def test_get_standard_plots(self):
exp = get_branin_experiment()
self.assertEqual(
len(
get_standard_plots(
experiment=exp,
generation_strategy=get_generation_strategy())),
0,
)
def test_get_standard_plots(self):
exp = get_branin_experiment()
self.assertEqual(
len(
get_standard_plots(
experiment=exp, model=get_generation_strategy().model
)
),
0,
)
exp = get_branin_experiment(with_batch=True, minimize=True)
exp.trials[0].run()
gs = choose_generation_strategy(search_space=exp.search_space)
gs._model = Models.BOTORCH(
experiment=exp,
data=exp.fetch_data(),
)
plots = get_standard_plots(experiment=exp, model=gs.model)
self.assertEqual(len(plots), 3)
self.assertTrue(all(isinstance(plot, go.Figure) for plot in plots))
def test_get_standard_plots(self):
exp = get_branin_experiment()
self.assertEqual(
len(
get_standard_plots(experiment=exp,
model=get_generation_strategy().model)),
0,
)
exp = get_branin_experiment(with_batch=True, minimize=True)
exp.trials[0].run()
plots = get_standard_plots(
experiment=exp,
model=Models.BOTORCH(experiment=exp, data=exp.fetch_data()),
)
self.assertEqual(len(plots), 6)
self.assertTrue(all(isinstance(plot, go.Figure) for plot in plots))
exp = get_branin_experiment_with_multi_objective(with_batch=True)
exp.optimization_config.objective.objectives[0].minimize = False
exp.optimization_config.objective.objectives[1].minimize = True
exp.optimization_config._objective_thresholds = [
ObjectiveThreshold(metric=exp.metrics["branin_a"],
op=ComparisonOp.GEQ,
bound=-100.0),
ObjectiveThreshold(metric=exp.metrics["branin_b"],
op=ComparisonOp.LEQ,
bound=100.0),
]
exp.trials[0].run()
plots = get_standard_plots(experiment=exp,
model=Models.MOO(experiment=exp,
data=exp.fetch_data()))
self.assertEqual(len(plots), 7)
# All plots are successfully created when objective thresholds are absent
exp.optimization_config._objective_thresholds = []
plots = get_standard_plots(experiment=exp,
model=Models.MOO(experiment=exp,
data=exp.fetch_data()))
self.assertEqual(len(plots), 7)
exp = get_branin_experiment_with_timestamp_map_metric(
with_status_quo=True)
exp.new_trial().add_arm(exp.status_quo)
exp.trials[0].run()
exp.new_trial(generator_run=Models.SOBOL(
search_space=exp.search_space).gen(n=1))
exp.trials[1].run()
plots = get_standard_plots(
experiment=exp,
model=Models.BOTORCH(experiment=exp, data=exp.fetch_data()),
true_objective_metric_name="branin",
)
self.assertEqual(len(plots), 9)
self.assertTrue(all(isinstance(plot, go.Figure) for plot in plots))
self.assertIn(
"Objective branin_map vs. True Objective Metric branin",
[p.layout.title.text for p in plots],
)
with self.assertRaisesRegex(
ValueError, "Please add a valid true_objective_metric_name"):
plots = get_standard_plots(
experiment=exp,
model=Models.BOTORCH(experiment=exp, data=exp.fetch_data()),
true_objective_metric_name="not_present",
)