Response_to_selection

 [RS] = Response_to_selection(AllFunVals) 
 Response_to_selection: Computes the response to selection for every
                        objective. $R(t) = \bar{f}(t+1) -\bar{f}(t)$.

 INPUT
 AllFunVals{maxgen} = FunVals(PopSize,n_objectives): Cell array that stores the evaluations of all the objectives
                                                     for all the individuals in every generation
  OUTPUT
  RS: Response to selection at each generation k>1
  Example:
  for i=1:ngen, auxr{1,i} = Cache{4,i}; end,
  [RS] = Response_to_selection(auxr)

 Last version 8/26/2008. Roberto Santana (roberto.santana@ehu.es)

0001 function[RS] = Response_to_selection(AllFunVals) 
0002 % [RS] = Response_to_selection(AllFunVals)
0003 % Response_to_selection: Computes the response to selection for every
0004 %                        objective. $R(t) = \bar{f}(t+1) -\bar{f}(t)$.
0005 %
0006 % INPUT
0007 % AllFunVals{maxgen} = FunVals(PopSize,n_objectives): Cell array that stores the evaluations of all the objectives
0008 %                                                     for all the individuals in every generation
0009 %  OUTPUT
0010 %  RS: Response to selection at each generation k>1
0011 %  Example:
0012 %  for i=1:ngen, auxr{1,i} = Cache{4,i}; end,
0013 %  [RS] = Response_to_selection(auxr)
0014 %
0015 % Last version 8/26/2008. Roberto Santana (roberto.santana@ehu.es)
0016 
0017 k = size(AllFunVals,2);                % Number of generations
0018 n_objectives = size(AllFunVals{1},2);  % Number of objectives
0019 PopSize =  size(AllFunVals{1},1);      % Population size
0020 
0021 for i=2:k,
0022   RS{i} = mean(AllFunVals{i}) - mean(AllFunVals{i-1});
0023 end