Hi K, You shouldn't need to do anything special for the complex case. Send me your code if you like and I can have a look.
David On 11/02/2011 09:08 AM, Kyunghoon Lee wrote: > Hi all, > > I made a code with rbOOmit for an acoustic horn problem. It seems the > greedy training process works, but if I run online with any inputs, the > output and output bound are always zeros. The way I did is > > // Read in the reduced basis data > rb_eval.read_offline_data_from_files(); > > // Set the parameters to online_mu_vector > rb_eval.set_current_parameters(online_mu_vector); > rb_eval.print_current_parameters(); > > // Now do the Online solve using the precomputed reduced basis > rb_eval.rb_solve(online_N); > > // Print out outputs as well as the corresponding output error > bounds. > std::cout<< "output = "<< rb_eval.RB_outputs[0] > << ", bound = "<< rb_eval.RB_output_error_bounds[0]<< > std::endl; > > I wonder if there is something I miss to handle complex outputs and output > bounds. > > K. Lee. > ------------------------------------------------------------------------------ > RSA® Conference 2012 > Save $700 by Nov 18 > Register now! > http://p.sf.net/sfu/rsa-sfdev2dev1 > _______________________________________________ > Libmesh-users mailing list > [email protected] > https://lists.sourceforge.net/lists/listinfo/libmesh-users ------------------------------------------------------------------------------ RSA® Conference 2012 Save $700 by Nov 18 Register now! http://p.sf.net/sfu/rsa-sfdev2dev1 _______________________________________________ Libmesh-users mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/libmesh-users
