Index

A

accuracy (core.surrogate.Surrogate attribute) activation (metamod.ANN_pt.SparseModel attribute) activations (in module metamod.ANN_pt) adaptive_candidates() (in module visumod.plots) adaptive_methods (in module datamod.sampling) algorithm (core.optimization.Optimization attribute)

ANN (class in metamod.ANN_tf) ANN_base (class in metamod.ANN) ANN_pt (class in metamod.ANN_pt) ansys_project_folder (datamod.evaluator.EvaluatorANSYS attribute) append_verification() (core.surrogate.Surrogate method) append_verification_to_database() (in module datamod.results) ask_to_overwrite() (in module core.settings)

B

benchmark() (core.optimization.Optimization method) benchmark_accuracy() (in module metamod.performance) best_hp (core.surrogate.Surrogate attribute) build_dense_model() (metamod.ANN_tf.ANN method)

build_hypermodel() (metamod.ANN_pt.ANN_pt method) (metamod.ANN_tf.ANN method) build_sparse_model() (metamod.ANN_tf.ANN method) build_surrogate (in module run)

C

calculate_hypervolume() (in module optimod.performance) call_ansys() (datamod.evaluator.EvaluatorANSYSAPDL method) (datamod.evaluator.EvaluatorANSYSWB method) can_run_ansys() (datamod.evaluator.EvaluatorANSYS method) check_convergence() (core.surrogate.Surrogate method) (in module metamod.performance) check_licenses() (datamod.evaluator.EvaluatorANSYS method) check_valid_settings() (in module core.settings) col_names (datamod.get_data attribute) compare_pareto_fronts() (in module visumod) compare_surrogate() (in module visumod) converged (core.optimization.Optimization attribute)

convergence_metric (core.surrogate.Surrogate attribute) convergence_operator() (in module metamod.performance) coordinates (datamod.get_data attribute) core (module) core.model (module) core.optimization (module) core.settings (module) core.surrogate (module) correlation_heatmap() (in module visumod) cross_validate() (in module metamod) CubicSquared (class in datamod.problems) curve() (in module visumod.plots) Custom (class in datamod.problems)

D

data (core.surrogate.Surrogate attribute) datamod (module) datamod.evaluator (module) datamod.problems (module) datamod.results (module) datamod.sampling (module) default_termination() (in module optimod.termination) defined_metrics (in module metamod.performance)

determine_samples() (in module datamod.sampling) dim_in (core.model.Model attribute) (datamod.get_data attribute) dim_out (core.model.Model attribute) (datamod.get_data attribute) direct (core.optimization.Optimization attribute) diverging (core.surrogate.Surrogate attribute) dump_json() (in module core.settings) dump_object() (in module core.settings)

E

early_stop (metamod.ANN_pt.ANN_pt attribute) (metamod.ANN_tf.ANN attribute) early_stopping() (metamod.ANN_pt.SparseModel method) error (core.optimization.Optimization attribute) error_measure (core.optimization.Optimization attribute) evaluate() (datamod.evaluator.EvaluatorANSYS method) (datamod.evaluator.EvaluatorANSYSAPDL method) (datamod.evaluator.EvaluatorANSYSWB method) (datamod.evaluator.EvaluatorBenchmark method) (datamod.evaluator.EvaluatorData method)

evaluate_metrics() (in module metamod.performance) evaluate_samples() (core.surrogate.Surrogate method) Evaluator (class in datamod.evaluator) evaluator (core.model.Model attribute) EvaluatorANSYS (class in datamod.evaluator) EvaluatorANSYSAPDL (class in datamod.evaluator) EvaluatorANSYSWB (class in datamod.evaluator) EvaluatorBenchmark (class in datamod.evaluator) EvaluatorData (class in datamod.evaluator) evaluators (in module core.model)

F

file (core.surrogate.Surrogate attribute) fit() (metamod.ANN_pt.SparseModel method)

forward() (metamod.ANN_pt.SparseModel method) function (core.optimization.Optimization attribute) (datamod.problems.Custom attribute)

