opensbt.visualization package

Submodules

opensbt.visualization.combined module

opensbt.visualization.combined.calculate_combined_crit_pop(run_paths)

Unions critical solutions from all runs to approximate “real” critical design space.

opensbt.visualization.combined.calculate_combined_pf(run_paths, critical_only=False)

opensbt.visualization.combined.make_comparison_plot(max_evaluations, save_folder, subplot_metrics, subplot_names, algo_names, distance_tick, shift_error=False, suffix='', colors=None, cmap=None, figsize=(7, 5), linestyles=None, alpha=None)

opensbt.visualization.combined.make_comparison_single(max_evaluations, save_folder, subplot_metrics, subplot_names, algo_names, suffix='')

opensbt.visualization.combined.make_subplots(max_evaluations, save_folder, subplot_metrics, subplot_names, algo_names, distance_tick, suffix='')

opensbt.visualization.combined.plot_combined_analysis(metric_name_load, run_paths_array, save_folder, n_func_evals_lim, n_fitting_points, metric_name_label=None, step_chkp=None, error_mean=False)

opensbt.visualization.combined.plot_combined_analysis_last_min_max(metric_name, run_paths_array, save_folder)

Outputs mean/std/min/max for final metric value instead for several number of evaluations as in plot_combined_analysis

opensbt.visualization.combined.plot_combined_hypervolume_lin_analysis(run_paths_array, save_folder)

opensbt.visualization.combined.read_metric_single(filename, metric_name)

opensbt.visualization.combined.read_pf_single(filename)

opensbt.visualization.combined.retrieve_metric_data_from_csv(paths, n_algos)

opensbt.visualization.combined.statistical_analysis(metric_name_load, runs_bases, runs_test, algo_test, save_folder, metric_name_label=None)

opensbt.visualization.combined.statistical_analysis_from_overview(metric_name, input_folder, save_folder)

opensbt.visualization.combined.write_analysis_results(result_runs_all, save_folder, nadir, ideal)

opensbt.visualization.combined.write_last_metric_values(metric_name_load, run_paths_array, save_folder, metric_name_label=None)

opensbt.visualization.combined.write_metric_data_to_csv(save_folder, metric_names, algo_names, plot_array_hv, plot_array_igd, plot_array_sp, suffix='')

opensbt.visualization.combined.write_metric_data_to_csv_cid(save_folder, metric_name, algo_names, plot_array, suffix='')

opensbt.visualization.configuration module

opensbt.visualization.output_metric module

opensbt.visualization.output_metric.calculate_n_crit_distinct(res: Result, save_folder: str, bound_min=None, bound_max=None, n_cells=10, optimal=False, var='F')

opensbt.visualization.output_metric.cid_analysis_hitherto(res: Result, save_folder: str, reference_set=None, n_evals_by_axis=None)

opensbt.visualization.output_metric.gd_analysis(res: Result, save_folder: str, input_pf=None, filename='gd', mode='default', critical_only=False)

opensbt.visualization.output_metric.gd_analysis_hitherto(res: Result, save_folder: str, input_pf=None, filename='gd_global', mode='default')

opensbt.visualization.output_metric.hypervolume_analysis(res, save_folder, critical_only=False, ref_point_hv=None, ideal=None, nadir=None)

opensbt.visualization.output_metric.hypervolume_analysis_local(res, save_folder)

opensbt.visualization.output_metric.igd_analysis(res: Result, save_folder: str, critical_only=False, input_pf=None, filename='igd')

opensbt.visualization.output_metric.igd_analysis_hitherto(res: Result, save_folder: str, input_pf=None, filename='igd_global')

opensbt.visualization.output_metric.si_analysis(res, save_folder, input_pf, critical_only=False, ideal=None, nadir=None)

opensbt.visualization.output_metric.spread_analysis(res, save_folder, critical_only=False)

opensbt.visualization.output_metric.spread_analysis_hitherto(res, save_folder, hitherto=False)

opensbt.visualization.output_metric.write_metric_history(n_evals, hist_F, metric_name, save_folder)

opensbt.visualization.scenario_plotter module

opensbt.visualization.scenario_plotter.plot_scenario_gif(parameter_values, simout: SimulationOutput, savePath=None, fileName=None, trace_interval=0.25)

