text: # 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)
  