result module¶
Scalability study - Result.
- class gemseo.problems.scalable.data_driven.study.result.ScalabilityResult(name, id_scaling, id_sample)[source]¶
Bases:
object
Scalability Result.
- Parameters:
- 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)[source]¶
Get a scalability result for a given optimization strategy and a given scaling strategy.
- Parameters:
algo (str) – The name of the optimization algorithm.
algo_options (Mapping[str, Any]) – The options of the optimization algorithm.
formulation (str) – The name of the MDO formulation.
formulation_options (Mapping[str, Any]) – The options of the MDO formulation.
scaling (Mapping[str, Any]) – The scaling strategy.
n_calls (Iterable[int]) – The number of calls per discipline.
n_calls_linearize (Iterable[int]) – The number of linearization per discipline
n_calls_top_level (Iterable[int]) – The number of calls per discipline
n_calls_linearize_top_level (Iterable[int]) – The number of linearizations per discipline.
exec_time (float) – The execution time.
status (int) – The status of the optimization scenario.
is_feasible (bool) – Whether the solution is feasible.
disc_names (Sequence[str]) – The names of the disciplines.
output_names (Sequence[str]) – The names of the outputs.
old_varsizes (Mapping[str, int]) – The sizes of the original variables.
new_varsizes (Mapping[str, int]) – The sizes of the new variables.
- Return type:
None