/**
 * 
 */
package agents;

import java.util.ArrayList;

import master.Product;

/**
 * @author mbilgic
 *
 */
public class AgentPhase25405 extends RationalBaselineAgent {
	
	//This agent learns only the market condition
	double marketCondition = 0.5;

	/**
	 * @param id
	 */
	public AgentPhase25405(String id) {
		super(id);
	}
	public class goodVtotal{
		int good = 0;
		int total = 0;
		public goodVtotal(boolean first){
			incrementer(first);
		}
		public goodVtotal(){
		}
		public int getGood(){
			return good;
		}
		public int getTotal(){
			return total;
		}
		public void incrementer(boolean in){
			good += in?1:0;
			++total;
		}
		public String toString(){
			return good+ " / " + total;
		}
	}
	goodVtotal[] typearray = null;

	/* (non-Javadoc)
	 * @see agents.Agent#learn(java.util.ArrayList)
	 */
	@Override
	public void learn(ArrayList<ArrayList<String>> trainingInstances) {
		if (typearray == null){
			typearray = new goodVtotal[1<<trainingInstances.get(0).size()];
			for(int index = 0; index < typearray.length; ++index){
				typearray[index] = new goodVtotal();
			}
		}
		for(ArrayList<String> j : trainingInstances){
			typearray[indexShifter(j)].incrementer(j.get(j.size()-1).equals("G")?true:false);
		}
		
	}
	public int indexShifter(ArrayList<String> in){
			if(in.get(in.size()-1).equals("G") || in.get(in.size()-1).equals("B")){
				in = (ArrayList<String>)in.clone();
				in.remove(in.size()-1);
			}
			int out = 0;
			for(int spot = 0; spot < in.size(); ++spot){
				if(in.get(spot).equals("T")){
					out += 1<<(in.size()-1)-spot;
				}
			}
			return out;
	}

	/* (non-Javadoc)
	 * @see agents.Agent#computeProbOfGood(java.util.ArrayList)
	 */
	@Override
	public double computeProbOfGood(ArrayList<String> prodFeatures) {
		return typearray[indexShifter(prodFeatures)].getGood()/(double)typearray[indexShifter(prodFeatures)].getTotal();
	}
}