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/*
 * Copyright 2019 Systems Research Group, University of St Andrews:
 * 
 *
 * This file is part of the module utilities.
 *
 * utilities is free software: you can redistribute it and/or modify it under the terms of the GNU General Public
 * License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later
 * version.
 *
 * utilities is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied
 * warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
 *
 * You should have received a copy of the GNU General Public License along with utilities. If not, see
 * .
 */
package uk.ac.standrews.cs.utilities.metrics;

import uk.ac.standrews.cs.utilities.metrics.implementation.SparseProbabilityMetric;

/**
 * @author Richard Connor [email protected]
 * Implements Structural Entropic Distance
 */
public class SED extends SparseProbabilityMetric {

    private int CHAR_VAL_UPPER_BOUND = 512;

    public SED() {}

    public SED(int CHAR_VAL_UPPER_BOUND) {
        this.CHAR_VAL_UPPER_BOUND = CHAR_VAL_UPPER_BOUND;
    }

    @Override
    public String getMetricName() {
        return "SED";
    }

    @Override
    public double calculateStringDistance(String x, String y) {

        double k = doCalc(stringToSparseArray(x, CHAR_VAL_UPPER_BOUND), stringToSparseArray(y, CHAR_VAL_UPPER_BOUND));
        return Math.pow(Math.pow(2, Math.max(0, k)) - 1, 0.486); // TODO magic number
    }

    public static void main(String[] a) {
        new SED().printExamples();
    }
}