fi.smaa.libror.MaximalVectorComputation.java Source code

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Here is the source code for fi.smaa.libror.MaximalVectorComputation.java

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/*
 * This file is part of libror.
 * libror is distributed from http://smaa.fi/libror
 * Copyright (C) 2011-15 Tommi Tervonen.
 *
 * This program 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.
 *
 * This program 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 this program.  If not, see <http://www.gnu.org/licenses/>.
 */

package fi.smaa.libror;

import java.util.Iterator;
import java.util.LinkedList;

import org.apache.commons.math.linear.Array2DRowRealMatrix;
import org.apache.commons.math.linear.RealMatrix;
import org.apache.commons.math.linear.RealVector;

/**
 * Implements Maximal Vector Computation
 *
 * @author Tommi Tervonen <tommi@smaa.fi>
 */
public class MaximalVectorComputation {

    /**
     * Implements the Best algorithm as described in Godfrey & al., VLDB Journal, 2007.
     * 
     * @param mat The matrix of values (each row = 1 vector of input)
     * 
     * @return Matrix containing rows from the input s.t. none are dominated
     */
    public static RealMatrix computeBEST(RealMatrix mat) {
        LinkedList<RealVector> list = matrixToListOfRows(mat);
        LinkedList<RealVector> results = new LinkedList<RealVector>();

        while (list.size() > 0) {
            Iterator<RealVector> iter = list.iterator();
            RealVector b = iter.next(); // Get the first
            iter.remove();
            while (iter.hasNext()) { // Find a max
                RealVector t = iter.next();
                if (dominates(b, t)) {
                    iter.remove();
                } else if (dominates(t, b)) {
                    iter.remove();
                    b = t;
                }
            }
            results.add(b);
            iter = list.iterator();
            while (iter.hasNext()) { // Clean up
                RealVector t = iter.next();
                if (dominates(b, t)) {
                    iter.remove();
                }
            }
        }

        return listOfRowsToMatrix(results);
    }

    /**
     * Implements the Best algorithm as described in Godfrey & al., VLDB Journal, 2007.
     * 
     * Returns indices of the rows from the original matrix.
     * 
     * @param mat The matrix of values (each row = 1 vector of input)
     * 
     * @return Matrix containing rows from the input s.t. none are dominated
     */
    public static int[] computeBESTindices(RealMatrix mat) {
        LinkedList<Integer> list = matrixToListOfIndices(mat);
        LinkedList<Integer> results = new LinkedList<Integer>();

        while (list.size() > 0) {
            Iterator<Integer> iter = list.iterator();
            Integer b = iter.next(); // Get the first
            iter.remove();
            while (iter.hasNext()) { // Find a max
                Integer t = iter.next();
                if (dominates(mat.getRowVector(b), mat.getRowVector(t))) {
                    iter.remove();
                } else if (dominates(mat.getRowVector(t), mat.getRowVector(b))) {
                    iter.remove();
                    b = t;
                }
            }
            results.add(b);
            iter = list.iterator();
            while (iter.hasNext()) { // Clean up
                Integer t = iter.next();
                if (dominates(mat.getRowVector(b), mat.getRowVector(t))) {
                    iter.remove();
                }
            }
        }

        return listOfIntegersToIntArray(results);
    }

    private static int[] listOfIntegersToIntArray(LinkedList<Integer> results) {
        int[] res = new int[results.size()];
        int index = 0;
        for (Integer in : results) {
            res[index] = in;
            index++;
        }
        return res;
    }

    private static LinkedList<Integer> matrixToListOfIndices(RealMatrix mat) {
        LinkedList<Integer> list = new LinkedList<Integer>();
        for (int i = 0; i < mat.getRowDimension(); i++) {
            list.add(i);
        }
        return list;
    }

    private static RealMatrix listOfRowsToMatrix(LinkedList<RealVector> results) {
        RealMatrix res = new Array2DRowRealMatrix(results.size(), results.getFirst().getDimension());

        for (int i = 0; i < results.size(); i++) {
            res.setRowVector(i, results.get(i));
        }
        return res;
    }

    /**
     * Checks whether v1 dominates v2.
     * 
     * @param v1
     * @param v2
     * @return true, if v1 \succ v2, false otherwise
     */
    public static boolean dominates(RealVector v1, RealVector v2) {
        assert (v1.getDimension() == v2.getDimension());

        boolean largerFound = false;

        for (int i = 0; i < v1.getDimension(); i++) {
            if (v1.getEntry(i) > v2.getEntry(i)) {
                largerFound = true;
            } else if (v1.getEntry(i) < v2.getEntry(i)) {
                return false;
            }
        }
        return largerFound;
    }

    private static LinkedList<RealVector> matrixToListOfRows(RealMatrix mat) {
        LinkedList<RealVector> list = new LinkedList<RealVector>();
        for (int i = 0; i < mat.getRowDimension(); i++) {
            list.add(mat.getRowVector(i));
        }
        return list;
    }
}