parameters: (self)
return_statement: return True
docstring: Recalculates the TF Asymmetry functions based on the datasets and normal functions in the model.
docstring_summary: Recalculates the TF Asymmetry functions based on the datasets and normal functions in the model.
docstring_tokens: Recalculates the TF Asymmetry functions based on the datasets and normal functions in the model .
function: def recalculate_tf_asymmetry_functions(self) -> bool:
          """Recalculates the TF Asymmetry functions based on the datasets and normal functions in the model."""
          tf_compliant, _ = self.check_datasets_are_tf_asymmetry_compliant()
          if self.fitting_context.tf_asymmetry_mode and tf_compliant:
              try:
                  self._recalculate_tf_asymmetry_functions()
              except RuntimeError:
                  self.reset_tf_asymmetry_functions()
                  logger.error("The input function was not of the form N*(1+f)+A*exp(-lambda*t)).")
                  return False
          else:
              self.reset_tf_asymmetry_functions()
          return True
function_tokens: def recalculate_tf_asymmetry_functions ( self ) -> bool : tf_compliant , _ = self . check_datasets_are_tf_asymmetry_compliant ( ) if self . fitting_context . tf_asymmetry_mode and tf_compliant : try : self . _recalculate_tf_asymmetry_functions ( ) except RuntimeError : self . reset_tf_asymmetry_functions ( ) logger . error ( "The input function was not of the form N*(1+f)+A*exp(-lambda*t))." ) return False else : self . reset_tf_asymmetry_functions ( ) return True