/**
 * 
 */
package agents;

import java.util.ArrayList;

import master.Product;

/**
 * @author mbilgic
 *
 */
public class AgentPhase25405 extends RationalBaselineAgent {
	ArrayList<ArrayList<String>> corpus;


	/**
	 * @param id
	 */
	public AgentPhase25405(String id) {
		super(id);
	}

	/* (non-Javadoc)
	 * @see agents.Agent#learn(java.util.ArrayList)
	 */
	@Override
	public void learn(ArrayList<ArrayList<String>> trainingInstances) {
		corpus = trainingInstances;
	}

	/* (non-Javadoc)
	 * @see agents.Agent#computeProbOfGood(java.util.ArrayList)
	 */
	@Override
	public double computeProbOfGood(ArrayList<String> prodFeatures) {
		double probGood = getProbClass("G");
		//System.out.println("---------------------");
		//System.out.println("Prob of good: "+probGood);
		int i =0;
		for(String j:prodFeatures){
			//System.out.println("Cond Prob of : "+getCondProb(i,j,"G"));
			probGood = probGood*getCondProb(i,j,"G");
			i++;
		}
		double probBad = getProbClass("B");
		//System.out.println("+++++++++++++++++++++");
		//System.out.println("Prob of bad: "+probBad);
		i =0;
		for(String j:prodFeatures){
			//System.out.println("Cond Prob of : "+getCondProb(i,j,"B"));
			probBad = probBad*getCondProb(i,j,"B");
			i++;
		}
		////System.out.println("Prob featlist: "+getFeatListProb(prodFeatures));
		//probGood  = probGood/getFeatListProb(prodFeatures);
		//System.out.println("Prob: "+(probGood)/(probGood+probBad));
		//System.out.println("*********************");
		return probGood/(probGood+probBad);
	}
	public double getProbClass(String in){
		int hits = 0;
		for(ArrayList<String> i:corpus){
			if(i.get(i.size()-1).equals(in)){
				++hits;
			}
		}
		return ((double)hits+1)/(2+corpus.size());
	}
	public double getCondProb(int featureIndex,String feature, String in){
		int classHits = 2;
		int bothHits = 1;
		for(ArrayList<String> i: corpus){
			if(i.get(i.size()-1).equals(in)){
				++classHits;
				if(i.get(featureIndex).equals(feature)){
					++bothHits;
				}
			}
		}
		return ((double)bothHits)/classHits;
	}
}