rb_test_convergence(detailed_data,model) More...
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Functions | |
function [
max_test_errs , max_mu_index , min_test_errs , min_mu_index ] = | rb_test_convergence (detailed_data, model) |
rb_test_convergence(detailed_data,model) More... | |
rb_test_convergence(detailed_data,model)
Definition in file rb_test_convergence.m.
function [ max_test_errs , max_mu_index , min_test_errs , min_mu_index ] = rb_test_convergence | ( | detailed_data, | |
model | |||
) |
rb_test_convergence(detailed_data,model)
function determining the maximum and minimum test-error (linfty-l2 or estimator) for the given set of vectors mu (columns in detailed_data.RB_info.M_test) of the RB simulation with corresponding RB set. A convergence test is performed by performing this maximum and minimum detection for all numbers of RB from 1 to the complete set. the output is max_test_errs(i): the maximum test-quantity on the given mu-subset for reduced basis RB(:,1:i). The number of the mu, which incurs this maximum error is returned in max_mu_index(i). Similarly for min_test_errs and min_mu_index.
detailed_data | detailed data |
model | model |
max_test_errs | max test errs |
max_mu_index | max mu index |
min_test_errs | min test errs |
min_mu_index | min mu index |
RB_error_indicator —
error
or estimator
RB_detailed_test_savepath —
in case of error
this path either contains the test-samples or they are generated. error_algorithm —
algorithm computing the true error in case of error
mode test_N_samples —
(optional) number of N samples, which are tested, i.e. value 11 for a basis of size N=21 will give 11 test-results for the values N = 1,3,5,7,9,11,13,15,17,19,21 an equidistant sampling of the N-interval is realized. If not specified, all numbers 1:N are tested set_mu —
set muRB_info.M_test —
RB info.M test RB —
RB grid —
a structure containing geometry information of a mesh used for the discretizations Definition at line 17 of file rb_test_convergence.m.