gemseo / problems / scalable / data_driven / study

result module

Scalability study - Result

class gemseo.problems.scalable.data_driven.study.result.ScalabilityResult(name, id_scaling, id_sample)

Bases: object

Scalability Result.

Constructor.

Parameters

• name (str) – name of the scalability result.

• id_scaling (int) – scaling identifiant

• id_sample (int) – sample identifiant

get(algo, algo_options, formulation, formulation_options, scaling, n_calls, n_calls_linearize, n_calls_top_level, n_calls_linearize_top_level, exec_time, status, is_feasible, disc_names, output_names, old_varsizes, new_varsizes)

Get a scalability result for a given optimization strategy and a given scaling strategy.

Parameters

• algo (str) – name of the optimization algorithm

• algo_options (dict) – options of the optimization algorithm

• formulation (str) – name of the MDO formulation

• formulation_options (dict) – options of the MDO formulation

• scaling – scaling strategy

• n_calls (list(int)) – number of calls for each discipline

• n_calls_linearize (list(int)) – number of linearization for each discipline

• n_calls_top_level (list(int)) – number of calls for each discipline

• n_calls_linearize_top_level (list(int)) – number of linearization for each discipline

• exec_time (float) – execution time

• status (int) – status of the optimization scenario

• is_feasible (bool) – feasibility of the optimization solution

• disc_names (list(str)) – list of discipline names

• output_names (dict) – list of output names

• old_varsizes (dict) – old variable sizes

• new_varsizes (dict) – new variable sizes

get_file_path(study_directory)

Get file path.

Parameters

study_directory (str) – study directory name.

load(study_directory)

Load a scalability result from a pickle file whose name is the name of the ScalabilityResult instance.

save(study_directory)

Save a scalability result into a pickle file whose name is the name of the ScalabilityResult instance.

Parameters

study_directory (str) – study directory name.