/**
* Make sure that the parameter sets of each population are updated (reinitialized) if a
* population is reinitialized.
*
* @see InterfacePopulationChangedEventListener
*/
@Override
public void registerPopulationStateChanged(Object source, String name) {
if (name.equals(Population.POPULATION_INITIALIZED)) {
Population pop = (Population) source;
CMAParamSet params = (CMAParamSet) (pop.getData(MutateESRankMuCMA.cmaParamsKey));
int mu;
if (pop.hasData(EvolutionStrategies.esMuParam)) {
mu = (Integer) pop.getData(EvolutionStrategies.esMuParam);
} else {
System.err.println("Unknown mu in reinit! using lambda/2...");
mu = pop.size() / 2;
}
pop.putData(
MutateESRankMuCMA.cmaParamsKey,
CMAParamSet.initCMAParams(params, mu, pop.size(), pop, params.firstSigma));
}
}
/**
* Initializes the CMA parameter set for given mu, lambda and a population. The initialSigma
* parameter is used as initial sigma directly unless it is <0, in that case the average range is
* used as initial sigma.
*
* @param params the CMA parameter set to be used - its data are overwritten
* @param mu ES mu parameter
* @param lambda ES lambda parameter
* @param pop associated Population
* @param initialSigma initial sigma or -1 to indicate the usage of average range
* @return
*/
public static CMAParamSet initCMAParams(
CMAParamSet params,
int mu,
int lambda,
double[] center,
double[][] range,
double initialSigma) {
// those are from initialize:
params.firstAdaptionDone = false;
params.range = range;
int dim = params.range.length;
params.eigenvalues = new double[dim];
Arrays.fill(params.eigenvalues, 1.);
params.meanX = new double[dim];
params.pathC = new double[dim];
params.pathS = new double[dim];
params.mC = Matrix.identity(dim, dim);
params.mB = Matrix.identity(dim, dim);
// from adaptAfterSel
params.weights = initWeights(mu, lambda);
double muEff = getMuEff(params.weights, mu);
params.c_sig = (muEff + 2) / (muEff + dim + 3);
// c_u_sig = Math.sqrt(c_sig * (2.-c_sig));
params.d_sig = params.c_sig + 1 + 2 * Math.max(0, Math.sqrt((muEff - 1) / (dim + 1)) - 1);
if (initialSigma < 0) { // this means we scale the average range
if (initialSigma != -0.25 && (initialSigma != -0.5)) {
EVAERROR.errorMsgOnce("Warning, unexpected initial sigma in CMAParamSet!");
}
initialSigma = -initialSigma * Mathematics.getAvgRange(params.range);
}
if (initialSigma <= 0) {
EVAERROR.errorMsgOnce("warning: initial sigma <= zero! Working with converged population?");
initialSigma = 10e-10;
}
params.sigma = initialSigma;
// System.out.println("INitial sigma: "+sigma);
params.firstSigma = params.sigma;
// System.out.println("new center is " + BeanInspector.toString(center));
params.meanX = center; // this might be ok?
return params;
}