code: def dimension(self):
          
          if self.C00 is None:  # no data yet
              if isinstance(self.dim, int):  # return user choice
                  warnings.warn('Returning user-input for dimension, since this model has not yet been estimated.')
                  return self.dim
              raise RuntimeError('Please call set_model_params prior using this method.')
  
          if not self._svd_performed:
              self._diagonalize()
          return self._dimension(self._rank0, self._rankt, self.dim, self.singular_values)
docs: output dimension