New context constraints.

git-svn-id: https://ws10smt.googlecode.com/svn/trunk@190 ec762483-ff6d-05da-a07a-a48fb63a330f

1 files changed, 53 insertions, 67 deletions

diff --git a/gi/posterior-regularisation/prjava/src/phrase/PhraseObjective.java b/gi/posterior-regularisation/prjava/src/phrase/PhraseObjective.java
index 0fdc169b..015ef106 100644
--- a/gi/posterior-regularisation/prjava/src/phrase/PhraseObjective.java
+++ b/gi/posterior-regularisation/prjava/src/phrase/PhraseObjective.java
@@ -2,6 +2,7 @@ package phrase;
 

 import java.io.PrintStream;

 import java.util.Arrays;

+import java.util.List;

 

 import optimization.gradientBasedMethods.ProjectedGradientDescent;

 import optimization.gradientBasedMethods.ProjectedObjective;

@@ -17,11 +18,12 @@ import optimization.stopCriteria.StopingCriteria;
 import optimization.stopCriteria.ValueDifference;

 import optimization.util.MathUtils;

 

-public class PhraseObjective extends ProjectedObjective{

-

-	private static final double GRAD_DIFF = 0.00002;

-	public static double INIT_STEP_SIZE = 10;

-	public static double VAL_DIFF = 0.000001; // FIXME needs to be tuned

+public class PhraseObjective extends ProjectedObjective

+{

+	static final double GRAD_DIFF = 0.00002;

+	static double INIT_STEP_SIZE = 10;

+	static double VAL_DIFF = 1e-6; // FIXME needs to be tuned

+	static int ITERATIONS = 100;

 	//private double c1=0.0001; // wolf stuff

 	//private double c2=0.9;

 	private static double lambda[][];

@@ -46,7 +48,7 @@ public class PhraseObjective extends ProjectedObjective{
 	 * q[edge][tag] propto p[edge][tag]*exp(-lambda)

 	 */

 	private double q[][];

-	private int data[][];

+	private List<Corpus.Edge> data;

 	

 	/**@brief log likelihood of the associated phrase

 	 * 

@@ -66,14 +68,14 @@ public class PhraseObjective extends ProjectedObjective{
 	public PhraseObjective(PhraseCluster cluster, int phraseIdx){

 		phrase=phraseIdx;

 		c=cluster;

-		data=c.c.data[phrase];

-		n_param=data.length*c.K;

+		data=c.c.getEdgesForPhrase(phrase);

+		n_param=data.size()*c.K;

 		

-		if( lambda==null){

-			lambda=new double[c.c.data.length][];

+		if (lambda==null){

+			lambda=new double[c.c.getNumPhrases()][];

 		}

 		

-		if(lambda[phrase]==null){

+		if (lambda[phrase]==null){

 			lambda[phrase]=new double[n_param];

 		}

 		

@@ -81,22 +83,17 @@ public class PhraseObjective extends ProjectedObjective{
 		newPoint  = new double[n_param];

 		gradient = new double[n_param];

 		initP();

-		projection=new SimplexProjection(c.scale);

-		q=new double [data.length][c.K];

+		projection=new SimplexProjection(c.scalePT);

+		q=new double [data.size()][c.K];

 

 		setParameters(parameters);

 	}

 

 	private void initP(){

-		int countIdx=data[0].length-1;

-		

-		p=new double[data.length][];

-		for(int edge=0;edge<data.length;edge++){

-			p[edge]=c.posterior(phrase,data[edge]);

-		}

-		for(int edge=0;edge<data.length;edge++){

-			llh+=Math.log

-				(data[edge][countIdx]*arr.F.l1norm(p[edge]));

+		p=new double[data.size()][];

+		for(int edge=0;edge<data.size();edge++){

+			p[edge]=c.posterior(data.get(edge));

+			llh += data.get(edge).getCount() * Math.log(arr.F.l1norm(p[edge])); // Was bug here - count inside log!

 			arr.F.l1normalize(p[edge]);

 		}

 	}

@@ -110,37 +107,36 @@ public class PhraseObjective extends ProjectedObjective{
 	private void updateFunction(){

 		updateCalls++;

 		loglikelihood=0;

-		int countIdx=data[0].length-1;

+

 		for(int tag=0;tag<c.K;tag++){

-			for(int edge=0;edge<data.length;edge++){

+			for(int edge=0;edge<data.size();edge++){

 				q[edge][tag]=p[edge][tag]*

-					Math.exp(-parameters[tag*data.length+edge]/data[edge][countIdx]);

+					Math.exp(-parameters[tag*data.size()+edge]/data.get(edge).getCount());

