// Path: src/edu/antonym/prototype/MetricEvaluator.java
// public interface MetricEvaluator {
// 	public double score(WordMetric metric) throws IOException;
// }
// 
// Path: src/edu/antonym/prototype/Vocabulary.java
// public interface Vocabulary {
// 	public int size();
// 	public int OOVindex();
// 	public String lookupIndex(int index);
// 	public int lookupWord(String word);
// 	public int getVocabSize();
// }
// 
// Path: src/edu/antonym/prototype/WordMetric.java
// public interface WordMetric {
// 	public Vocabulary getVocab();
// 
// 	public double similarity(int word1, int word2);
// }


import java.io.IOException;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.Random;
import edu.antonym.prototype.MetricEvaluator;
import edu.antonym.prototype.Vocabulary;
import edu.antonym.prototype.WordMetric;
package edu.antonym.test;



public class TestCaseMCMC implements MetricEvaluator {

	/*
	 * important notes: adjust n or gamma if you want the algorithm to go faster
	 * 
	 * Example usage:
	 * 	TestCaseMCMC n = new TestCaseMCMC(input);
	 *	ArrayList<ArrayList<String>> r = n.get2cluster(metric);
	 *  // print out result cluster 1, cluster 2, word not found
	 *	for(int i=0;i<r.size();i++){
	 *		for(int j=0;j<r.get(i).size();j++){
	 *			System.out.print(r.get(i).get(j)+" ");
	 *		}
	 *		System.out.println();
	 *	}
	 */
	public ArrayList<String> wordsense = new ArrayList<String>();
	
	public TestCaseMCMC(ArrayList<String> input){
		wordsense = new ArrayList<String>(input);
	}
	
	@Override
	public double score(WordMetric metric) throws IOException {
		// TODO Auto-generated method stub
		return 0;
	}

	public ArrayList<ArrayList<String>> get2cluster(WordMetric metric) throws IOException{
		
// Path: src/edu/antonym/prototype/MetricEvaluator.java
// public interface MetricEvaluator {
// 	public double score(WordMetric metric) throws IOException;
// }
// 
// Path: src/edu/antonym/prototype/Vocabulary.java
// public interface Vocabulary {
// 	public int size();
// 	public int OOVindex();
// 	public String lookupIndex(int index);
// 	public int lookupWord(String word);
// 	public int getVocabSize();
// }
// 
// Path: src/edu/antonym/prototype/WordMetric.java
// public interface WordMetric {
// 	public Vocabulary getVocab();
// 
// 	public double similarity(int word1, int word2);
// }


// Path: src/edu/antonym/test/TestCaseMCMC.java
import java.io.IOException;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.Random;
import edu.antonym.prototype.MetricEvaluator;
import edu.antonym.prototype.Vocabulary;
import edu.antonym.prototype.WordMetric;

package edu.antonym.test;



public class TestCaseMCMC implements MetricEvaluator {

	/*
	 * important notes: adjust n or gamma if you want the algorithm to go faster
	 * 
	 * Example usage:
	 * 	TestCaseMCMC n = new TestCaseMCMC(input);
	 *	ArrayList<ArrayList<String>> r = n.get2cluster(metric);
	 *  // print out result cluster 1, cluster 2, word not found
	 *	for(int i=0;i<r.size();i++){
	 *		for(int j=0;j<r.get(i).size();j++){
	 *			System.out.print(r.get(i).get(j)+" ");
	 *		}
	 *		System.out.println();
	 *	}
	 */
	public ArrayList<String> wordsense = new ArrayList<String>();
	
	public TestCaseMCMC(ArrayList<String> input){
		wordsense = new ArrayList<String>(input);
	}
	
	@Override
	public double score(WordMetric metric) throws IOException {
		// TODO Auto-generated method stub
		return 0;
	}

	public ArrayList<ArrayList<String>> get2cluster(WordMetric metric) throws IOException{
		
		Vocabulary vocab = metric.getVocab();