import ABC, abstractmethod
import numpy as np
class CameraSource(ABC):
@abstractmethod
def get_width(self) -> int:
raise NotImplementedError
@abstractmethod
def get_height(self) -> int:
raise NotImplementedError
@abstractmethod
def get_fps(self) -> float:
ra... |
5ea4a05caf80824e59b68dc7740661994779ce5dbe20c8b9e2293a217ede775a | Python | 645 | 28 | import numpy as np
import circe as ci
import scanpy as sc
import scipy as sp
adata = sc.read_h5ad(snakemake.input.celltype_atac)
adata.var['start'] = adata.var['start'].astype(int)
adata.var['end'] = adata.var['end'].astype(int)
adata.var['chr'] = adata.var['chromosome']
adata = ci.metacells.compute_metacells(
ad... |
28bd716a2a79afb9d8fb7a0b5b5e9b9a881f918963b062442462b19fac3bd85a | Python | 646 | 28 | import pytest
from pandas.compat import PY311
from pandas import (
offsets,
period_range,
)
import pandas._testing as tm
class TestFreq:
def test_freq_setter_deprecated(self):
# GH#20678
idx = period_range("2018Q1", periods=4, freq="Q")
# no warning for getter
with tm.as... |
2e08b745110b5557a872af61125cd2bb8cf1e1cd479b02b3da201ff072454543 | Python | 646 | 29 | from __future__ import annotations
from ..utils._typed_cache import typed_cache
from ._sentences_per_word import sentences_per_word
from ._chars_per_word import chars_per_word
@typed_cache
def gulpease_index(text: str) -> float:
"""Calculate Indice Gulpease Index for Italian texts
https://it.wikipedia.org/wi... |
8d364d8feaff9f498bd27dc7cb3511ac9b139cc55b4110f55f1a696bbec3cedb | Python | 647 | 23 | import os
from os import PathLike
from pathlib import Path
from typing import List, Sequence
def basename(path: os.PathLike) -> str:
while Path(path).stem != str(path):
path = Path(path).stem
return str(path)
def write_empty_file(filename: os.PathLike) -> None:
open(filename, mode='w').close()
... |
01f17dd02edbef8f69345844d7574be9b1619f35da95e0ce52b0d3e6708c9434 | Python | 648 | 29 |
from .layer import Layer
from .titlecluster import TitleCluster
class TitleLayer(Layer):
'''
classdocs
'''
def __init__(self, neutype='LIF'):
'''
Constructor
'''
self.neutype = neutype
self.groups = {}
def setTestStates(self):
for id, g in self.g... |
f0bc3390275870f2177bf6fe7b874c273ebe4b2f145e491e0caedb31af669ba8 | Python | 648 | 24 | import numpy as np
import logging
import yass
from yass import preprocess
from yass import detect
from yass import cluster
np.random.seed(0)
# configure logging module to get useful information
logging.basicConfig(level=logging.INFO)
# set yass configuration parameters
yass.set_config('config_sample.yaml', 'preproc... |
7e13b6ed185df91f084092a7b8fbcc20c82db3394a12a935812772101b6f2cbd | Python | 649 | 21 | import numpy as np
def construct_balanced_subset(x, y):
xdata, ydata = [], []
minsize = np.inf
for cls_ in np.unique(y):
xdata.append(x[y == cls_])
ydata.append(y[y == cls_])
if ydata[-1].shape[0] < minsize:
minsize = ydata[-1].shape[0]
for i in range(len(xdata)):
... |
bb9fe52cf7e8314ea2fab9eae64b5b57b94b5daa5364b5fb1475dc6722528cd5 | Python | 649 | 17 | ## ...........................................................................
##
## PIMMS (Polymer Interactions in Multicomponent Mixtures)
## Alex Holehouse, Pappu Lab, Holehouse Lab
## Copyright 2015 - 2026
## ...........................................................................
from . import mega_crank
#... |
f6ad72e7a377f37e49007d66d1c7063502350000e28e4eded3a94b3ff76187e6 | Python | 651 | 19 | # -*- coding: utf-8 -*-
import numpy as np
def calc_score(probe_type_list, pt_fdbk_list, key_present, key_absent):
"""
Calculate the final score of the participant based on the number of
correct answers.