This functions visualizes the executed scenario.

opensbt.visualization.visualization3d module

opensbt.visualization.visualization3d.read_testcases(filename)

opensbt.visualization.visualization3d.visualize_3d(population, save_folder, labels, mode='critical', markersize=20, do_save=False, dimension='X', angles=[(45, -45), (45, 45), (45, 135), (45, 225), (0, 0), (0, 90), (0, 180), (0, 270)], show=False)

This function generated 3D plots of executed test inputs.

opensbt.visualization.visualizer module

class opensbt.visualization.visualizer.HandlerCircle(patch_func=None, **kwargs)

Bases: HandlerPatch

create_artists(legend, orig_handle, xdescent, ydescent, width, height, fontsize, trans)

Return the legend artists generated.

Parameters:

• legend (~matplotlib.legend.Legend) – The legend for which these legend artists are being created.

• orig_handle (~matplotlib.artist.Artist or similar) – The object for which these legend artists are being created.

• xdescent (int) – The rectangle (xdescent, ydescent, width, height) that the legend artists being created should fit within.

• ydescent (int) – The rectangle (xdescent, ydescent, width, height) that the legend artists being created should fit within.

• width (int) – The rectangle (xdescent, ydescent, width, height) that the legend artists being created should fit within.

• height (int) – The rectangle (xdescent, ydescent, width, height) that the legend artists being created should fit within.

• fontsize (int) – The fontsize in pixels. The legend artists being created should be scaled according to the given fontsize.

• trans (~matplotlib.transforms.Transform) – The transform that is applied to the legend artists being created. Typically from unit coordinates in the handler box to screen coordinates.

opensbt.visualization.visualizer._additional_description(res, save_folder, algorithm_name, **kwargs)

opensbt.visualization.visualizer._calc_properties(res, save_folder, algorithm_name, **kwargs)

opensbt.visualization.visualizer.all_critical_individuals(res, save_folder)

Output of all critical individuals

opensbt.visualization.visualizer.all_individuals(res, save_folder)

Output of all evaluated individuals

opensbt.visualization.visualizer.backup_problem(res, save_folder)

opensbt.visualization.visualizer.create_markers()

opensbt.visualization.visualizer.create_save_folder(problem: Problem, results_folder: str, algorithm_name: str, is_experimental=False)

opensbt.visualization.visualizer.design_space(res, save_folder, classification_type=ClassificationType.DT, iteration=None)

opensbt.visualization.visualizer.get_pop_using_mode(res: Result, mode: str)

opensbt.visualization.visualizer.objective_space(res, save_folder, iteration=None, show=False, last_iteration=True)

opensbt.visualization.visualizer.optimal_individuals(res, save_folder)

Output of optimal individuals (duplicate free)

opensbt.visualization.visualizer.plot_multi_objective_space(res, n_obj, save_folder_objective, objective_names, show, pf, last_iteration)

opensbt.visualization.visualizer.plot_single_objective_space(result, save_folder_plot, objective_names, show, pf)

opensbt.visualization.visualizer.plot_timeseries(res, save_folder, mode='crit', type='X', max='100')

opensbt.visualization.visualizer.plot_timeseries_basic(res, save_folder, mode='crit', write_max=100)

opensbt.visualization.visualizer.simulations(res, save_folder, mode='all', write_max=100)

Visualization of the results of simulations

opensbt.visualization.visualizer.write_calculation_properties(res: Result, save_folder: str, algorithm_name: str, algorithm_parameters: Dict, **kwargs)

opensbt.visualization.visualizer.write_generations(res, save_folder)

opensbt.visualization.visualizer.write_pf_individuals(save_folder, pf_pop)

Output of pf individuals (duplicate free)

opensbt.visualization.visualizer.write_simout(path, pop)

opensbt.visualization.visualizer.write_simulation_output(res: Result, save_folder: str, mode='all', write_max=100)

opensbt.visualization.visualizer.write_summary_results(res, save_folder)

Module contents