def _get_objective_v_param_plot(
search_space: SearchSpace,
model: ModelBridge,
metric_name: str,
trials: Dict[int, BaseTrial],
) -> Optional[go.Figure]:
range_params = list(search_space.range_parameters.keys())
if len(range_params) == 1:
# individual parameter slice plot
output_slice_plot = plot_slice_plotly(
model=not_none(model),
param_name=range_params[0],
metric_name=metric_name,
generator_runs_dict={
str(t.index): not_none(checked_cast(Trial, t).generator_run)
for t in trials.values()
},
)
return output_slice_plot
if len(range_params) > 1:
# contour plot
output_contour_plot = interact_contour_plotly(
model=not_none(model),
metric_name=metric_name,
)
return output_contour_plot
# if search space contains no range params
logger.warning(
"_get_objective_v_param_plot requires a search space with at least one "
"RangeParameter. Returning None."
)
return None
def testSlices(self):
exp = get_branin_experiment(with_batch=True)
exp.trials[0].run()
model = Models.BOTORCH(
# Model bridge kwargs
experiment=exp,
data=exp.fetch_data(),
)
# Assert that each type of plot can be constructed successfully
plot = plot_slice_plotly(model, model.parameters[0],
list(model.metric_names)[0])
self.assertIsInstance(plot, go.Figure)
plot = interact_slice_plotly(model)
self.assertIsInstance(plot, go.Figure)
plot = plot_slice(model, model.parameters[0],
list(model.metric_names)[0])
self.assertIsInstance(plot, AxPlotConfig)
plot = interact_slice(model)
self.assertIsInstance(plot, AxPlotConfig)