File: //opt/cloudlinux/venv/lib/python3.11/site-packages/astroid/brain/brain_scipy_signal.py
# 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)