physbo.search.discrete.results module

class physbo.search.discrete.results.history

ベースクラス: object

export_all_sequence_best_fx()

Export all fx and actions at each sequence.

(The total number of data is total_num_research.)

戻り値:

• best_fx (numpy.ndarray)

• best_actions (numpy.ndarray)

export_sequence_best_fx()

Export fx and actions at each sequence. (The total number of data is num_runs.)

戻り値:

• best_fx (numpy.ndarray)

• best_actions (numpy.ndarray)

load(filename)

Load the information of the history.

パラメータ:

filename (str) -- The name of the file which stores the information of the history

save(filename)

Save the information of the history.

パラメータ:

filename (str) -- The name of the file which stores the information of the history

property time_get_action

property time_run_simulator

property time_total

property time_update_predictor

write(t, action, time_total=None, time_update_predictor=None, time_get_action=None, time_run_simulator=None)

Overwrite fx and chosen_actions by t and action.

パラメータ:

• t (numpy.ndarray) -- N dimensional array. The negative energy of each search candidate (value of the objective function to be optimized).

• action (numpy.ndarray) -- N dimensional array. The indexes of actions of each search candidate.

• time_total (numpy.ndarray) -- N dimenstional array. The total elapsed time in each step. If None (default), filled by 0.0.

• time_update_predictor (numpy.ndarray) -- N dimenstional array. The elapsed time for updating predictor (e.g., learning hyperparemters) in each step. If None (default), filled by 0.0.

• time_get_action (numpy.ndarray) -- N dimenstional array. The elapsed time for getting next action in each step. If None (default), filled by 0.0.

• time_run_simulator (numpy.ndarray) -- N dimenstional array. The elapsed time for running the simulator in each step. If None (default), filled by 0.0.