"""
probe_type = np.array(probe_type_list)
pt_fdbk = np.array(pt_fdbk_list)
correct_a... |
f0d28e52c13c5ad87e5a6238265bdf100b110f1be1cad944ce88c00654e57542 | Python | 652 | 30 | import torch
import numpy as np
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
def unit(x):
if len(x.shape)>0:
maxx=np.max(x)
minx=np.min(x)
marge=maxx-minx
if marge!=0:
xx=(x-minx)/marge
xx=np.clip(xx, 0,1)
else:
xx... |
8090d05c99306423f55c750cdd54d9f3ab031ee8927870219482e457725785d5 | Python | 653 | 27 | """Tests for fooof.plts.fm."""
from py.test import raises
from fooof import FOOOF
from fooof.plts.fm import *
from fooof.tests.utils import plot_test
###################################################################################################
###################################################################... |
85eff0e2a410552d99d66b391824e9b434d734e5c15f0d27f334ae582a7c9fa6 | Python | 653 | 26 | from __future__ import annotations
import typing as t
from .extension import SQLAlchemy
__all__ = [
"SQLAlchemy",
]
def __getattr__(name: str) -> t.Any:
if name == "__version__":
import importlib.metadata
import warnings
warnings.warn(
"The '__version__' attribute is de... |
a924783d4b801c43ead68f0d51e89ffcc4ab378debbd279642db264cae88d5ae | Python | 653 | 30 | import pytest
from pandas import (
Period,
PeriodIndex,
Series,
period_range,
)
import pandas._testing as tm
pytestmark = pytest.mark.filterwarnings(
"ignore:Setting a value on a view:FutureWarning"
)
@pytest.mark.parametrize(
"cons",
[
lambda x: PeriodIndex(x),
lambda x:... |
529e5edc2025a33fe64ebccbba01f08597de386ef6177eee7267a0ff1f852548 | Python | 654 | 23 | """Helper script to download datasets.
This script retrieves datasets used in example notebooks so that notebooks can be
rendered in parallel.
"""
import cedalion.data as data
data.get_fingertapping()
data.get_fingertappingDOT()
data.get_colin27_headmodel_files()
data.get_icbm152_headmodel_files()
data.get_ninja_ca... |
915dfd52030cbd4082c4a4f8543b073a6d8a19919344b5fe9f66f7d86f948502 | Python | 654 | 26 | 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_polysyllable_words(text: str, lang: str) -> int:
"""Count the words with three or more syllables. Contractions and h... |
54e7a4375874f8bddc974feb0aee5c809ba9ac7782c43997c2983178f697c2b8 | Python | 656 | 22 | import os
import seaborn as sns
from nilearn.plotting import view_img_on_surf
from nilearn import image
sns.set_theme()
sns.set_style("whitegrid")
sns.set_context("talk")
### plot fmri image for methods
cache = DATA_ROOT = "/storage/store/work/haggarwa/"
DATA_ROOT2 = "/storage/store2/work/haggarwa/"
output_dir = os.p... |
6d3c82cfd118dcd55c7056f8ef6c3b82a331ae689d06cc4766396c7cc6b03ec9 | Python | 657 | 21 | __all__ = [
'LFC', #'ATE', 'SATE', 'FC',
'fit_glm', 'reset_random_seeds', 'fit_gcate'
]
from causarray.DR_learner import LFC # ATE, SATE, FC
from causarray.gcate_glm import fit_glm
from causarray.utils import prep_causarray_data, reset_random_seeds, comp_size_factor
from causarray.gcate import *
from ca... |
d28fdb89523ec0b87b91cc3d147bdbc18cb336f3343c8d3a4110f6661883d85b | Python | 658 | 29 | """
Helpers for sharing tests between DataFrame/Series
"""
from __future__ import annotations
from typing import TYPE_CHECKING
from pandas import DataFrame
if TYPE_CHECKING:
from pandas._typing import DtypeObj
def get_dtype(obj) -> DtypeObj:
if isinstance(obj, DataFrame):
# Note: we are assuming on... |
3b8d61c1518bc85b4886ffb36ded890598aa0f785e180ecb3a4d7446ec5f70a7 | Python | 659 | 25 | def get_groupby_method_args(name, obj):
"""
Get required arguments for a groupby method.
