comparison src/samer/models/SmoothGeneralisedExponential.java @ 0:bf79fb79ee13

Initial Mercurial check in.

+package samer.models;
+
+import samer.maths.*;
+import samer.maths.opt.*;
+import samer.tools.*;
+import samer.core.*;
+import samer.core.types.*;
+import java.util.*;
+
+/**
+	Non-adaptive generalised exponential factorial prior: the pointy
+	bit of the usual GeneralisedExponential has been smoothed out
+	by blending with a quadratic.
+ */
+
+public class SmoothGeneralisedExponential extends NamedTask implements Model, Observer {
+	Vec		input;
+	VVector	alpha, e, grad;
+	int			N;
+	VDouble	E;
+	double[]	x, g, e0, _e, a, eps;
+	double	last_eps;
+
+	public SmoothGeneralisedExponential(Vec x) { this(x.size()); setInput(x); }
+	public SmoothGeneralisedExponential(int n)  {
+		super("genExp");
+		Shell.push(node);
+		N=n;
+		E=new VDouble("E");
+		e=new VVector("e",N);
+		grad=new VVector("phi",N);
+		alpha=new VVector("alpha",N);
+		eps=new double[N];
+		alpha.addSaver();
+		Shell.pop();
+
+		alpha.addObserver(this);
+		g=grad.array(); // new double[N];
+		e0=new double[N];
+		a=alpha.array();
+		_e=e.array();
+		
+		Mathx.setAll(a,1.0); 
+		setEps(0.1);
+	}
+
+	public void update(Observable obs, Object arg) {
+		setEps(last_eps);
+	}
+	public void setEps(double e) {
+		last_eps=e;
+		for (int i=0; i<N; i++) { eps[i]=Math.pow(e,2-a[i]); }
+	}
+	public void setInput(Vec in) { input=in; x=input.array(); }
+	public int getSize() { return N; }
+	public void dispose() {
+		alpha.dispose();
+		grad.dispose();
+		E.dispose();
+	}
+
+	public VVector	getEnergyVector() { return e; }
+	public VDouble	getEnergySignal() { return E; }
+	public double	getEnergy() { return E.value; }
+	public double [] getGradient() { return g; 	}
+	public VVector  getAlpha() { return alpha; }
+	
+	public void run() { compute(); }
+	public void infer() {}
+	public void compute() {
+		// compute log likelihood
+
+		for (int i=0; i<N; i++) {
+			double t=Math.abs(x[i]);
+			_e[i] = t*t/(Math.pow(t,2-a[i]) + eps[i]);
+		}
+
+		// compute gradient g_i = dL/dx_i
+		for (int i=0; i<N; i++) {
+			if (x[i]==0) g[i]=0;
+			else g[i] = a[i]*(_e[i]/x[i]);
+		}
+
+		e.changed();
+		grad.changed();
+		E.set(Mathx.sum(_e));
+	}
+
+	public Functionx functionx() {
+		return new Functionx() {
+			double [] __e=new double[N];
+			public void dispose() {}
+			public void evaluate(Datum P) { P.f=evaluate(P.x,P.g); }
+			public double evaluate(double [] x, double [] g) {
+				for (int i=0; i<N; i++) {
+					if (x[i]==0) { g[i]=0; __e[i]=0; }
+					else {
+						double t=Math.abs(x[i]);
+						__e[i] = t*t/(Math.pow(t,2-a[i]) + eps[i]);
+						g[i] = a[i]*(__e[i]/x[i]);
+					}
+				}
+				return  Mathx.sum(__e); // +L0;
+			}
+		};
+	}
+}