/** * Copyright 2014, Emory University * * 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 edu.emory.clir.clearnlp.classification.instance; import static org.junit.Assert.assertEquals; import org.junit.Test; import edu.emory.clir.clearnlp.classification.instance.SparseInstance; import edu.emory.clir.clearnlp.classification.instance.SparseInstanceCollector; import edu.emory.clir.clearnlp.classification.vector.SparseFeatureVector; /** * @since 3.0.0 * @author Jinho D. Choi ({@code jinho.choi@emory.edu}) */ public class SparseInstanceCollectorTest { @Test public void test() { SparseInstanceCollector collector = new SparseInstanceCollector(); collector.addInstance(new SparseInstance("2", getSparseFeatureVector1())); collector.addInstance(new SparseInstance("0", getSparseFeatureVector2())); collector.addInstance(new SparseInstance("1", getSparseFeatureVector3())); assertEquals(3, collector.getLabelSize()); assertEquals(4, collector.getFeatureSize()); } private SparseFeatureVector getSparseFeatureVector1() { SparseFeatureVector vector = new SparseFeatureVector(); vector.addFeature(0); vector.addFeature(1); return vector; } private SparseFeatureVector getSparseFeatureVector2() { SparseFeatureVector vector = new SparseFeatureVector(); vector.addFeature(1); vector.addFeature(2); return vector; } private SparseFeatureVector getSparseFeatureVector3() { SparseFeatureVector vector = new SparseFeatureVector(); vector.addFeature(2); vector.addFeature(3); return vector; } }