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A library that models real-world objects in Java, referred to as ComplexDataObjects. Other features: IO and preprocessing of ComplexDataObjects.

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package com.github.TKnudsen.ComplexDataObject.model.distanceMeasure.Boolean;

import java.util.List;

import com.github.TKnudsen.ComplexDataObject.model.distanceMeasure.WeightedDistanceMeasure;

/**
 * 
 * Title: WeightedMeanManhattanDistanceMeasure
 * 
 * 
 * 
 * Description:
 * 
 * 
 * 
 * Copyright: (c) 2016-2017 Juergen Bernard
 * 
 * 
 * @author Christian Ritter
 * @version 1.01
 */
public class WeightedMeanManhattanDistanceMeasure extends WeightedDistanceMeasure {

	public WeightedMeanManhattanDistanceMeasure(List weights) {
		super(weights);
	}

	public WeightedMeanManhattanDistanceMeasure(List weights, double nullValue) {
		super(weights, nullValue);
	}

	@Override
	public String getDescription() {
		return "WeightedMeanManhattanDistanceMeasure";
	}

	@Override
	public double getDistance(Boolean[] o1, Boolean[] o2) {
		// check if arrays have same length
		if (o1.length != o2.length || o1.length != getWeights().size()) {
			try {
				throw new Exception("The Arrays have different Sizes.");
			} catch (Exception e) {
				e.printStackTrace();
			}
			return Double.NaN;
		}

		double equal = 0;
		double unequal = 0;

		int length = o1.length;

		for (int i = 0; i < length; i++) {
			if (o1[i] == null || o2[i] == null)
				unequal += getNullValue() * getWeights().get(i);
			else if (o1[i].equals(o2[i]))
				equal += getWeights().get(i);
			else
				unequal += getWeights().get(i);
		}

		return unequal / (equal + unequal);
	}

	@Override
	public String getName() {
		return "WeightedMeanManhattanDistanceMeasure";
	}

}