When parametrizing a test over groupby methods (e.g. "sum", "mean", "fillna"),
it is often the case that arguments are required for certain methods.
Parameters
----------
name: str
Name of the ... |
670e8a487f08387d285c597a2391931fe58f1ff456ddc1f1ea75566d2a24e6ec | Python | 659 | 16 | import pandas as pd
# Read the files
cluster_df = pd.read_csv('CT2_log/euclidean/final_candidate/cluster.csv')
distances_df = pd.read_csv('CT2_log/euclidean/high_variation_genes/deletion_distance.csv')
# Merge the dataframes
merged_df = pd.merge(cluster_df, distances_df,
left_on='Gene Name', righ... |
e134df8ec98fb03c815091be24d38c8e1c193c39bafedf19ccf34e59ae93477f | Python | 660 | 23 | from .lifneuron import LIFNeuron
class GenreLIFNeuron(LIFNeuron):
'''
classdocs
'''
def __init__(self, tau_ref=0, vthresh=5, Rm=2, Cm=0.2):
'''
Constructor
'''
LIFNeuron.__init__(self, tau_ref, vthresh, Rm, Cm)
def update(self, dt, t):
self.spike = False
... |
208447a4eb099494a0923ab5528781a0c4ea86f369de037d17231be4a7fc125e | Python | 661 | 26 | # This file is dual licensed under the terms of the Apache License, Version
# 2.0, and the BSD License. See the LICENSE file in the root of this repository
# for complete details.
__all__ = [
"__title__",
"__summary__",
"__uri__",
"__version__",
"__author__",
"__email__",
"__license__",
... |
2f57c60eccb676666a7ffcb76d7568f6650caf526c962f4175270284e110927b | Python | 661 | 30 | import pytest
from pandas import (
Series,
Timedelta,
TimedeltaIndex,
timedelta_range,
)
import pandas._testing as tm
pytestmark = pytest.mark.filterwarnings(
"ignore:Setting a value on a view:FutureWarning"
)
@pytest.mark.parametrize(
"cons",
[
lambda x: TimedeltaIndex(x),
... |
374d3f8a0536e7f1e362ebc0a8340aa81a6a6f3e878c1f7ba3d131bdba3d0733 | Python | 662 | 27 | import pytest
from pandas import DataFrame
import pandas._testing as tm
class TestGet:
def test_get(self, float_frame):
b = float_frame.get("B")
tm.assert_series_equal(b, float_frame["B"])
assert float_frame.get("foo") is None
tm.assert_series_equal(
float_frame.get("... |
7550de992a50779226414c9dc849f1de91616db47dd46f3a4040289fa8e41430 | Python | 663 | 17 | from DPOAE_analysis import ExperimentEvaluator
main_path = '/Path/To/Your/Data/' # Update this to your actual data path
# create list of participants to be processed
# also works for subsample of participants
subjects = [f'P{str(p).zfill(2)}' for p in range(1, 41)]
exclude = ['P13', 'P20']
subjects = [subject for su... |
eda8d96d8657f626cb17e9cd40dc5418da320ed81dd62cbd7848eb70a6d98d1d | Python | 663 | 18 | # -*- 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... |
01d8b9291959c439327bc29b398250511708e2b0bbc3a1f4113761b6d443ca29 | Python | 665 | 28 | import pytest
import pandas
import sbmlcore
def test_tempfactors():
a = sbmlcore.TempFactors('tests/3pl1.pdb')
assert len(a.results) == 185
# check that all the -180 < phi <= 180 (and also for psi)
assert all(a.results.temp_factor >= 0)
assert float(a.results[a.results.resid==1].temp_factor)... |
065b2f6c7cb1e80518b6e645cd5ef2da5514ec9f897d32bac3942f762ac0a984 | Python | 666 | 19 | ## ...........................................................................
