add optimization library source code

git-svn-id: https://ws10smt.googlecode.com/svn/trunk@204 ec762483-ff6d-05da-a07a-a48fb63a330f

1 files changed, 127 insertions, 0 deletions

diff --git a/gi/posterior-regularisation/prjava/src/optimization/examples/x2y2WithConstraints.java b/gi/posterior-regularisation/prjava/src/optimization/examples/x2y2WithConstraints.java
new file mode 100644
index 00000000..391775b7
--- /dev/null
+++ b/gi/posterior-regularisation/prjava/src/optimization/examples/x2y2WithConstraints.java
@@ -0,0 +1,127 @@
+package optimization.examples;
+
+
+import optimization.gradientBasedMethods.ProjectedGradientDescent;
+import optimization.gradientBasedMethods.ProjectedObjective;
+import optimization.gradientBasedMethods.stats.OptimizerStats;
+import optimization.linesearch.ArmijoLineSearchMinimizationAlongProjectionArc;
+import optimization.linesearch.InterpolationPickFirstStep;
+import optimization.linesearch.LineSearchMethod;
+import optimization.projections.BoundsProjection;
+import optimization.projections.Projection;
+import optimization.projections.SimplexProjection;
+import optimization.stopCriteria.CompositeStopingCriteria;
+import optimization.stopCriteria.GradientL2Norm;
+import optimization.stopCriteria.ProjectedGradientL2Norm;
+import optimization.stopCriteria.StopingCriteria;
+import optimization.stopCriteria.ValueDifference;
+
+
+/**
+ * @author javg
+ * 
+ * 
+ *ax2+ b(y2 -displacement)
+ */
+public class x2y2WithConstraints extends ProjectedObjective{
+
+
+	double a, b;
+	double dx;
+	double dy;
+	Projection projection;
+	
+	
+	public x2y2WithConstraints(double a, double b, double[] params, double dx, double dy, Projection proj){
+		//projection = new BoundsProjection(0.2,Double.MAX_VALUE);
+		super();
+		projection = proj;	
+		this.a = a;
+		this.b = b;
+		this.dx = dx;
+		this.dy = dy;
+		setInitialParameters(params);
+		System.out.println("Function " +a+"(x-"+dx+")^2 + "+b+"(y-"+dy+")^2");
+		System.out.println("Gradient " +(2*a)+"(x-"+dx+") ; "+(b*2)+"(y-"+dy+")");
+		printParameters();
+		projection.project(parameters);
+		printParameters();
+		gradient = new double[2];
+	}
+	
+	public double getValue() {
+		functionCalls++;
+		return a*(parameters[0]-dx)*(parameters[0]-dx)+b*((parameters[1]-dy)*(parameters[1]-dy));
+	}
+
+	public double[] getGradient() {
+		if(gradient == null){
+			gradient = new double[2];
+		}
+		gradientCalls++;
+		gradient[0]=2*a*(parameters[0]-dx);
+		gradient[1]=2*b*(parameters[1]-dy);
+		return gradient;
+	}
+	
+	
+	public double[] projectPoint(double[] point) {
+		double[] newPoint = point.clone();
+		projection.project(newPoint);
+		return newPoint;
+	}	
+	
+	public void optimizeWithProjectedGradientDescent(LineSearchMethod ls, OptimizerStats stats, x2y2WithConstraints o){
+		ProjectedGradientDescent optimizer = new ProjectedGradientDescent(ls);
+		StopingCriteria stopGrad = new ProjectedGradientL2Norm(0.001);
+		StopingCriteria stopValue = new ValueDifference(0.001);
+		CompositeStopingCriteria compositeStop = new CompositeStopingCriteria();
+		compositeStop.add(stopGrad);
+		compositeStop.add(stopValue);
+		
+		optimizer.setMaxIterations(5);
+		boolean succed = optimizer.optimize(o,stats,compositeStop);
+		System.out.println("Ended optimzation Projected 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 String toString(){
+		
+		return "P1: " + parameters[0] + " P2: " + parameters[1] + " value " + getValue() + " grad (" + getGradient()[0] + ":" + getGradient()[1]+")";
+	}
+	
+	public static void main(String[] args) {
+		double a = 1;
+		double b=1;
+		double x0 = 0;
+		double y0  =1;
+		double dx = 0.5;
+		double dy = 0.5	;
+		double [] parameters = new double[2];
+		parameters[0] = x0;
+		parameters[1] = y0;
+		x2y2WithConstraints o = new x2y2WithConstraints(a,b,parameters,dx,dy, new SimplexProjection(0.5));
+		System.out.println("Starting optimization " + " x0 " + o.parameters[0]+ " x1 " + o.parameters[1] + " a " + a + " b "+b );
+		o.setDebugLevel(4);
+		
+		LineSearchMethod ls = new ArmijoLineSearchMinimizationAlongProjectionArc(new InterpolationPickFirstStep(1));
+		
+		OptimizerStats stats = new OptimizerStats();
+		o.optimizeWithProjectedGradientDescent(ls, stats, o);
+		
+//		o = new x2y2WithConstraints(a,b,x0,y0,dx,dy);
+//		stats = new OptimizerStats();
+//		o.optimizeWithSpectralProjectedGradientDescent(stats, o);
+	}
+	
+	
+	
+	
+}