/*
 * Created on Aug 2, 2005
 *
 */
package aima.learning.inductive;

import java.util.ArrayList;
import java.util.Hashtable;
import java.util.List;

import aima.learning.framework.Example;

public class DecisionList {
	private String positive, negative;

	private List<DLTest> tests;
	private Hashtable<DLTest,String> testOutcomes;

	public DecisionList(String positive,String negative) {
		this.positive = positive;
		this.negative = negative;
		this.tests = new ArrayList<DLTest>();
		testOutcomes =  new Hashtable<DLTest,String>();
	}

	public String predict(Example example) {
		if (tests.size() == 0) {
			return negative;
		}
		for (DLTest test :tests){
			if (test.matches(example)){
				return testOutcomes.get(test);
			}
		}
		return negative;
	}

	public void add(DLTest test,String outcome) {
		tests.add(test);
		testOutcomes.put(test,outcome);
	}

	public DecisionList mergeWith(DecisionList dlist2) {
		DecisionList merged = new DecisionList(positive,negative);
		for (DLTest test:tests){
			merged.add(test,testOutcomes.get(test));
		}
		for (DLTest test:dlist2.tests){
			merged.add(test,dlist2.testOutcomes.get(test));
		}
		return merged;
	}
	public String toString(){
		StringBuffer buf = new StringBuffer();
		for (DLTest test:tests){
			buf.append(test.toString()+" => "+testOutcomes.get(test)+" ELSE \n");
		}
		buf.append("END");
		return buf.toString();
	}

}