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package optimization.linesearch;
import optimization.util.Interpolation;
/**
* Implements Back Tracking Line Search as described on page 37 of Numerical Optimization.
* Also known as armijo rule
* @author javg
*
*/
public class ArmijoLineSearchMinimization implements LineSearchMethod{
/**
* How much should the step size decrease at each iteration.
*/
double contractionFactor = 0.5;
double c1 = 0.0001;
double sigma1 = 0.1;
double sigma2 = 0.9;
double initialStep;
int maxIterations = 10;
public ArmijoLineSearchMinimization(){
this.initialStep = 1;
}
//Experiment
double previousStepPicked = -1;;
double previousInitGradientDot = -1;
double currentInitGradientDot = -1;
public void reset(){
previousStepPicked = -1;;
previousInitGradientDot = -1;
currentInitGradientDot = -1;
}
public void setInitialStep(double initial){
initialStep = initial;
}
/**
*
*/
public double getStepSize(DifferentiableLineSearchObjective o) {
currentInitGradientDot = o.getInitialGradient();
//Should update all in the objective
o.updateAlpha(initialStep);
int nrIterations = 0;
//System.out.println("tried alpha" + initialStep + " value " + o.getCurrentValue());
while(!WolfeConditions.suficientDecrease(o,c1)){
if(nrIterations >= maxIterations){
o.printLineSearchSteps();
return -1;
}
double alpha=o.getAlpha();
double alphaTemp =
Interpolation.quadraticInterpolation(o.getOriginalValue(), o.getInitialGradient(), alpha, o.getCurrentValue());
if(alphaTemp >= sigma1 || alphaTemp <= sigma2*o.getAlpha()){
// System.out.println("using alpha temp " + alphaTemp);
alpha = alphaTemp;
}else{
// System.out.println("Discarding alpha temp " + alphaTemp);
alpha = alpha*contractionFactor;
}
// double alpha =o.getAlpha()*contractionFactor;
o.updateAlpha(alpha);
//System.out.println("tried alpha" + alpha+ " value " + o.getCurrentValue());
nrIterations++;
}
//System.out.println("Leavning line search used:");
//o.printLineSearchSteps();
previousInitGradientDot = currentInitGradientDot;
previousStepPicked = o.getAlpha();
return o.getAlpha();
}
public double getInitialGradient() {
return currentInitGradientDot;
}
public double getPreviousInitialGradient() {
return previousInitGradientDot;
}
public double getPreviousStepUsed() {
return previousStepPicked;
}
}
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