001/**
002 * Copyright (C) 2007 - 2016, Jens Lehmann
003 *
004 * This file is part of DL-Learner.
005 *
006 * DL-Learner is free software; you can redistribute it and/or modify
007 * it under the terms of the GNU General Public License as published by
008 * the Free Software Foundation; either version 3 of the License, or
009 * (at your option) any later version.
010 *
011 * DL-Learner is distributed in the hope that it will be useful,
012 * but WITHOUT ANY WARRANTY; without even the implied warranty of
013 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
014 * GNU General Public License for more details.
015 *
016 * You should have received a copy of the GNU General Public License
017 * along with this program.  If not, see <http://www.gnu.org/licenses/>.
018 */
019package org.dllearner.algorithms.el;
020
021import org.dllearner.core.ComponentAnn;
022import org.dllearner.core.ComponentInitException;
023
024@ComponentAnn(name = "DisjunctiveHeuristic", shortName = "disjunctive_heuristic", version = 0.1)
025public class DisjunctiveHeuristic implements ELHeuristic {
026
027        ELDescriptionTreeComparator edt = new ELDescriptionTreeComparator();
028        
029        @Override
030        public int compare(SearchTreeNode tree1, SearchTreeNode tree2) {
031                double diff = tree1.getScore().getAccuracy()-tree2.getScore().getAccuracy();
032                if(diff < 0.00001 && diff > -0.00001) {
033                        return edt.compare(tree1.getDescriptionTree(), tree2.getDescriptionTree());
034                } else if(diff > 0){
035                        return 1;
036//                      return (int)Math.signum(diff);
037                } else {
038                        return -1;
039                }
040        }
041
042        /* (non-Javadoc)
043         * @see org.dllearner.core.Component#init()
044         */
045        @Override
046        public void init() throws ComponentInitException {
047        }
048
049        @Override
050        public double getNodeScore(SearchTreeNode node) {
051                return node.getScore().getAccuracy();
052        }
053}