lin_evol_opt_rb_init_values_separate_bases.m

function [a0,c0] = lin_evol_opt_rb_init_values_separate_bases(model,detailed_data)
%function a0 = lin_evol_opt_rb_init_values_separate_bases(models,detailed_data)
%
% function computing the reduced basis initial values for the solution (a0) and the
% derivative solutions (c0). If the
% decomposition mode is 'coefficients', the detailed_data are
% superfluous, can (and should for H-independence) be empty.
%
% required fields of model 
% init_values_algorithm: name of function for computing the
%                 detailed initvalues-DOF with arguments (grid, params)
%                 example: init_values_cog
%
% c0 is a cell array
%
% Function supports affine decomposition, i.e. different operation modes
% guided by optional field decomp_mode in params. See also the
% contents.txt for general explanation
%

% Markus Dihlmann 30.03.2011

% determine affine_decomposition_mode as integer  
decomp_mode = model.decomp_mode;

if decomp_mode == 0 % complete: simple projection on RB
  %Nmax = size(detailed_data.RB,2);
  u0 = model.init_values_algorithm(model,detailed_data);
  A = detailed_data.W;
  a0 = u0' * A * detailed_data.RB;
  
  if model.compute_derivative_info
      RB_der = detailed_data.RB_der;
      p = sum(model.compute_derivative_indices);
      der_indices = find(model.compute_derivative_indices);
      c0=cell(p,1);
      for i=1:p
         c0{i} = u0' * A * RB_der{der_indices(i)};
      end
  else
      c0=[];
  end
  
elseif decomp_mode == 1
  Nmax = size(detailed_data.RB,2);
  u0 = model.init_values_algorithm(model,detailed_data);
  Q_u0 = length(u0);
  a0 = cell(Q_u0,1);
  a0(:) = {zeros(Nmax,1)}; 
  %    a0     : initial data projected on RB set: starting coefficients
  A = detailed_data.W;
  for q=1:Q_u0
    a0{q} = u0{q}' * A *  detailed_data.RB;
  end;
  
  % c0       :initial data projection on RB_derivatives
  if model.compute_derivative_info
      RB_der = detailed_data.RB_der;
      if isfield(model,'separate_bases_derivative_nr')
          p=model.separate_bases_derivative_nr;
          c0=cell(p,1);
          c0{p} = cell(Q_u0,1);
          c0{p}(:) = {zeros(size(RB_der{p},2),1)}; 
             for q=1:Q_u0
                c0{p}{q} = u0{q}' * A *  RB_der{p};
             end;
      else
          p = length(RB_der);
          c0=cell(p,1);
          for i=1:p
             c0{i} = cell(Q_u0,1);
             c0{i}(:) = {zeros(size(RB_der{i},2),1)}; 
             for q=1:Q_u0
                c0{i}{q} = u0{q}' * A *  RB_der{i};
             end;
          end
      end
      
  else
      c0={0};
  end
else % decomp_mode== 2 -> coefficients simply transfered from u0
  u0 = model.init_values_algorithm(model, []);
  a0 = u0;
  if model.compute_derivative_info
    c0 = model.rb_derivative_init_values_coefficients(model);
    %filter out coefficients actually needed
    %der_indices = find(model.compute_derivative_indices);
    %c0 = c0(der_indices,:);
  else 
      c0=0;
  end
end;