code: def sparse_to_unmasked_sparse_from_mask_and_pixel_centres(total_sparse_pixels, mask,
                                                            unmasked_sparse_grid_pixel_centres):
      
  
      pix_to_full_pix = np.zeros(total_sparse_pixels)
  
      pixel_index = 0
  
      for full_pixel_index in range(unmasked_sparse_grid_pixel_centres.shape[0]):
  
          y = unmasked_sparse_grid_pixel_centres[full_pixel_index, 0]
          x = unmasked_sparse_grid_pixel_centres[full_pixel_index, 1]
  
          if not mask[y, x]:
              pix_to_full_pix[pixel_index] = full_pixel_index
              pixel_index += 1
  
      return pix_to_full_pix
docs: Determine the mapping between every masked pixelization-grid pixel and pixelization-grid pixel. This is
      performed by checking whether each pixelization-grid pixel is within the regular-masks, and mapping the indexes.
  
      Parameters
      -----------
      total_sparse_pixels : int
          The total number of pixels in the pixelization grid which fall within the regular-masks.
      mask : ccd.masks.Mask
          The regular-masks within which pixelization pixels must be inside
      unmasked_sparse_grid_pixel_centres : ndarray
          The centres of the unmasked pixelization grid pixels.