/*
* 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.matrix;
/**
* Date: 07.02.2005
* Time: 22:10:54
*
* @author Mathias Lux, mathias@juggle.at
*/
public interface DistanceMatrix {
/**
* Calculates the distance between objects using the distance function for k = 0,
* using {@link net.semanticmetadata.lire.indexing.fastmap.DistanceCalculator#getDistance(Object, Object)}. If it has not
* been computed previously it is computed and stored now.
*
* @param o1 Object 1 to compute
* @param o2 Object 2 to compute
* @return the distance as float from [0, infinite)
*/
double getDistance(Object o1, Object o2);
/**
* Calculates the distance between objects using the distance function for k = 0,
* using {@link net.semanticmetadata.lire.indexing.fastmap.DistanceCalculator#getDistance(Object, Object)}. If it has not
* been computed previously it is computed and stored now.
*
* @param index1 index of first object to compute
* @param index2 index of second object to compute
* @return the distance as float from [0, infinite)
*/
double getDistance(int index1, int index2);
/**
* Used for the heuristic for getting the pivots as described in the paper. This method calls
* with parameters (row, 0, null, null).
*
* @param row defines the row where we want to find the maximum
* @return the index of the object with maximum distance to the row object.
*/
int getMaximumDistance(int row);
/**
* Returns the dimension of the matrix
*
* @return dimension, which is > 0
*/
int getDimension();
/**
* Returns the user object for given index number
*
* @param rowNumber
* @return
* @see #getIndexOfObject(Object)
*/
Object getUserObject(int rowNumber);
/**
* Returns the index in the matrix of the given user object or -1 if not found
*
* @param o the object to search for
* @return the index number of the object or -1 if not found
* @see #getUserObject(int)
*/
int getIndexOfObject(Object o);
/**
* Creates and returns a newly created similarity Matrix from the given
* distance Matrix
*
* @return the similarityMatrix or null if not implemented or possible
*/
public SimilarityMatrix getSimilarityMatrix();
}