original_docstring: 
      Returns the curvature matrix `F` from a blurred mapping matrix `f` and the 1D noise-map $\sigma$
       (see Warren & Dye 2003).
  
      Parameters
      -----------
      mapping_matrix
          The matrix representing the mappings (these could be blurred or transfomed) between sub-grid pixels and
          pixelization pixels.
      noise_map
          Flattened 1D array of the noise-map used by the inversion during the fit.
      
docstring: Returns the curvature matrix `F` from a blurred mapping matrix `f` and the 1D noise-map $\sigma$
  .
  
  Parameters
  
  mapping_matrix
  The matrix representing the mappings (these could be blurred or transfomed) between sub-grid pixels and
  pixelization pixels.
  noise_map
  Flattened 1D array of the noise-map used by the inversion during the fit.
docstring_tokens: Returns the curvature matrix ` F ` from a blurred mapping matrix ` f ` and the 1D noise - map $ \ sigma$ . Parameters mapping_matrix The matrix representing the mappings ( these could be blurred or transfomed ) between sub - grid pixels and pixelization pixels . noise_map Flattened 1D array of the noise - map used by the inversion during the fit .
code: def curvature_matrix_via_mapping_matrix_from(
      mapping_matrix: np.ndarray, noise_map: np.ndarray
  ) -> np.ndarray:
      """
      Returns the curvature matrix `F` from a blurred mapping matrix `f` and the 1D noise-map $\sigma$
       (see Warren & Dye 2003).
  
      Parameters
      -----------
      mapping_matrix
          The matrix representing the mappings (these could be blurred or transfomed) between sub-grid pixels and
          pixelization pixels.
      noise_map
          Flattened 1D array of the noise-map used by the inversion during the fit.
      """
      array = mapping_matrix / noise_map[:, None]
      curvature_matrix = np.dot(array.T, array)
      return curvature_matrix
code_tokens: def curvature_matrix_via_mapping_matrix_from ( mapping_matrix : np . ndarray , noise_map : np . ndarray ) -> np . ndarray : array = mapping_matrix / noise_map [ : , None ] curvature_matrix = np . dot ( array . T , array ) return curvature_matrix
short_docstring: Returns the curvature matrix `F` from a blurred mapping matrix `f` and the 1D noise-map $\sigma$
  (see Warren & Dye 2003).
short_docstring_tokens: Returns the curvature matrix ` F ` from a blurred mapping matrix ` f ` and the 1D noise - map $ \ sigma$ ( see Warren & Dye 2003 ) .
comment: """
      Returns the curvature matrix `F` from a blurred mapping matrix `f` and the 1D noise-map $\sigma$
       (see Warren & Dye 2003).
  
      Parameters
      -----------
      mapping_matrix
          The matrix representing the mappings (these could be blurred or transfomed) between sub-grid pixels and
          pixelization pixels.
      noise_map
          Flattened 1D array of the noise-map used by the inversion during the fit.
      """