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package optimization.stopCriteria;
import optimization.gradientBasedMethods.Objective;
import optimization.gradientBasedMethods.ProjectedObjective;
import optimization.util.MathUtils;
/**
* Divides the norm by the norm at the begining of the iteration
* @author javg
*
*/
public class NormalizedGradientL2Norm extends GradientL2Norm{
/**
* Stop if gradientNorm/(originalGradientNorm) smaller
* than gradientConvergenceValue
*/
protected double originalGradientNorm = -1;
public void reset(){
originalGradientNorm = -1;
}
public NormalizedGradientL2Norm(double gradientConvergenceValue){
super(gradientConvergenceValue);
}
public boolean stopOptimization(Objective obj){
double norm = MathUtils.L2Norm(obj.gradient);
if(originalGradientNorm == -1){
originalGradientNorm = norm;
}
if(originalGradientNorm < 1E-10){
System.out.println("Gradient norm is zero " + originalGradientNorm);
return true;
}
double normalizedNorm = 1.0*norm/originalGradientNorm;
if( normalizedNorm < gradientConvergenceValue){
System.out.println("Gradient norm below normalized normtreshold: " + norm + " original: " + originalGradientNorm + " normalized norm: " + normalizedNorm);
return true;
}else{
// System.out.println("projected gradient norm: " + norm);
return false;
}
}
}
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