IndexLinearizer.java

package edu.berkeley.nlp.classify;

import java.io.Serializable;

/**
 * The IndexLinearizer maintains the linearization of the two-dimensional
 * features-by-labels pair space. This is because, while we might think
 * about lambdas and derivatives as being indexed by a feature-label pair,
 * the optimization code expects one long vector for lambdas and
 * derivatives. To go from a pair featureIndex, labelIndex to a single
 * pairIndex, use getLinearIndex().
 */
public class IndexLinearizer implements Serializable {
	/**
	 * 
	 */
	private static final long serialVersionUID = 6164226851901151038L;
	int numFeatures;
	int numLabels;

	public int getNumLinearIndexes() {
		return numFeatures * numLabels;
	}

	public int getLinearIndex(int featureIndex, int labelIndex) {
		return labelIndex + featureIndex * numLabels;
	}

	public int getFeatureIndex(int linearIndex) {
		return linearIndex / numLabels;
	}

	public int getLabelIndex(int linearIndex) {
		return linearIndex % numLabels;
	}

	public IndexLinearizer(int numFeatures, int numLabels) {
		this.numFeatures = numFeatures;
		this.numLabels = numLabels;
	}
}