code: def get_mae(self, data_x=None, data_y=None):
          
          if data_x is None:
              data_x = np.array(self.args["x"])
          if data_y is None:
              data_y = np.array(self.args["y"])
          if len(data_x) != len(data_y):
              raise ValueError("Lengths of data_x and data_y are different")
          mae_y = self.bestfit_func(data_x)
          return np.mean(abs(mae_y - data_y))
docs: Get Mean Absolute Error using
          self.bestfit_func
  
          args:
              data_x: array_like, default=x
                  x value used to determine rmse, used if only a section
                  of x is to be calculated
              data_y: array_like, default=y
                  y value used to determine rmse, used if only a section
                  of y is to be calculated