def setup_study(trial_num, _intermediate_values):
# type: (int, List[List[float]]) -> Study
_study = optuna.study.create_study(direction="minimize")
trial_ids = [
_study._storage.create_new_trial(_study._study_id)
for _ in range(trial_num)
]
for step, values in enumerate(_intermediate_values):
# Study does not have any trials.
with pytest.raises(ValueError):
_all_trials = _study._storage.get_all_trials(_study._study_id)
_direction = _study._storage.get_study_direction(
_study._study_id)
percentile._get_percentile_intermediate_result_over_trials(
_all_trials, _direction, step, 25)
for i in range(trial_num):
trial_id = trial_ids[i]
value = values[i]
_study._storage.set_trial_intermediate_value(
trial_id, step, value)
# Set trial states complete because this method ignores incomplete trials.
for trial_id in trial_ids:
_study._storage.set_trial_state(trial_id, TrialState.COMPLETE)
return _study
def test_get_percentile_intermediate_result_over_trials():
# type: () -> None
def setup_study(trial_num, _intermediate_values):
# type: (int, List[List[float]]) -> Study
_study = optuna.study.create_study(direction="minimize")
trial_ids = [_study._storage.create_new_trial(
_study.study_id) for _ in range(trial_num)]
for step, values in enumerate(_intermediate_values):
# Study does not have any trials.
with pytest.raises(ValueError):
_all_trials = _study._storage.get_all_trials(_study.study_id)
_direction = _study._storage.get_study_direction(_study.study_id)
percentile._get_percentile_intermediate_result_over_trials(
_all_trials, _direction, step, 25)
for i in range(trial_num):
trial_id = trial_ids[i]
value = values[i]
_study._storage.set_trial_intermediate_value(trial_id, step, value)
# Set trial states complete because this method ignores incomplete trials.
for trial_id in trial_ids:
_study._storage.set_trial_state(trial_id, TrialState.COMPLETE)
return _study
# Input value has no NaNs but float values (step=0).
intermediate_values = [[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]]
study = setup_study(9, intermediate_values)
all_trials = study._storage.get_all_trials(study.study_id)
direction = study._storage.get_study_direction(study.study_id)
assert 0.3 == percentile._get_percentile_intermediate_result_over_trials(
all_trials, direction, 0, 25.0)
# Input value has a float value and NaNs (step=1).
intermediate_values.append([
0.1, 0.2, 0.3, 0.4, 0.5,
float('nan'), float('nan'), float('nan'), float('nan')])
study = setup_study(9, intermediate_values)
all_trials = study._storage.get_all_trials(study.study_id)
direction = study._storage.get_study_direction(study.study_id)
assert 0.2 == percentile._get_percentile_intermediate_result_over_trials(
all_trials, direction, 1, 25.0)
# Input value has NaNs only (step=2).
intermediate_values.append([
float('nan'), float('nan'), float('nan'), float('nan'), float('nan'),
float('nan'), float('nan'), float('nan'), float('nan')])
study = setup_study(9, intermediate_values)
all_trials = study._storage.get_all_trials(study.study_id)
direction = study._storage.get_study_direction(study.study_id)
assert math.isnan(percentile._get_percentile_intermediate_result_over_trials(
all_trials, direction, 2, 75))