##
## PIMMS (Polymer Interactions in Multicomponent Mixtures)
## Alex Holehouse, Pappu Lab, Holehouse Lab
## Copyright 2015 - 2026
## ...........................................................................
from . import mega_crank
#... |
75708fb4b8867d0f41da983fb3f60aedfbd6c145be09b54e3d8527f69685a2c9 | Python | 666 | 24 | """
Tests for Timestamp timezone-related methods
"""
from datetime import datetime
from pandas._libs.tslibs import timezones
from pandas import Timestamp
class TestTimestampTZOperations:
# ------------------------------------------------------------------
def test_timestamp_timetz_equivalent_with_datetime_... |
9f9df45a13c274cf5280b0305a7589f49d6f61f616deff460f2d9a37cd5dd39f | Python | 666 | 24 | from .lifneuron import LIFNeuron
class ComposerLIFNeuron(LIFNeuron):
'''
classdocs
'''
def __init__(self, tau_ref=0, vthresh=5, Rm=2, Cm=0.2):
'''
Constructor
'''
LIFNeuron.__init__(self, tau_ref, vthresh, Rm, Cm)
def update(self, dt, t):
self.spike = Fals... |
adf2a0cb7d5405c52102f3fd9a8ce5493dc4fd1e4af32fc310fe875ea6e913a4 | Python | 667 | 29 | from __future__ import annotations
from ..utils._typed_cache import typed_cache
from ..counts._count_letters import count_letters
from ..counts._count_words import count_words
@typed_cache
def letters_per_word(text: str) -> float:
"""Calculate the average word length in letters.
This function is a combinati... |
1e06453d3d3686e8093bbba14938f079b70a39ddf82647186368123ed3b27668 | Python | 668 | 25 | """
config for datetime formatting
"""
from __future__ import annotations
from pandas._config import config as cf
pc_date_dayfirst_doc = """
: boolean
When True, prints and parses dates with the day first, eg 20/01/2005
"""
pc_date_yearfirst_doc = """
: boolean
When True, prints and parses dates with the yea... |
6991ad516a67e02a054c3d114cc5627de994c05bdd663bf9eebbd862f3d61dbc | Python | 669 | 30 | from __future__ import annotations
from ..utils._typed_cache import typed_cache
from ._letters_per_word import letters_per_word
from ._words_per_sentence import words_per_sentence
@typed_cache
def gutierrez_polini(text: str) -> float:
"""Calculate Guttierrez de Polini index
https://legible.es/blog/comprensi... |
6321547bfb34c509d85a0ca43ebb4da21f37555fed0305421fb69332554ad184 | Python | 670 | 22 | 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", 113.418),
(resources.SHORT_TEXT, "en_US", 117.74),
... |
6815343635486134103c1e29c21008b8252c6b96c6dfcb9b9f80554c08c10550 | Python | 670 | 23 | from typing import Union
from ase import Atoms
from ase.calculators.calculator import Calculator, compare_atoms
from AIMD.protein import Protein
def check_state(self: Calculator, atoms: Union[Atoms, Protein], tol=1e-15):
r"""
Check for any system changes since last calculation.
- Skips the check and ass... |
d4ac9ea5d284e35670452f89cdc2b38ce7dc5cda3b2a78e30960c5e084ed01c9 | Python | 670 | 26 | import numpy as np
from rulebasedpolicy.point import *
class RandomMap:
def __init__(self, size, board):
self.size = size
self.board = board
self.obstacle = size//8
self.GenerateObstacle()
def GenerateObstacle(self):
self.obstacle_point = []
# Generate an obsta... |
5453e8e701aef94bed00e171de1a3120b991748f644cec4220824ce1faa04419 | Python | 671 | 33 | import pytest
import pandas as pd
from pandas.tests.extension.list.array import (
ListArray,
ListDtype,
make_data,
)
@pytest.fixture
def dtype():
return ListDtype()
@pytest.fixture
def data():
"""Length-100 ListArray for semantics test."""
