From 925087356b853e2099c1b60d8b757d7aa02121a9 Mon Sep 17 00:00:00 2001
From: Chris Dyer <cdyer@cab.ark.cs.cmu.edu>
Date: Tue, 2 Oct 2012 00:19:43 -0400
Subject: cdec cleanup, remove bayesian stuff, parsing stuff

---
 .../prjava/src/test/CorpusTest.java                |  60 ----------
 .../prjava/src/test/HMMModelStats.java             | 105 -----------------
 .../prjava/src/test/IntDoublePair.java             |  23 ----
 .../prjava/src/test/X2y2WithConstraints.java       | 131 ---------------------
 4 files changed, 319 deletions(-)
 delete mode 100644 gi/posterior-regularisation/prjava/src/test/CorpusTest.java
 delete mode 100644 gi/posterior-regularisation/prjava/src/test/HMMModelStats.java
 delete mode 100644 gi/posterior-regularisation/prjava/src/test/IntDoublePair.java
 delete mode 100644 gi/posterior-regularisation/prjava/src/test/X2y2WithConstraints.java

(limited to 'gi/posterior-regularisation/prjava/src/test')

diff --git a/gi/posterior-regularisation/prjava/src/test/CorpusTest.java b/gi/posterior-regularisation/prjava/src/test/CorpusTest.java
deleted file mode 100644
index b4c3041f..00000000
--- a/gi/posterior-regularisation/prjava/src/test/CorpusTest.java
+++ /dev/null
@@ -1,60 +0,0 @@
-package test;
-
-import java.util.Arrays;
-import java.util.HashMap;
-
-import data.Corpus;
-import hmm.POS;
-
-public class CorpusTest {
-
-	public static void main(String[] args) {
-		Corpus c=new Corpus(POS.trainFilename);
-
-		
-		int idx=30;
-		
-		
-		HashMap<String, Integer>vocab=
-			(HashMap<String, Integer>) io.SerializedObjects.readSerializedObject(Corpus.alphaFilename);
-		
-		HashMap<String, Integer>tagVocab=
-			(HashMap<String, Integer>) io.SerializedObjects.readSerializedObject(Corpus.tagalphaFilename);
-		
-		
-		String [] dict=new String [vocab.size()+1];
-		for(String key:vocab.keySet()){
-			dict[vocab.get(key)]=key;
-		}
-		dict[dict.length-1]=Corpus.UNK_TOK;
-		
-		String [] tagdict=new String [tagVocab.size()+1];
-		for(String key:tagVocab.keySet()){
-			tagdict[tagVocab.get(key)]=key;
-		}
-		tagdict[tagdict.length-1]=Corpus.UNK_TOK;
-		
-		String[] sent=c.get(idx);
-		int []data=c.getInt(idx);
-		
-		
-		String []roundtrip=new String [sent.length];
-		for(int i=0;i<sent.length;i++){
-			roundtrip[i]=dict[data[i]];
-		}
-		System.out.println(Arrays.toString(sent));
-		System.out.println(Arrays.toString(roundtrip));
-		
-		sent=c.tag.get(idx);
-		data=c.tagData.get(idx);
-		
-		
-		roundtrip=new String [sent.length];
-		for(int i=0;i<sent.length;i++){
-			roundtrip[i]=tagdict[data[i]];
-		}
-		System.out.println(Arrays.toString(sent));
-		System.out.println(Arrays.toString(roundtrip));
-	}
-
-}
diff --git a/gi/posterior-regularisation/prjava/src/test/HMMModelStats.java b/gi/posterior-regularisation/prjava/src/test/HMMModelStats.java
deleted file mode 100644
index d54525c8..00000000
--- a/gi/posterior-regularisation/prjava/src/test/HMMModelStats.java
+++ /dev/null
@@ -1,105 +0,0 @@
-package test;
-
-import hmm.HMM;
-import hmm.POS;
-
-import java.io.File;
-import java.io.FileNotFoundException;
-import java.io.IOException;
-import java.io.PrintStream;
-import java.util.ArrayList;
-import java.util.Collections;
-import java.util.HashMap;
-
-import data.Corpus;
-
-public class HMMModelStats {
-
-	public static String modelFilename="../posdata/posModel.out";
-	public static String alphaFilename="../posdata/corpus.alphabet";
