code: def plot(self):
          
          fig = self.dataset.plot()
          ax = fig.gca()
          ax.set_title(
              "{}\n{}, {}".format(self.dataset._get_dataset_name(), self.name, self.get_bmr_text())
          )
          if self.has_successfully_executed:
              self._set_x_range(ax)
              ax.plot(self._xs, self.get_ys(self._xs), label=self.name, **plotting.LINE_FORMAT)
              self._add_bmr_lines(ax)
          else:
              self._add_plot_failure(ax)
  
          ax.legend(**settings.LEGEND_OPTS)
  
          return fig
docs: After model execution, print the dataset, curve-fit, BMD, and BMDL.
  
          Example
          -------
  
          >>> import os
          >>> fn = os.path.expanduser('~/Desktop/image.png')
          >>> fig = model.plot()
          >>> fig.savefig(fn)
          >>> fig.clear()
  
          .. figure:: ../tests/resources/test_exponential_m4_plot.png
             :scale: 80%
             :align: center
             :alt: Example generated BMD plot
  
             BMD models can generate plots using the ``plot()`` method; an example
             is shown here.