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package optimization.examples;
import optimization.gradientBasedMethods.ConjugateGradient;
import optimization.gradientBasedMethods.GradientDescent;
import optimization.gradientBasedMethods.LBFGS;
import optimization.gradientBasedMethods.Objective;
import optimization.gradientBasedMethods.stats.OptimizerStats;
import optimization.linesearch.GenericPickFirstStep;
import optimization.linesearch.LineSearchMethod;
import optimization.linesearch.WolfRuleLineSearch;
import optimization.stopCriteria.GradientL2Norm;
import optimization.stopCriteria.StopingCriteria;
/**
* @author javg
*
*/
public class x2y2 extends Objective{
//Implements function ax2+ by2
double a, b;
public x2y2(double a, double b){
this.a = a;
this.b = b;
parameters = new double[2];
parameters[0] = 4;
parameters[1] = 4;
gradient = new double[2];
}
public double getValue() {
functionCalls++;
return a*parameters[0]*parameters[0]+b*parameters[1]*parameters[1];
}
public double[] getGradient() {
gradientCalls++;
gradient[0]=2*a*parameters[0];
gradient[1]=2*b*parameters[1];
return gradient;
// if(debugLevel >=2){
// double[] numericalGradient = DebugHelpers.getNumericalGradient(this, parameters, 0.000001);
// for(int i = 0; i < parameters.length; i++){
// double diff = Math.abs(gradient[i]-numericalGradient[i]);
// if(diff > 0.00001){
// System.out.println("Numerical Gradient does not match");
// System.exit(1);
// }
// }
// }
}
public void optimizeWithGradientDescent(LineSearchMethod ls, OptimizerStats stats, x2y2 o){
GradientDescent optimizer = new GradientDescent(ls);
StopingCriteria stop = new GradientL2Norm(0.001);
// optimizer.setGradientConvergenceValue(0.001);
optimizer.setMaxIterations(100);
boolean succed = optimizer.optimize(o,stats,stop);
System.out.println("Ended optimzation Gradient Descent\n" + stats.prettyPrint(1));
System.out.println("Solution: " + " x0 " + o.parameters[0]+ " x1 " + o.parameters[1]);
if(succed){
System.out.println("Ended optimization in " + optimizer.getCurrentIteration());
}else{
System.out.println("Failed to optimize");
}
}
public void optimizeWithConjugateGradient(LineSearchMethod ls, OptimizerStats stats, x2y2 o){
ConjugateGradient optimizer = new ConjugateGradient(ls);
StopingCriteria stop = new GradientL2Norm(0.001);
optimizer.setMaxIterations(10);
boolean succed = optimizer.optimize(o,stats,stop);
System.out.println("Ended optimzation Conjugate Gradient\n" + stats.prettyPrint(1));
System.out.println("Solution: " + " x0 " + o.parameters[0]+ " x1 " + o.parameters[1]);
if(succed){
System.out.println("Ended optimization in " + optimizer.getCurrentIteration());
}else{
System.out.println("Failed to optimize");
}
}
public void optimizeWithLBFGS(LineSearchMethod ls, OptimizerStats stats, x2y2 o){
LBFGS optimizer = new LBFGS(ls,10);
StopingCriteria stop = new GradientL2Norm(0.001);
optimizer.setMaxIterations(10);
boolean succed = optimizer.optimize(o,stats,stop);
System.out.println("Ended optimzation LBFGS\n" + stats.prettyPrint(1));
System.out.println("Solution: " + " x0 " + o.parameters[0]+ " x1 " + o.parameters[1]);
if(succed){
System.out.println("Ended optimization in " + optimizer.getCurrentIteration());
}else{
System.out.println("Failed to optimize");
}
}
public static void main(String[] args) {
x2y2 o = new x2y2(1,10);
System.out.println("Starting optimization " + " x0 " + o.parameters[0]+ " x1 " + o.parameters[1]);
o.setDebugLevel(4);
LineSearchMethod wolfe = new WolfRuleLineSearch(new GenericPickFirstStep(1),0.001,0.9);;
// LineSearchMethod ls = new ArmijoLineSearchMinimization();
OptimizerStats stats = new OptimizerStats();
o.optimizeWithGradientDescent(wolfe, stats, o);
o = new x2y2(1,10);
System.out.println("Starting optimization " + " x0 " + o.parameters[0]+ " x1 " + o.parameters[1]);
// ls = new ArmijoLineSearchMinimization();
stats = new OptimizerStats();
o.optimizeWithConjugateGradient(wolfe, stats, o);
o = new x2y2(1,10);
System.out.println("Starting optimization " + " x0 " + o.parameters[0]+ " x1 " + o.parameters[1]);
// ls = new ArmijoLineSearchMinimization();
stats = new OptimizerStats();
o.optimizeWithLBFGS(wolfe, stats, o);
}
public String toString(){
return "P1: " + parameters[0] + " P2: " + parameters[1] + " value " + getValue();
}
}
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