private boolean getNextPosition(
final Function1D<DoubleMatrix1D, Double> function,
final Function1D<DoubleMatrix1D, DoubleMatrix1D> grad,
final DataBundle data) {
final DoubleMatrix1D p = getDirection(data);
if (data.getLambda0() < 1.0) {
data.setLambda0(1.0);
} else {
data.setLambda0(data.getLambda0() * BETA);
}
updatePosition(p, function, data);
final double g1 = data.getG1();
// the function is invalid at the new position, try to recover
if (Double.isInfinite(g1) || Double.isNaN(g1)) {
bisectBacktrack(p, function, data);
}
if (data.getG1() > data.getG0() / (1 + ALPHA * data.getLambda0())) {
quadraticBacktrack(p, function, data);
int count = 0;
while (data.getG1() > data.getG0() / (1 + ALPHA * data.getLambda0())) {
if (count > 5) {
return false;
}
cubicBacktrack(p, function, data);
count++;
}
}
final DoubleMatrix1D deltaX = data.getDeltaX();
data.setX((DoubleMatrix1D) MA.add(data.getX(), deltaX));
data.setG0(data.getG1());
final DoubleMatrix1D gradNew = grad.evaluate(data.getX());
data.setDeltaGrad((DoubleMatrix1D) MA.subtract(gradNew, data.getGrad()));
data.setGrad(gradNew);
return true;
}
private boolean isConverged(final DataBundle data) {
final DoubleMatrix1D deltaX = data.getDeltaX();
final DoubleMatrix1D x = data.getX();
final int n = deltaX.getNumberOfElements();
double diff, scale;
for (int i = 0; i < n; i++) {
diff = Math.abs(deltaX.getEntry(i));
scale = Math.abs(x.getEntry(i));
if (diff > _absoluteTol + scale * _relativeTol) {
return false;
}
}
return (MA.getNorm2(data.getGrad()) < _absoluteTol);
}
private DoubleMatrix1D getDirection(final DataBundle data) {
return (DoubleMatrix1D)
MA.multiply(data.getInverseHessianEsimate(), MA.scale(data.getGrad(), -1.0));
}
