code: def filter_convolve_stack(data, filters, filter_rot=False, method='scipy'):
      r
  
      # Return the convolved data cube.
      return np.array([filter_convolve(x, filters, filter_rot=filter_rot,
                      method=method) for x in data])
docs: r"""Filter convolve
  
      This method convolves the a stack of input images with the wavelet filters
  
      Parameters
      ----------
      data : np.ndarray
          Input data, 3D array
      filters : np.ndarray
          Wavelet filters, 3D array
      filter_rot : bool, optional
          Option to rotate wavelet filters (default is 'False')
      method : str {'astropy', 'scipy'}, optional
          Convolution method (default is 'scipy')
  
      Returns
      -------
      np.ndarray convolved data
  
      Examples
      --------
      >>> from modopt.signal.wavelet import filter_convolve_stack
      >>> x = np.arange(9).reshape(3, 3).astype(float)
      >>> filter_convolve(x, x)
      array([[[   4.,    1.,    4.],
              [  13.,   10.,   13.],
              [  22.,   19.,   22.]],
  
             [[  13.,   10.,   13.],
              [  49.,   46.,   49.],
              [  85.,   82.,   85.]],
  
             [[  22.,   19.,   22.],
              [  85.,   82.,   85.],
              [ 148.,  145.,  148.]]])