/*
* This file is part of the LIRE project: http://www.semanticmetadata.net/lire
* LIRE 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 2 of the License, or
* (at your option) any later version.
*
* LIRE 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 LIRE; if not, write to the Free Software
* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
*
* We kindly ask you to refer the any or one of the following publications in
* any publication mentioning or employing Lire:
*
* Lux Mathias, Savvas A. Chatzichristofis. Lire: Lucene Image Retrieval –
* An Extensible Java CBIR Library. In proceedings of the 16th ACM International
* Conference on Multimedia, pp. 1085-1088, Vancouver, Canada, 2008
* URL: http://doi.acm.org/10.1145/1459359.1459577
*
* Lux Mathias. Content Based Image Retrieval with LIRE. In proceedings of the
* 19th ACM International Conference on Multimedia, pp. 735-738, Scottsdale,
* Arizona, USA, 2011
* URL: http://dl.acm.org/citation.cfm?id=2072432
*
* Mathias Lux, Oge Marques. Visual Information Retrieval using Java and LIRE
* Morgan & Claypool, 2013
* URL: http://www.morganclaypool.com/doi/abs/10.2200/S00468ED1V01Y201301ICR025
*
* Copyright statement:
* --------------------
* (c) 2002-2013 by Mathias Lux (mathias@juggle.at)
* http://www.semanticmetadata.net/lire, http://www.lire-project.net
*/
package net.semanticmetadata.lire.indexing.fastmap;
import net.semanticmetadata.lire.matrix.DistanceMatrix;
/**
* Date: 07.02.2005
* Time: 22:06:25
*
* @author Mathias Lux, mathias@juggle.at
*/
public interface FastmapDistanceMatrix extends DistanceMatrix {
/**
* Calculates and returns the distance between two objects. Please note that the
* distance function has to be symmetric and must obey the triangle inequality.
* distance in k is: d[k+1](o1,o2)^2 = d[k](o1,o2)^2 - (x1[k]-x2[k])^2 .
*
* @param index1 index of first object to compute
* @param index2 index of second object to compute
* @param k defines the dimension of current fastmap operation
* @param x1 is needed when k > 0 (see documentation above), all x1[l] with l < k have to be present.
* @param x2 is needed when k > 0 (see documentation above), all x2[l] with l < k have to be present.
* @return the distance as float from [0, infinite)
*/
double getDistance(int index1, int index2, int k, double[] x1, double[] x2);
/**
* Used for the heuristic for getting the pivots as described in the paper.
*
* @param row defines the row where we want to find the maximum
* @param k defines the dimension of current fastmap operation
* @param points is needed when k > 0 (see documentation above), all x1[l] with l < k have to be present.
* @return the index of the object with maximum distance to the row object.
*/
int getMaximumDistance(int row, int k, double[][] points);
/**
* Normalizes the matrix for all values to [0,1]
*/
public void normalize();
}