晋太元中，武陵人捕鱼为业。缘溪行，忘路之远近。忽逢桃花林，夹岸数百步，中无杂树，芳草鲜美，落英缤纷。渔人甚异之，复前行，欲穷其林。 　　林尽水源，便得一山，山有小口，仿佛若有光。便舍船，从口入。初极狭，才通人。复行数十步，豁然开朗。土地平旷，屋舍俨然，有良田、美池、桑竹之属。阡陌交通，鸡犬相闻。其中往来种作，男女衣着，悉如外人。黄发垂髫，并怡然自乐。 　　见渔人，乃大惊，问所从来。具答之。便要还家，设酒杀鸡作食。村中闻有此人，咸来问讯。自云先世避秦时乱，率妻子邑人来此绝境，不复出焉，遂与外人间隔。问今是何世，乃不知有汉，无论魏晋。此人一一为具言所闻，皆叹惋。余人各复延至其家，皆出酒食。停数日，辞去。此中人语云：“不足为外人道也。”(间隔 一作：隔绝) 　　既出，得其船，便扶向路，处处志之。及郡下，诣太守，说如此。太守即遣人随其往，寻向所志，遂迷，不复得路。 　　南阳刘子骥，高尚士也，闻之，欣然规往。未果，寻病终。后遂无问津者。 sh-3ll

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# Licensed under the LGPL: https://www.gnu.org/licenses/old-licenses/lgpl-2.1.en.html
# For details: https://github.com/PyCQA/astroid/blob/main/LICENSE
# Copyright (c) https://github.com/PyCQA/astroid/blob/main/CONTRIBUTORS.txt

"""Astroid hooks for scipy.signal module."""
from astroid.brain.helpers import register_module_extender
from astroid.builder import parse
from astroid.manager import AstroidManager


def scipy_signal():
    return parse(
        """
    # different functions defined in scipy.signals

    def barthann(M, sym=True):
        return numpy.ndarray([0])

    def bartlett(M, sym=True):
        return numpy.ndarray([0])

    def blackman(M, sym=True):
        return numpy.ndarray([0])

    def blackmanharris(M, sym=True):
        return numpy.ndarray([0])

    def bohman(M, sym=True):
        return numpy.ndarray([0])

    def boxcar(M, sym=True):
        return numpy.ndarray([0])

    def chebwin(M, at, sym=True):
        return numpy.ndarray([0])

    def cosine(M, sym=True):
        return numpy.ndarray([0])

    def exponential(M, center=None, tau=1.0, sym=True):
        return numpy.ndarray([0])

    def flattop(M, sym=True):
        return numpy.ndarray([0])

    def gaussian(M, std, sym=True):
        return numpy.ndarray([0])

    def general_gaussian(M, p, sig, sym=True):
        return numpy.ndarray([0])

    def hamming(M, sym=True):
        return numpy.ndarray([0])

    def hann(M, sym=True):
        return numpy.ndarray([0])

    def hanning(M, sym=True):
        return numpy.ndarray([0])

    def impulse2(system, X0=None, T=None, N=None, **kwargs):
        return numpy.ndarray([0]), numpy.ndarray([0])

    def kaiser(M, beta, sym=True):
        return numpy.ndarray([0])

    def nuttall(M, sym=True):
        return numpy.ndarray([0])

    def parzen(M, sym=True):
        return numpy.ndarray([0])

    def slepian(M, width, sym=True):
        return numpy.ndarray([0])

    def step2(system, X0=None, T=None, N=None, **kwargs):
        return numpy.ndarray([0]), numpy.ndarray([0])

    def triang(M, sym=True):
        return numpy.ndarray([0])

    def tukey(M, alpha=0.5, sym=True):
        return numpy.ndarray([0])
        """
    )


register_module_extender(AstroidManager(), "scipy.signal", scipy_signal)