data = make_data()
while len(data[0]) == len(d... |
8de920013ad3369d68be34ab9520f1934caf66e7e2d20c5249b048a99629581f | Python | 671 | 17 | import numpy as np
import torch
def assert_shapes_hamiltonian(batch):
assert batch.forces.shape == batch.pos.shape
assert isinstance(batch.hamiltonian, list)
assert isinstance(batch.overlap, list)
assert isinstance(batch.core, list)
for H, S, C in zip(batch.hamiltonian, batch.overlap, batch.core):... |
fe1131a738ed1f3daf2f31df5a5f00c5f5a1c29a3da661e32bf67f13c9f6c280 | Python | 671 | 25 | """Contains enums for partial task detection"""
from enum import Enum
class TASK(Enum):
SAVE_GBKS = 0
HMM_SCAN = 1
HMM_ALIGN = 2
COMPARISON = 3
class INPUT_TASK(Enum):
NO_DATA = 0 # nothing done yet
NEW_DATA = 1 # new data incoming, all data in database accounted for
PARTIAL_DATA = 2 ... |
ea2fa97599dc56188244bfc284acab4cb3619f5e1a0dbb18c36e37f8f7c09c94 | Python | 673 | 27 | __all__ = [
"NaT",
"NaTType",
"OutOfBoundsDatetime",
"Period",
"Timedelta",
"Timestamp",
"iNaT",
"Interval",
]
# Below imports needs to happen first to ensure pandas top level
# module gets monkeypatched with the pandas_datetime_CAPI
# see pandas_datetime_exec in pd_datetime.c
import p... |
045da7e4e790cf5416db149ecb62f17cd0adc1b8e74da7577481f6b68a8979c8 | Python | 677 | 29 | # SPDX-FileCopyrightText: 2015 Eric Larson
#
# SPDX-License-Identifier: Apache-2.0
"""CacheControl import Interface.
Make it easy to import from cachecontrol without long namespaces.
"""
__author__ = "Eric Larson"
__email__ = "eric@ionrock.org"
__version__ = "0.14.3"
from pip._vendor.cachecontrol.adapter import Cac... |
150845476227a70240dc57d74c32c0762bdfe93337327939d818b497c110431e | Python | 677 | 29 | import pytest
import pandas
import sbmlcore
def test_rasp():
a = sbmlcore.RaSP('tests/cavity_pred_3PL1_A.csv')
assert len(a.results) == 185*20
assert all((a.results.rasp_score_ml_fermi >= 0) & (a.results.rasp_score_ml_fermi <= 1))
assert all(a.results.rasp_score_ml >= -2)
# these should... |
304a1dadfda53f07595fbb2db6425b6a7ad47b169ee5321a55301c153993c3e9 | Python | 677 | 25 | from .hamiltonian_dataset import ( # database interface for Hamiltonian datasets
HamiltonianDatabase,
HamiltonianDataset,
)
from .nablaDFT_dataset import ( # PyTorch Lightning interfaces for datasets
ASENablaDFT,
PyGHamiltonianDataModule,
PyGNablaDFTDataModule,
)
from .pyg_datasets import ( # PyT... |
26d760d8c37cb4b02a7f16dbe30313589b2b0a8d0d2167ba95c3242e76544c43 | Python | 678 | 22 | import torch
from .rk_common import _ButcherTableau, RKAdaptiveStepsizeODESolver
_FEHLBERG2_TABLEAU = _ButcherTableau(
alpha=torch.tensor([1 / 2, 1.0], dtype=torch.float64),
beta=[
torch.tensor([1 / 2], dtype=torch.float64),
torch.tensor([1 / 256, 255 / 256], dtype=torch.float64),
]... |
03e19b08795b0df54f181d7474d1a71a0e03b6b2ab9516d1b2961fb834d498f3 | Python | 679 | 22 | import pytest
from pandas import (
DataFrame,
MultiIndex,
)
class TestGetValue:
def test_get_set_value_no_partial_indexing(self):
# partial w/ MultiIndex raise exception
index = MultiIndex.from_tuples([(0, 1), (0, 2), (1, 1), (1, 2)])
df = DataFrame(index=index, columns=range(4))
... |
923c01e75b490894b13dc401e7fa9d032610e1caa41f1d5f9b9b67ff03d20add | Python | 679 | 20 | # 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.