 			}

 		}

 	

-		for(int edge=0;edge<data.length;edge++){

-			loglikelihood+=data[edge][countIdx] * Math.log(arr.F.l1norm(q[edge]));

+		for(int edge=0;edge<data.size();edge++){

+			loglikelihood+=data.get(edge).getCount() * Math.log(arr.F.l1norm(q[edge]));

 			arr.F.l1normalize(q[edge]);

 		}

 		

 		for(int tag=0;tag<c.K;tag++){

-			for(int edge=0;edge<data.length;edge++){

-				gradient[tag*data.length+edge]=-q[edge][tag];

+			for(int edge=0;edge<data.size();edge++){

+				gradient[tag*data.size()+edge]=-q[edge][tag];

 			}

 		}

 	}

 	

 	@Override

-	// TODO Auto-generated method stub

 	public double[] projectPoint(double[] point) {

-		double toProject[]=new double[data.length];

+		double toProject[]=new double[data.size()];

 		for(int tag=0;tag<c.K;tag++){

-			for(int edge=0;edge<data.length;edge++){

-				toProject[edge]=point[tag*data.length+edge];

+			for(int edge=0;edge<data.size();edge++){

+				toProject[edge]=point[tag*data.size()+edge];

 			}

 			projection.project(toProject);

-			for(int edge=0;edge<data.length;edge++){

-				newPoint[tag*data.length+edge]=toProject[edge];

+			for(int edge=0;edge<data.size();edge++){

+				newPoint[tag*data.size()+edge]=toProject[edge];

 			}

 		}

 		return newPoint;

@@ -148,22 +144,19 @@ public class PhraseObjective extends ProjectedObjective{
 

 	@Override

 	public double[] getGradient() {

-		// TODO Auto-generated method stub

 		gradientCalls++;

 		return gradient;

 	}

 

 	@Override

 	public double getValue() {

-		// TODO Auto-generated method stub

 		functionCalls++;

 		return loglikelihood;

 	}

 

 	@Override

 	public String toString() {

-		// TODO Auto-generated method stub

-		return "";

+		return "No need for pointless toString";

 	}

 

 	public double [][]posterior(){

@@ -185,7 +178,7 @@ public class PhraseObjective extends ProjectedObjective{
 		CompositeStopingCriteria compositeStop = new CompositeStopingCriteria();

 		compositeStop.add(stopGrad);

 		compositeStop.add(stopValue);

-		optimizer.setMaxIterations(100);

+		optimizer.setMaxIterations(ITERATIONS);

 		updateFunction();

 		boolean succed = optimizer.optimize(this,stats,compositeStop);

 //		System.out.println("Ended optimzation Projected Gradient Descent\n" + stats.prettyPrint(1));

@@ -197,45 +190,38 @@ public class PhraseObjective extends ProjectedObjective{
 		lambda[phrase]=parameters;

 		//	ps.println(Arrays.toString(parameters));

 		

-		//	for(int edge=0;edge<data.length;edge++){

+		//	for(int edge=0;edge<data.getSize();edge++){

 		//	ps.println(Arrays.toString(q[edge]));

 		//	}

 		

 	}

 	

-	/**

-	 * L - KL(q||p) -

-	 * 	 scale * \sum_{tag,phrase} max_i P(tag|i th occurrence of phrase)

-	 * @return

-	 */

-	public double primal()

+	public double KL_divergence()

+	{

+		return -loglikelihood + MathUtils.dotProduct(parameters, gradient);

+	}

+	

+	public double loglikelihood()

+	{

+		return llh;

+	}

+	

+	public double l1lmax()

 	{

-		

-		double l=llh;

-		

-//		ps.print("Phrase "+phrase+": "+l);

-		double kl=-loglikelihood

-			+MathUtils.dotProduct(parameters, gradient);

-//		ps.print(", "+kl);

-		//System.out.println("llh " + llh);

-		//System.out.println("kl " + kl);

-		

-

-		l=l-kl;

 		double sum=0;

 		for(int tag=0;tag<c.K;tag++){

 			double max=0;

-			for(int edge=0;edge<data.length;edge++){

-				if(q[edge][tag]>max){

+			for(int edge=0;edge<data.size();edge++){

+				if(q[edge][tag]>max)

 					max=q[edge][tag];

-				}

 			}

 			sum+=max;

 		}

-		//System.out.println("l1lmax " + sum);

-//		ps.println(", "+sum);

-		l=l-c.scale*sum;

-		return l;

+		return sum;

+	}

+

+	public double primal()

+	{

+		return loglikelihood() - KL_divergence() - c.scalePT * l1lmax();	

 	}

-	

 }