code: def _interp_kernel_ft(norm_freqs, interp):
      
      # Numpy's sinc(x) is equal to the 'math' sinc(pi * x)
      ker_ft = np.sinc(norm_freqs)
      interp_ = str(interp).lower()
      if interp_ == 'nearest':
          pass
      elif interp_ == 'linear':
          ker_ft *= ker_ft
      else:
          raise ValueError("`interp` '{}' not understood".format(interp))
  
      ker_ft /= np.sqrt(2 * np.pi)
      return ker_ft
docs: Scaled FT of a one-dimensional interpolation kernel.
  
      For normalized frequencies ``-1/2 <= xi <= 1/2``, this
      function returns::
  
          sinc(pi * xi)**k / sqrt(2 * pi)
  
      where ``k=1`` for 'nearest' and ``k=2`` for 'linear' interpolation.
  
      Parameters
      ----------
      norm_freqs : `numpy.ndarray`
          Normalized frequencies between -1/2 and 1/2
      interp : {'nearest', 'linear'}
          Type of interpolation kernel
  
      Returns
      -------
      ker_ft : `numpy.ndarray`
          Values of the kernel FT at the given frequencies