/* * Copyright 2014 the original author or authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ package org.springframework.xd.analytics.ml.pmml; import static org.hamcrest.CoreMatchers.*; import static org.junit.Assert.*; import static org.springframework.xd.analytics.ml.pmml.TupleTestUtils.*; import java.util.Arrays; import org.junit.Rule; import org.junit.Test; import org.junit.rules.ExpectedException; import org.springframework.beans.factory.annotation.Value; import org.springframework.xd.analytics.ml.Analytic; import org.springframework.xd.tuple.Tuple; /** * @author Thomas Darimont */ public class KMeansClusteringPmmlAnalyticTest extends AbstractPmmlAnalyticTest { /** * @see XD-1420 */ @Test public void testKmeansClusteringIris1() { Analytic<Tuple, Tuple> analytic = useAnalytic("iris-kmeans-clustering-1", null, Arrays.asList("predictedValue")); Tuple output = analytic.evaluate(objectToTuple(new Object() { @Value("Sepal.Length") double sepalLength = 6.4; @Value("Sepal.Width") double sepalWidth = 3.2; @Value("Petal.Length") double petalLength = 4.5; @Value("Petal.Width") double petalWidth = 1.5; })); assertThat(output.getString("predictedValue"), is("1")); // versicolor output = analytic.evaluate(objectToTuple(new Object() { @Value("Sepal.Length") double sepalLength = 6.9; @Value("Sepal.Width") double sepalWidth = 3.1; @Value("Petal.Length") double petalLength = 5.4; @Value("Petal.Width") double petalWidth = 2.1; })); assertThat(output.getString("predictedValue"), is("3")); // virginica } }