parameters: (self)
docstring: Undoes the previous fit using the saved undo data.
docstring_summary: Undoes the previous fit using the saved undo data.
docstring_tokens: Undoes the previous fit using the saved undo data .
function: def undo_previous_fit(self) -> None:
          """Undoes the previous fit using the saved undo data."""
          if self.number_of_undos() > 0:
              self.fitting_context.undo_previous_fit()
  
              undo_dataset_index = self.fitting_context.dataset_indices_for_undo.pop()
              undo_fit_function = self.fitting_context.single_fit_functions_for_undo.pop()
              undo_fit_status = self.fitting_context.fit_statuses_for_undo.pop()
              undo_chi_squared = self.fitting_context.chi_squared_for_undo.pop()
  
              self.fitting_context.single_fit_functions[undo_dataset_index] = undo_fit_function
              self.fitting_context.fit_statuses[undo_dataset_index] = undo_fit_status
              self.fitting_context.chi_squared[undo_dataset_index] = undo_chi_squared
function_tokens: def undo_previous_fit ( self ) -> None : if self . number_of_undos ( ) > 0 : self . fitting_context . undo_previous_fit ( ) undo_dataset_index = self . fitting_context . dataset_indices_for_undo . pop ( ) undo_fit_function = self . fitting_context . single_fit_functions_for_undo . pop ( ) undo_fit_status = self . fitting_context . fit_statuses_for_undo . pop ( ) undo_chi_squared = self . fitting_context . chi_squared_for_undo . pop ( ) self . fitting_context . single_fit_functions [ undo_dataset_index ] = undo_fit_function self . fitting_context . fit_statuses [ undo_dataset_index ] = undo_fit_status self . fitting_context . chi_squared [ undo_dataset_index ] = undo_chi_squared