samer@0: /*
samer@0:  *	Copyright (c) 2000, Samer Abdallah, King's College London.
samer@0:  *	All rights reserved.
samer@0:  *
samer@0:  *	This software is provided AS iS and WITHOUT ANY WARRANTY; 
samer@0:  *	without even the implied warranty of MERCHANTABILITY or 
samer@0:  *	FITNESS FOR A PARTICULAR PURPOSE.
samer@0:  */
samer@0: 
samer@0: package	samer.maths.opt;
samer@0: import  samer.maths.*;
samer@0: import  samer.core.*;
samer@0: import  samer.core.types.*;
samer@0: import  samer.core.util.heavy.*;
samer@0: 
samer@0: /**
samer@0: 		unconstrained minimiser for smooth functions:
samer@0: 		-	ConjugateGradient 
samer@0: 		-	OR Quasi-newton (using GillMurray updates)
samer@0: 
samer@0: 		-	Safeguarded cubic interpolation line search using gradients
samer@0:    */
samer@0: 
samer@0: 
samer@0: public class UnconstrainedConjGrad extends MinimiserBase
samer@0: {
samer@0: 	ConjGrad		dir;
samer@0: 	double			guess;
samer@0: 
samer@0: 	public UnconstrainedConjGrad(Vec v, Functionx f)
samer@0: 	{
samer@0: 		super(v,f);
samer@0: 		dir = new ConjGrad(this);
samer@0: 		add(new VParameter( "hessian", new DoubleModel() {
samer@0: 			public void set(double h) { dir.invhess=1/h; }
samer@0: 			public double get() { return 1/dir.invhess; }
samer@0: 		} ));
samer@0: 	}
samer@0: 
samer@0: 	public void stopping() {}
samer@0: 	public void run()
samer@0: 	{
samer@0: 		double	beta;
samer@0: 		int		i, maxiter=getMaxiter();
samer@0: 		boolean	triedSteepest=false;
samer@0: 
samer@0: 		// dir.resetHessian(1);
samer@0: 		evaluate();
samer@0: 		dir.init();
samer@0: 		setSlope();
samer@0: 		// beta = vs.beta.value;
samer@0: 		beta = initialStep();
samer@0: 		sig1.off();
samer@0: 
samer@0: 		for (i=0; i<maxiter; i++) {
samer@0: 
samer@0: 			step(beta);
samer@0: 			lstest.init();
samer@0: 			ls.run(lstest);			// line search
samer@0: 			lsiters.next(lstest.count);
samer@0: 			steplength.next(alpha);
samer@0: 
samer@0: 			if (lstest.tiny && (P2.f>=P1.f)) {
samer@0: 				//  tiny step was no good
samer@0: 				sig1.on();
samer@0: 				sig2.off();
samer@0: 				if (gconv.isSatisfied(P1.g,this)) break;
samer@0: 				if (triedSteepest=true) break;
samer@0: 				sig2.on();
samer@0: 
samer@0: 				beta = this.beta.value;
samer@0: 
samer@0: 
samer@0: 				dir.init(); // reset to steepest descent
samer@0: 				setSlope();
samer@0: 				triedSteepest=true;
samer@0: 				continue;
samer@0: 			}
samer@0: 
samer@0: 			if (xfconv.isSatisfied(this)) { break; }
samer@0: 
samer@0: 			beta = nextStep();
samer@0: 			// beta = vs.beta.value;
samer@0: 			dir.update();
samer@0: 			move();
samer@0: 			perIteration();
samer@0: 		}
samer@0: 
samer@0: 		perOptimisation(i); // finishing off stuff
samer@0: 	}
samer@0: }