# for test files, silence irrelevant and noisy pylint warnings
# pylint: disable=no-self-use,protected-access,missing-docstring
import unittest
from antismash.detection.... |
b6760ff84327a8f98abfe4790812c7265562681a7fdd3248de3e3ef8d7e002d1 | Python | 679 | 23 | import os
import sys
import inspect
from pettingzoo import test
from smac.env.pettingzoo import StarCraft2PZEnv as sc2
import pickle
current_dir = os.path.dirname(
os.path.abspath(inspect.getfile(inspect.currentframe()))
)
parent_dir = os.path.dirname(current_dir)
sys.path.insert(0, parent_dir)
if __name__ == "_... |
b92cfada4a1ec6723c59ab7304d9fff4414e4bf83f98956d3f546142adb324fb | Python | 679 | 27 | from typing import List
import torch
def accuracy(output: torch.Tensor, target: torch.Tensor, top_k=(1,)) -> List[float]:
"""Computes the precision@k for the specified values of k"""
max_k = max(top_k)
batch_size = target.size(0)
_, predict = output.topk(max_k, 1, True, True)
predict = predict.t... |
424e72f83e7e39d4582a40a073e92d7312863464823ed788484b01c9715623d3 | Python | 680 | 41 | from pandas.core.reshape.concat import concat
from pandas.core.reshape.encoding import (
from_dummies,
get_dummies,
)
from pandas.core.reshape.melt import (
lreshape,
melt,
wide_to_long,
)
from pandas.core.reshape.merge import (
merge,
merge_asof,
merge_ordered,
)
from pandas.core.reshap... |
703a239af287c691d2f6e94b0a495b5ae4299742a9e92fda46124881b1abe82a | Python | 680 | 21 | '''
Primary Auditory Cortex
'''
import torch
from braincog.base.node.node import *
from braincog.base.brainarea.BrainArea import *
from braincog.base.connection import CustomLinear
from braincog.base.learningrule.STDP import *
class PAC(BrainArea):
def __int__(self,w,mask):
self.noteNetworks = NoteLIFNode... |
85d13958177a4b2f869e7223ec08a96f4b4b91ebfeaabbfafd0e29aa8290750a | Python | 680 | 30 | """Module containing code related to genbank file parsing and storage"""
from .gbk import GBK
from .region import Region
from .candidate_cluster import CandidateCluster
from .proto_cluster import ProtoCluster, MergedProtoCluster
from .proto_core import ProtoCore, MergedProtoCore
from .cds import (
CDS,
check_tr... |
95950b86d33ad0f598259242479cd50457e99cf6e45e738f319c59e4b39e503a | Python | 680 | 21 | import iaode
def test_package_metadata() -> None:
assert isinstance(iaode.__version__, str)
assert iaode.__version__.startswith("0."), "Expected release-style version"
assert "agent" in iaode.__all__
def test_get_data_dir_idempotent() -> None:
cache_dir = iaode.datasets.get_data_dir()
assert cac... |
c0288df75f9e2f13915e546aba20f4f9e77fd27f1e19a51e0f5f3564e7c4b789 | Python | 680 | 15 | from enum import Enum
class Phase(Enum):
"""
Enumerates the distinct phases in the AmygdalaEngrams model:
- PERCEPTION: Network processes sensory input and updates synaptic weights.
- REFLECTION: (This constant exists for historical reasons -- Fiebig & Lansner (2014) postulated a replay of patterns in... |
5eabc67806fd96b5cfd557702923af6c3bb2b6a0ee2795520ec2ca4006b98089 | Python | 682 | 19 | import pytest
import pandas._testing as tm
class TestCategoricalWarnings:
def test_tab_complete_warning(self, ip):
# https://github.com/pandas-dev/pandas/issues/16409
pytest.importorskip("IPython", minversion="6.0.0")
from IPython.core.completer import provisionalcompleter
code =... |
3bbb66ce9bc84f4baff47e4afb231329cc19a6697d704681e422d53225244429 | Python | 685 | 33 | """
Public API for extending pandas objects.
"""
from pandas._libs.lib import no_default
from pandas.core.dtypes.base import (
ExtensionDtype,
register_extension_dtype,
)
from pandas.core.accessor import (
register_dataframe_accessor,
register_index_accessor,
register_series_accessor,
)
from pand... |
be67b3b8a3112b73ddae7a6799412bcee0408e129de73cde9630df060e5cae8d | Python | 685 | 29 | from __future__ import annotations
from ..utils._typed_cache import typed_cache
from ..counts._count_words import count_words
from ..counts._count_sentences import count_sentences
@typed_cache
def words_per_sentence(text: str) -> float:
"""Calculate the average number of words per sentence.