G

generate_results() (datamod.evaluator.Evaluator method) get_blackblue_cmap() (in module visumod.plots) get_callbacks() (metamod.ANN_tf.ANN method) get_data (class in datamod) get_info() (datamod.evaluator.EvaluatorANSYS method) (datamod.evaluator.EvaluatorBenchmark method) (datamod.evaluator.EvaluatorData method) (datamod.evaluator.RealoadNotAnEvaluator method) get_input_coordinates() (in module metamod.deploy)

get_input_from_id() (in module core.settings) get_operator() (in module optimod) get_plot_args() (in module visumod.plots) get_plotting_coordinates() (in module metamod.deploy) get_range() (in module datamod) get_results() (datamod.evaluator.EvaluatorANSYSAPDL method) (datamod.evaluator.EvaluatorANSYSWB method) get_results_folders() (in module core.settings) get_samples() (datamod.evaluator.EvaluatorData method) GettingStarted (class in datamod.problems)

H

Halton (class in datamod.sampling) header_names() (in module datamod.results)

heatmap() (in module visumod.plots) history (metamod.ANN_pt.TrainHistory attribute) hp_optimized (core.surrogate.Surrogate attribute)

I

initializers (in module metamod.ANN_pt) input (datamod.get_data attribute) input_param_name (datamod.evaluator.EvaluatorANSYS attribute)

invalid_param() (in module metamod.validation) iteration (datamod.evaluator.Evaluator attribute) (datamod.evaluator.EvaluatorANSYSWB attribute) iterations (core.optimization.Optimization attribute)

L

learning_curves() (in module visumod.plots) load_json() (in module core.settings) load_object() (in module core.settings) load_problem() (in module datamod)

load_results() (core.surrogate.Surrogate method) (in module datamod.results) load_surrogate (in module run) log_dir (metamod.ANN.ANN_base attribute)

M

make_data_file() (in module datamod.results) make_response_files() (in module datamod.results) make_workfolder() (in module core.settings) MatlabPeaks (class in datamod.problems) max_samples (in module core.surrogate) metamod (module) metamod.ANN (module) metamod.ANN_pt (module) metamod.ANN_tf (module)

metamod.deploy (module) metamod.performance (module) metamod.validation (module) Model (class in core.model) model (core.optimization.Optimization attribute) (core.surrogate.Surrogate attribute) (in module run) (metamod.ANN_pt.ANN_pt attribute) (metamod.ANN_tf.ANN attribute)

N

n_const (core.model.Model attribute) (core.optimization.Optimization attribute) n_obj (core.model.Model attribute) name (core.surrogate.Surrogate attribute) (metamod.ANN_pt.ANN_pt attribute) (metamod.ANN_tf.ANN attribute)

no_samples (core.surrogate.Surrogate attribute) norm_in (datamod.get_data attribute) norm_out (datamod.get_data attribute) normalize() (in module datamod)

O

Optimization (class in core.optimization) optimization (in module run) optimization_stats (core.optimization.Optimization attribute) optimize() (core.optimization.Optimization method) (in module run) optimize_hyperparameters() (core.surrogate.Surrogate method) (in module metamod) optimized (metamod.ANN.ANN_base attribute)

optimized_to_samples (core.surrogate.Surrogate attribute) optimod (module) optimod.performance (module) optimod.termination (module) optimum_model (core.optimization.Optimization attribute) optimum_surrogate (core.optimization.Optimization attribute) output (datamod.evaluator.EvaluatorANSYSWB attribute) (datamod.get_data attribute)

P

pareto_fronts() (in module visumod.plots) pcp() (in module visumod.plots) perform_optimization (in module run) plot_adaptive_candidates() (in module visumod) plot_raw() (in module visumod) plot_response() (core.surrogate.Surrogate method) plot_results() (core.optimization.Optimization method)

plot_training_history() (in module visumod) pretrain() (metamod.ANN_pt.ANN_pt method) (metamod.ANN_tf.ANN method) problem (core.optimization.Optimization attribute) (datamod.evaluator.EvaluatorBenchmark attribute) problem_ids (in module run) problems (in module datamod.problems) prune_model() (metamod.ANN_tf.ANN method)

