code: def regular_to_sparse_from_sparse_mappings(regular_to_unmasked_sparse, unmasked_sparse_to_sparse):
      
      total_regular_pixels = regular_to_unmasked_sparse.shape[0]
  
      regular_to_sparse = np.zeros(total_regular_pixels)
  
      for regular_index in range(total_regular_pixels):
      #    print(regular_index, regular_to_unmasked_sparse[regular_index], unmasked_sparse_to_sparse.shape[0])
          regular_to_sparse[regular_index] = unmasked_sparse_to_sparse[regular_to_unmasked_sparse[regular_index]]
  
  
      return regular_to_sparse
docs: Using the mapping between the regular-grid and unmasked pixelization grid, compute the mapping between each regular
      pixel and the masked pixelization grid.
  
      Parameters
      -----------
      regular_to_unmasked_sparse : ndarray
          The index mapping between every regular-pixel and masked pixelization pixel.
      unmasked_sparse_to_sparse : ndarray
          The index mapping between every masked pixelization pixel and unmasked pixelization pixel.