private void eidgendecomposition(CMAEvolutionaryAlgorithm algorithm, int N, int flgforce) {
if (countCUpdatesSinceEigenupdate == 0 && flgforce < 2) {
return;
}
if (!algorithm.getFlgDiag()
&& flgforce <= 0
&& countCUpdatesSinceEigenupdate < 1.0 / algorithm.getCcov() / N / 5.0) {
return;
}
if (algorithm.getFlgDiag()) {
for (int i = 0; i < N; i++) {
algorithm.getDiag()[i] = Math.sqrt(algorithm.getC()[i][i]);
}
algorithm.setCountCupdatesSinceEigenupdate(0);
} else {
// set B <- C
for (int i = 0; i < N; i++) {
for (int j = 0; j <= i; j++) {
algorithm.getB()[i][j] = algorithm.getB()[j][i] = algorithm.getC()[i][j];
}
}
// eigendecomposition:
double[] offdiag = new double[N];
tred2(N, algorithm.getB(), algorithm.getDiag(), offdiag);
tql2(N, algorithm.getDiag(), offdiag, algorithm.getB());
checkEigenSystem(N, algorithm.getC(), algorithm.getDiag(), algorithm.getB());
for (int i = 0; i < N; i++) {
if (algorithm.getDiag()[i] < 0.0) {
if (algorithm.isDebug()) {
System.err.println("ERROR - An eigenvalue has become negative.");
}
}
algorithm.getDiag()[i] = Math.sqrt(algorithm.getDiag()[i]);
}
algorithm.setCountCupdatesSinceEigenupdate(0);
}
/*
* TODO: Check if necessary
*/
if (StatUtils.min(algorithm.getDiag()) == 0.0) {
algorithm.setAxisRatio(Double.POSITIVE_INFINITY);
} else {
algorithm.setAxisRatio(
StatUtils.max(algorithm.getDiag()) / StatUtils.min(algorithm.getDiag()));
}
} // eigendecomposition