R

range_in (core.model.Model attribute) (core.optimization.Optimization attribute) (datamod.get_data attribute) range_norm (core.surrogate.Surrogate attribute) range_out (datamod.get_data attribute) RealoadNotAnEvaluator (class in datamod.evaluator) ref_point (core.optimization.Optimization attribute) ref_points (in module core.optimization) reload() (core.surrogate.Surrogate method) reload_info() (in module metamod) reload_surrogate() (in module run) reoptimization_ratio (core.surrogate.Surrogate attribute)

report() (core.optimization.Optimization method) (core.surrogate.Surrogate method) report_divergence() (in module metamod.performance) res (core.optimization.Optimization attribute) resample_adaptive() (in module datamod.sampling) resample_static() (in module datamod.sampling) response (datamod.get_data attribute) response_grid() (in module datamod.sampling) restart_check() (in module core.settings) results (datamod.evaluator.EvaluatorBenchmark attribute) retrieve_metric() (in module metamod.performance) RMSE() (in module metamod.performance) run (module)

S

sample() (core.surrogate.Surrogate method) (in module datamod.sampling) sample_adaptive() (in module datamod.sampling) sample_bounds (in module datamod.sampling) sample_size_convergence() (in module visumod) samples (core.surrogate.Surrogate attribute) sampling_iterations (core.surrogate.Surrogate attribute) samplings (in module datamod.sampling) save() (core.surrogate.Surrogate method) (metamod.ANN_pt.ANN_pt method) (metamod.ANN_tf.ANN method) save_figure() (in module visumod.plots) save_results (datamod.evaluator.Evaluator attribute) scale() (in module datamod) scale_samples() (in module datamod.sampling) scatter() (in module visumod.plots) scatter_pymoo() (in module visumod.plots) scrape_license_info() (datamod.evaluator.EvaluatorANSYS method) set_algorithm() (in module optimod) set_optimization() (in module optimod) set_problem() (core.optimization.Optimization method) set_surrogate() (in module metamod)

set_validation() (in module metamod.validation) set_validation_values() (metamod.ANN.ANN_base method) settings (in module core.settings) setup (datamod.evaluator.EvaluatorANSYS attribute) solve_problem() (in module optimod) source_file (datamod.evaluator.EvaluatorData attribute) SparseModel (class in metamod.ANN_pt) split_holdout() (in module metamod.validation) split_kfold() (in module metamod.validation) split_methods (in module metamod.validation) split_rlt() (in module metamod.validation) Squared (class in datamod.problems) store() (metamod.ANN_pt.TrainHistory method) subnetworks (metamod.ANN_pt.SparseModel attribute) surface_pymoo() (in module visumod.plots) Surrogate (class in core.surrogate) surrogate (core.optimization.Optimization attribute) (core.surrogate.Surrogate attribute) (in module run) surrogate_response() (in module visumod) surrogates (core.surrogate.Surrogate attribute) swish() (in module metamod.ANN_pt)

T

tbd (metamod.ANN.ANN_base attribute) template (datamod.evaluator.EvaluatorANSYSWB attribute) termination (core.optimization.Optimization attribute) train() (core.surrogate.Surrogate method)

train_from_data (in module run) train_surrogate() (in module metamod) (in module run) trained (core.surrogate.Surrogate attribute) TrainHistory (class in metamod.ANN_pt)

U

unnormalize_res() (in module optimod) update_input() (datamod.evaluator.EvaluatorANSYSAPDL method) (datamod.evaluator.EvaluatorANSYSWB method)

update_settings() (in module core.settings)

V

valid_licences (datamod.evaluator.EvaluatorANSYS attribute) validation_points (metamod.ANN.ANN_base attribute) verification (core.surrogate.Surrogate attribute) verification_file (core.surrogate.Surrogate attribute) verify() (core.optimization.Optimization method)

verify_results() (in module optimod.performance) vis_design_space() (in module visumod) vis_objective_space() (in module visumod) vis_objective_space_pcp() (in module visumod) visumod (module) visumod.plots (module)

W

workbench_project (datamod.evaluator.EvaluatorANSYSWB attribute)

write_results() (in module datamod.results) write_stats() (metamod.ANN.ANN_base method)