hp_demo.m

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%demo script for hp-approach routine 
clear;
params.coarse_factor =8;
model = advection_fv_output_model(params);

model.RB_train_rand_seed = 1234;
model.RB_error_indicator = 'estimator';
model.get_rb_from_detailed_data = @(detailed_data)detailed_data.RB;
model.orthonormalize=@model_orthonormalize_qr;
%size of the training set:
model.RB_train_size = 20;  



% parameters for hp-approach
hp_params.rho = 10;
hp_params.rho_POD = 1;
hp_params.error_tol1=0.8;
hp_params.error_tol2=0.01;
%generate the hp-model and the model_data
hp_model=hp_gen_model(model,hp_params);
model_data = gen_model_data(hp_model);

%set the first anchor 
hp_model = set_mu(hp_model,[1;1]);

%compute a h_refinment and RB generation
hp_model = h_refinement(hp_model,model_data);
hp_model = hp_rb_generation(hp_model);

%compute a reduced simulation for parameter [0.13;0.13]
hp_model = set_mu(hp_model,[0.13;0.13]);
sim_data = hp_simulation(hp_model);

plot_sim_data(hp_model,model_data,sim_data,[]);