CADETProcess.optimization.OptimizationResults#
- class CADETProcess.optimization.OptimizationResults(success, exit_flag, exit_message, time_elapsed, cpu_time, system_information)[source]#
Optimization results.
- Attributes:
- optimization_problemOptimizationProblem
Optimization problem.
- optimizerOptimizerBase
Optimizer used to optimize the OptimizationProblem.
- successbool
True if optimization was successfully terminated. False otherwise.
- exit_flagint
Information about the solver termination.
- exit_messagestr
Additional information about the solver status.
- time_elapsedfloat
Execution time of simulation.
- cpu_timefloat
CPU run time, taking into account the number of cores used for the optimiation.
- system_informationdict
Information about the system on which the optimization was performed.
x
listnp.array: Optimal points.
f
np.ndarraynp.array: Optimal objective values.
g
np.ndarraynp.array: Optimal nonlinear constraint values.
- population_lastPopulation
Last population.
- pareto_frontParetoFront
Pareto optimal solutions.
- meta_frontParetoFront
Reduced pareto optimal solutions using meta scores and multi-criteria decision functions.
Methods
Verify if all required parameters are set.
plot_convergence
([target, figs, axs, ...])Plot the convergence of optimization metrics over evaluations.
plot_corner
(*args, **kwargs)Create a corner plot of the independent variables.
plot_figures
([show])Plot result figures.
plot_objectives
([include_meta, plot_pareto, ...])Plot objective function values for all optimization generations.
plot_pareto
([show, plot_pareto, ...])Plot Pareto fronts for each generation in the optimization.
Create csv files for optimization results.
to_dict
()Convert Results to a dictionary.
update
(new)Update Results.
update_from_dict
(data)Update internal state from dictionary.
update_meta
(meta_front)Update meta front with new population.
update_pareto
([pareto_new])Update pareto front with new population.
save_results
setup_convergence_figure