code: def _smooth_acf(acf, windowfwhm=7, windowsize=21):
      '''This returns a smoothed version of the ACF.
  
      Convolves the ACF with a Gaussian of given `windowsize` and `windowfwhm`.
  
      Parameters
      ----------
  
      acf : np.array
          The auto-correlation function array to smooth.
  
      windowfwhm : int
          The smoothing window Gaussian kernel's FWHM .
  
      windowsize : int
          The number of input points to apply the smoothing over.
  
      Returns
      -------
  
      np.array
          Smoothed version of the input ACF array.
  
      '''
  
      convkernel = Gaussian1DKernel(windowfwhm, x_size=windowsize)
      smoothed = convolve(acf, convkernel, boundary='extend')
  
      return smoothef _smooth_acf(acf, windowfwhm=7, windowsize=21):
      '''This returns a smoothed version of the ACF.
  
      Convolves the ACF with a Gaussian of given `windowsize` and `windowfwhm`.
  
      Parameters
      ----------
  
      acf : np.array
          The auto-correlation function array to smooth.
  
      windowfwhm : int
          The smoothing window Gaussian kernel's FWHM .
  
      windowsize : int
          The number of input points to apply the smoothing over.
  
      Returns
      -------
  
      np.array
          Smoothed version of the input ACF array.
  
      '''
  
      convkernel = Gaussian1DKernel(windowfwhm, x_size=windowsize)
      smoothed = convolve(acf, convkernel, boundary='extend')
  
      return smoothed
docs: This returns a smoothed version of the ACF.
  
      Convolves the ACF with a Gaussian of given `windowsize` and `windowfwhm`.
  
      Parameters
      ----------
  
      acf : np.array
          The auto-correlation function array to smooth.
  
      windowfwhm : int
          The smoothing window Gaussian kernel's FWHM .
  
      windowsize : int
          The number of input points to apply the smoothing over.
  
      Returns
      -------
  
      np.array
          Smoothed version of the input ACF array.