package mpqareader;

import java.util.*;

import se.lth.cs.nlp.nlputils.core.*;
import se.lth.cs.nlp.nlputils.ml_long.*;

public class IntensitiesSplitter extends LearningAlgorithm<IntensitiesDefinition, SparseVector, Intensities> {

	private String algName;
	//private String[] algArgs;
	private String algArgs;
	
	public IntensitiesSplitter(String algName, String algArgs) {
		this.algName = algName;
		//this.algArgs = algArgs.split("\\s+");
		this.algArgs = algArgs;
		
		System.out.println(this.algName);
		System.out.println(Arrays.asList(this.algArgs));		
    }

	private static final int[] RANGE = { BOWPolSubjSentClassifier.NONE,
		BOWPolSubjSentClassifier.LOW, BOWPolSubjSentClassifier.MEDIUM, BOWPolSubjSentClassifier.HIGH };
	
	public Classifier<SparseVector, Intensities> train(
			IntensitiesDefinition problem,
			List<Pair<SparseVector, Intensities>> trainingSet) {
		AlgorithmFactory af = new AlgorithmFactory();		
		Classifier<SparseVector, Integer>[] cls = new Classifier[3];
		for(int i = 0; i < 3; i++) {		
			EncodedMulticlassDefinition subSpec = new EncodedMulticlassDefinition(RANGE);
			LearningAlgorithm alg = af.create(algName, algArgs);
			ArrayList<Pair<SparseVector, Integer>> ts = new ArrayList();
			for(Pair<SparseVector, Intensities> p: trainingSet) {
				int subInt;
				switch(i) {
				case 0:
					subInt = p.right.pos;
					break;
				case 1:
					subInt = p.right.neu;
					break;
				case 2:
					subInt = p.right.neg;
					break;
				default:
					throw new RuntimeException("!!!");
				}
				ts.add(new Pair(p.left.copy(), subInt));
			}
			cls[i] = alg.train(subSpec, ts);
		}		
		return new SplitIntensitiesClassifier(cls);
	}

	private static class SplitIntensitiesClassifier extends Classifier<SparseVector, Intensities> {
		private static final long serialVersionUID = 0L;
		Classifier<SparseVector, Integer> poscl, neucl, negcl;
		SplitIntensitiesClassifier(Classifier<SparseVector, Integer>[] cls) {
			poscl = cls[0];
			neucl = cls[1];
			negcl = cls[2];
		}
		public Intensities classify(SparseVector sv) {
			int pos = poscl.classify(sv);
			int neu = neucl.classify(sv);
			int neg = negcl.classify(sv);
			return new Intensities(pos, neu, neg);
		}
	}
	
	
}