Home > Mateda2.0 > knowledge_extraction > Response_to_selection.m

# Response_to_selection

## PURPOSE

[RS] = Response_to_selection(AllFunVals)

## SYNOPSIS

function[RS] = Response_to_selection(AllFunVals)

## DESCRIPTION

     [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)

## CROSS-REFERENCE INFORMATION

This function calls:

This function is called by:

- FitnessMeasuresComp %%%%%%%%%%%%%%% COMPUTATION OF FITNESS RELATED MEASURES %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
- Realized_heritability [b] = Realized_heritability(AllFunVals,AllSelFunVals)

## SOURCE CODE

    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