parameters: (self)
docstring: Returns true if the currently selected normalisation has its value fixed.
docstring_summary: Returns true if the currently selected normalisation has its value fixed.
docstring_tokens: Returns true if the currently selected normalisation has its value fixed .
function: def is_current_normalisation_fixed(self) -> bool:
          """Returns true if the currently selected normalisation has its value fixed."""
          if self.fitting_context.current_dataset_index is not None:
              if self.fitting_context.simultaneous_fitting_mode:
                  return self._is_normalisation_fixed_in_tf_asymmetry_simultaneous_mode(self.current_dataset_index)
              else:
                  return self._is_normalisation_fixed_in_tf_asymmetry_single_fit_mode(self.current_dataset_index)
          else:
              return DEFAULT_IS_NORMALISATION_FIXED
function_tokens: def is_current_normalisation_fixed ( self ) -> bool : if self . fitting_context . current_dataset_index is not None : if self . fitting_context . simultaneous_fitting_mode : return self . _is_normalisation_fixed_in_tf_asymmetry_simultaneous_mode ( self . current_dataset_index ) else : return self . _is_normalisation_fixed_in_tf_asymmetry_single_fit_mode ( self . current_dataset_index ) else : return DEFAULT_IS_NORMALISATION_FIXED