This function is... |
719a6dcf357d12b73eb246b78825d65b4ea5500c754f92818100a3a5827f73c9 | Python | 687 | 22 | from .layer import Layer
from .genrecluster import GenreCluster
class GenreLayer(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 setTestState... |
c32e816398274bf7995cf83aab9bebb3b40ddaac7d162cebfa0672c31d259a6d | Python | 687 | 20 | import tensorflow as tf
import tensorflow_probability as tfp
#from https://github.com/kundajelab/basepair/blob/cda0875571066343cdf90aed031f7c51714d991a/basepair/losses.py#L87
def multinomial_nll(true_counts, logits):
"""Compute the multinomial negative log-likelihood
Args:
true_counts: observed count va... |
7ee88172311b856da775a4f29e56420aa05381590e9daf29f7f7979557ec156d | Python | 688 | 17 | from typing import Optional
from qtpy.QtCore import QModelIndex
from qtpy.QtWidgets import QTableView, QWidget
class ChannelTableView(QTableView):
def __init__(self, parent: Optional[QWidget] = None) -> None:
super(ChannelTableView, self).__init__(parent)
self.horizontalHeader().setStretchLastSec... |
b0431adfca9aaa3bf1d5989ddce0805236b7d4138153e512b9230f06f537ca3a | Python | 689 | 24 | """Filetype information."""
from pip._internal.utils.misc import splitext
WHEEL_EXTENSION = ".whl"
BZ2_EXTENSIONS: tuple[str, ...] = (".tar.bz2", ".tbz")
XZ_EXTENSIONS: tuple[str, ...] = (
".tar.xz",
".txz",
".tlz",
".tar.lz",
".tar.lzma",
)
ZIP_EXTENSIONS: tuple[str, ...] = (".zip", WHEEL_EXTENSI... |
0cab8487657622424ebbe067bab5af6b1f0cab911c407b46f8afb39dc199469a | Python | 690 | 21 | """
Tests for the deprecated keyword arguments for `read_json`.
"""
from io import StringIO
import pandas as pd
import pandas._testing as tm
from pandas.io.json import read_json
def test_good_kwargs():
df = pd.DataFrame({"A": [2, 4, 6], "B": [3, 6, 9]}, index=[0, 1, 2])
with tm.assert_produces_warning(None... |
fa13adf7fa6f95d785ebd314283d392c8661e19e890bb8a8ddafa473328537d8 | Python | 690 | 20 | import time, os
import pandas as pd
os.environ["CUDA_VISIBLE_DEVICES"]="6"
start = time.time()
res = []
for epoch in [1, 10, 50, 100, 150, 300, 500]:
cmd = '/home/sxh/anaconda3/envs/chemprop/bin/python train.py --data_path DMPNN/train_dmpnn.csv --dataset_type regression --config_path DMPNN/logs_config --save_... |
040e2e7b9997e47d1684ba86fa093855231b60cf5fc3b8540f6bd6a4805770f1 | Python | 691 | 23 | """
Testing pipeline.run
"""
import yaml
from yass import pipeline
def test_works_with_nnet_config(patch_triage_network, path_to_config,
make_tmp_folder):
pipeline.run(path_to_config, output_dir=make_tmp_folder)
# def test_works_with_threshold_config(path_to_config_threshold,
# ... |
70f07f6bd2d7cf9c6fb116d7d68daac807632dab5925d43f2dce4c70d5fe5fb6 | Python | 691 | 31 | """Wrappers to call pyproject.toml-based build backend hooks.
"""
from typing import TYPE_CHECKING
from ._impl import (
BackendUnavailable,
BuildBackendHookCaller,
HookMissing,
UnsupportedOperation,
default_subprocess_runner,
quiet_subprocess_runner,
)
__version__ = "1.2.0"
__all__ = [
"B... |
71147a23e948b1e7c6f79bc465bf13b9776f9b0ee974f15e76906778b54a046f | Python | 692 | 20 | import pytest
import pandas._testing as tm
from pandas.core.arrays import TimedeltaArray
class TestAccumulator:
def test_accumulators_disallowed(self):
# GH#50297
arr = TimedeltaArray._from_sequence(["1D", "2D"], dtype="m8[ns]")
with pytest.raises(TypeError, match="cumprod not supported")... |
96c8e9527ea7c2e00cf886e5d17206fdcb1e56c14ad9f300d2ae95cfcaa4976b | Python | 692 | 22 | import numpy as np
# from https://github.com/songrotek/DDPG/blob/master/ou_noise.py
class OUNoise:
def __init__(self, action_dimension, scale=0.1, mu=0, theta=0.15, sigma=0.2):
self.action_dimension = action_dimension
self.scale = scale
self.mu = mu
self.theta = theta
self.... |
97d03bf6ee4f4dca1aef4836eb014f2d31a76ef6297bbea13e4d48bf7df881bd | Python | 692 | 26 | import numpy as np
import pytest
from pandas import (
NaT,
PeriodIndex,
period_range,
)
import pandas._testing as tm
from pandas.tseries import offsets
class TestPickle:
@pytest.mark.parametrize("freq", ["D", "M", "Y"])
def test_pickle_round_trip(self, freq):
idx = PeriodIndex(["2016-05-... |
c26524f71627636931df3d86bb0fb622027f153c13e00698b9dfbf15544ede19 | Python | 692 | 17 | # Copyright (C) 2008,2010,2013 Bernd Feige