-	public static String statsFilename="../posdata/model.stats";
-
-	public static final int NUM_WORD=50;
-	
-	public static String testFilename="../posdata/en_test.conll";
-	
-	public static double [][]maxwt;
-	
-	public static void main(String[] args) {
-		HashMap<String, Integer>vocab=
-			(HashMap<String, Integer>) io.SerializedObjects.readSerializedObject(alphaFilename);
-		
-		Corpus test=new Corpus(testFilename,vocab);
-		
-		String [] dict=new String [vocab.size()+1];
-		for(String key:vocab.keySet()){
-			dict[vocab.get(key)]=key;
-		}
-		dict[dict.length-1]=Corpus.UNK_TOK;
-		
-		HMM hmm=new HMM();
-		hmm.readModel(modelFilename);
-
-		
-		
-		PrintStream ps = null;
-		try {
-			ps = io.FileUtil.printstream(new File(statsFilename));
-		} catch (IOException e) {
-			e.printStackTrace();
-			System.exit(1);
-		}
-		
-		double [][] emit=hmm.getEmitProb();
-		for(int i=0;i<emit.length;i++){
-			ArrayList<IntDoublePair>l=new ArrayList<IntDoublePair>();
-			for(int j=0;j<emit[i].length;j++){
-				l.add(new IntDoublePair(j,emit[i][j]));
-			}
-			Collections.sort(l);
-			ps.println(i);
-			for(int j=0;j<NUM_WORD;j++){
-				if(j>=dict.length){
-					break;
-				}
-				ps.print(dict[l.get(j).idx]+"\t");
-				if((1+j)%10==0){
-					ps.println();
-				}
-			}
-			ps.println("\n");
-		}
-		
-		checkMaxwt(hmm,ps,test.getAllData());
-		
-		int terminalSym=vocab.get(Corpus .END_SYM);
-		//sample 10 sentences
-		for(int i=0;i<10;i++){
-			int []sent=hmm.sample(terminalSym);
-			for(int j=0;j<sent.length;j++){
-				ps.print(dict[sent[j]]+"\t");
-			}
-			ps.println();
-		}
-		
-		ps.close();
-		
-	}
-	
-	public static void checkMaxwt(HMM hmm,PrintStream ps,int [][]data){
-		double [][]emit=hmm.getEmitProb();
-		maxwt=new double[emit.length][emit[0].length];
-		
-		hmm.computeMaxwt(maxwt,data);
-		double sum=0;
-		for(int i=0;i<maxwt.length;i++){
-			for(int j=0;j<maxwt.length;j++){
-				sum+=maxwt[i][j];
-			}
-		}
-		
-		ps.println("max w t P(w_i|t): "+sum);
-		
-	}
-	
-}
diff --git a/gi/posterior-regularisation/prjava/src/test/IntDoublePair.java b/gi/posterior-regularisation/prjava/src/test/IntDoublePair.java
deleted file mode 100644
index 3f9f0ad7..00000000
--- a/gi/posterior-regularisation/prjava/src/test/IntDoublePair.java
+++ /dev/null
@@ -1,23 +0,0 @@
-package test;
-
-public class IntDoublePair implements Comparable{
-	double val;
-	int idx;
-	public int compareTo(Object o){
-		if(o instanceof IntDoublePair){
-			IntDoublePair pair=(IntDoublePair)o;
-			if(pair.val>val){
-				return 1;
-			}
-			if(pair.val<val){
-				return -1;
-			}
-			return 0;
-		}
-		return -1;
-	}
-	public IntDoublePair(int i,double v){
-		val=v;
-		idx=i;
-	}
-}
diff --git a/gi/posterior-regularisation/prjava/src/test/X2y2WithConstraints.java b/gi/posterior-regularisation/prjava/src/test/X2y2WithConstraints.java
deleted file mode 100644
index 9059a59e..00000000
--- a/gi/posterior-regularisation/prjava/src/test/X2y2WithConstraints.java
+++ /dev/null
@@ -1,131 +0,0 @@
-package test;
-
-
-
-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 = 0.2	;
-		double [] parameters = new double[2];
-		parameters[0] = x0;
-		parameters[1] = y0;
-		X2y2WithConstraints o = new X2y2WithConstraints(a,b,parameters,dx,dy, 
-				new SimplexProjection(0.5)
-				//new BoundsProjection(0.0,0.4)
-		);
-		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);
-	}
-	
-	
-	
-	
-}
-- 
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