/*
* RapidMiner
*
* Copyright (C) 2001-2008 by Rapid-I and the contributors
*
* Complete list of developers available at our web site:
*
* http://rapid-i.com
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU Affero 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 Affero General Public License for more details.
*
* You should have received a copy of the GNU Affero General Public License
* along with this program. If not, see http://www.gnu.org/licenses/.
*/
package com.rapidminer.test;
import com.rapidminer.operator.IOContainer;
import com.rapidminer.operator.MissingIOObjectException;
import com.rapidminer.operator.performance.PerformanceVector;
import com.rapidminer.operator.similarity.attributebased.EuclideanDistance;
import com.rapidminer.operator.similarity.clustermodel.TreeDistance;
/**
* Tests for Similarity in Learner/Unsupervised/Clustering/Similarity
*
* @author Marcin Skirzynski
* @version $Id: SimilaritySampleDataTest.java,v 1.9 2008/09/12 10:29:52 tobiasmalbrecht Exp $
*/
public class SimilaritySampleDataTest extends OperatorDataSampleTest {
private double[] expectedValues;
private String[] first;
private String[] second;
private String similarity;
public SimilaritySampleDataTest(String file, String similarity, String[] first, String[] second, double[] expectedValues) {
super(file);
this.expectedValues = expectedValues;
this.first = first;
this.second = second;
this.similarity = similarity;
}
public void checkOutput(IOContainer output) throws MissingIOObjectException {
if (similarity.equals("Tree")) {
TreeDistance treedistance = output.get(TreeDistance.class);
for (int i=0;i<expectedValues.length;i++) {
assertEquals(treedistance.similarity(first[i],second[i]), expectedValues[i]);
}
}
if (similarity.equals("Euclidean")) {
EuclideanDistance euclideandistance = output.get(EuclideanDistance.class);
for (int i=0;i<expectedValues.length;i++) {
assertEquals(euclideandistance.similarity(first[i],second[i]), expectedValues[i]);
}
}
if (similarity.equals("Comparator")) {
PerformanceVector performancevector = output.get(PerformanceVector.class);
assertEquals(expectedValues[0],performancevector.getCriterion("similarity").getAverage(), 0.00001);
}
}
}