# This file is part of avg_q and released under the GPL v3 (see avg_q/COPYING).
"""
Utility function to make a set_channelposition compatible string
from a vector of channel names
"""
import math
def channelnames2channelpos(channelnames):
nr_of_channels=len(channelnames)
nco... |
7b7679e947ec16c14c4508e38c86b7107bee79f5b972cb12926ad1e68b9a2e04 | Python | 695 | 17 | # Copyright 2021 The NetKet Authors - 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.org/licenses/LICENSE-2.0
#
# Unless required by applicable ... |
08338dd396e70835f5e07a4a6e9d69ed9764e0c534d5a520f47d856f4ea510ec | Python | 696 | 32 | from __future__ import annotations
import re
from ..utils._typed_cache import typed_cache
from ._count_words import count_words
@typed_cache
def count_sentences(text: str) -> int:
"""Count the sentences of the text.
Parameters
----------
text : str
A text string.
Returns
-------
... |
5cbe413a569111194f2d99db9cb96f1a6aeb8024de41fa721c4d77210b2be0ed | Python | 697 | 19 | import pandas as pd
# PWS region genes
pws_region_genes = ["MKRN3", "MAGEL2", "NDN", "NPAP1", "SNURF", "SNRPN", "UBE3A", "GABRB3",
"GABRA5", "GABRG3", "ATP10A", "OCA2", "HERC2", "NIPA1", "NIPA2", "CYFIP1", "TUBGCP5"]
# Read candidate genes
candidates_df = pd.read_csv('CT2_log/euclidean/final_candi... |
3324354c9196d981389afc35c2eebca126dc9b75d66a4bfffe78271824329a25 | Python | 698 | 25 | import os
import pandas as pd
import starfile
from pydantic import BaseModel
class RlnTiltSeries(BaseModel):
name: str
data: pd.DataFrame
class Config:
arbitrary_types_allowed = True
@classmethod
def from_star_file(cls, filename: os.PathLike):
star = starfile.read(filename, alwa... |
4c9791e9e4328d928f06beb269098b650e42a6d8cc145bf6a5fbd14eb86decec | Python | 698 | 32 | """Module containing code related to enums"""
from .input_parameters import INPUT_MODE
from .input_parameters import RUN_MODE
from .source_type import SOURCE_TYPE
from .partial_task import TASK, INPUT_TASK, HMM_TASK
from .comparison import (
ALIGNMENT_MODE,
EXTEND_STRATEGY,
LCS_MODE,
COMPARISON_MODE,
... |
e3699d26ab6abd7dcf94149d721d58ea3441be17b42336713a82edf81197d374 | Python | 698 | 27 | import numpy as np
import pytest
from pandas import (
Index,
MultiIndex,
)
# Note: identical the "multi" entry in the top-level "index" fixture
@pytest.fixture
def idx():
# a MultiIndex used to test the general functionality of the
# general functionality of this object
major_axis = Index(["foo",... |
83f715dda83e80d3bdb26ef86f39a6fd1b710754caaa57550b0100cfc412ff4e | Python | 700 | 25 | """module containing a test for the profiler"""
# from python
from unittest import TestCase
import psutil
import os
import time
# from this module
from big_scape.diagnostics.profiler import calc_cpu_percent
class TestProfiler(TestCase):
"""Test class for the profiler functions"""
def test_cpu_percent_withi... |
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