original_docstring: 
      Returns the reconstructed data vector from the blurred mapping matrix `f` and solution vector *S*.
  
      Parameters
      -----------
      mapping_matrix
          The matrix representing the blurred mappings between sub-grid pixels and pixelization pixels.
  
      
docstring: Returns the reconstructed data vector from the blurred mapping matrix `f` and solution vector *S*.
  Parameters
  
  mapping_matrix
  The matrix representing the blurred mappings between sub-grid pixels and pixelization pixels.
docstring_tokens: Returns the reconstructed data vector from the blurred mapping matrix ` f ` and solution vector * S * . Parameters mapping_matrix The matrix representing the blurred mappings between sub - grid pixels and pixelization pixels .
code: def mapped_reconstructed_data_via_image_to_pix_unique_from(
      data_to_pix_unique: np.ndarray,
      data_weights: np.ndarray,
      pix_lengths: np.ndarray,
      reconstruction: np.ndarray,
  ) -> np.ndarray:
      """
      Returns the reconstructed data vector from the blurred mapping matrix `f` and solution vector *S*.
  
      Parameters
      -----------
      mapping_matrix
          The matrix representing the blurred mappings between sub-grid pixels and pixelization pixels.
  
      """
  
      data_pixels = data_to_pix_unique.shape[0]
  
      mapped_reconstructed_data = np.zeros(data_pixels)
  
      for data_0 in range(data_pixels):
          for pix_0 in range(pix_lengths[data_0]):
  
              pix_for_data = data_to_pix_unique[data_0, pix_0]
  
              mapped_reconstructed_data[data_0] += (
                  data_weights[data_0, pix_0] * reconstruction[pix_for_data]
              )
  
      return mapped_reconstructed_data
code_tokens: def mapped_reconstructed_data_via_image_to_pix_unique_from ( data_to_pix_unique : np . ndarray , data_weights : np . ndarray , pix_lengths : np . ndarray , reconstruction : np . ndarray , ) -> np . ndarray : data_pixels = data_to_pix_unique . shape [ 0 ] mapped_reconstructed_data = np . zeros ( data_pixels ) for data_0 in range ( data_pixels ) : for pix_0 in range ( pix_lengths [ data_0 ] ) : pix_for_data = data_to_pix_unique [ data_0 , pix_0 ] mapped_reconstructed_data [ data_0 ] += ( data_weights [ data_0 , pix_0 ] * reconstruction [ pix_for_data ] ) return mapped_reconstructed_data
short_docstring: Returns the reconstructed data vector from the blurred mapping matrix `f` and solution vector *S*.
short_docstring_tokens: Returns the reconstructed data vector from the blurred mapping matrix ` f ` and solution vector * S * .
comment: """
      Returns the reconstructed data vector from the blurred mapping matrix `f` and solution vector *S*.
  
      Parameters
      -----------
      mapping_matrix
          The matrix representing the blurred mappings between sub-grid pixels and pixelization pixels.
  
      """