/* * Encog(tm) Core v3.4 - Java Version * http://www.heatonresearch.com/encog/ * https://github.com/encog/encog-java-core * Copyright 2008-2016 Heaton Research, Inc. * * 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. * * For more information on Heaton Research copyrights, licenses * and trademarks visit: * http://www.heatonresearch.com/copyright */ package org.encog.util.normalize; import junit.framework.TestCase; import org.encog.NullStatusReportable; import org.encog.neural.data.basic.BasicNeuralDataSet; import org.encog.util.SerializeRoundTrip; import org.encog.util.normalize.input.InputField; import org.encog.util.normalize.input.InputFieldMLDataSet; import org.encog.util.normalize.output.OutputFieldRangeMapped; import org.encog.util.normalize.target.NormalizationStorageArray2D; import org.junit.Assert; public class TestNormDataSet extends TestCase { public static final double[][] ARRAY_2D = { {1.0,2.0,3.0,4.0,5.0}, {6.0,7.0,8.0,9.0} }; private DataNormalization create() { InputField a,b; double[][] arrayOutput = new double[2][2]; BasicNeuralDataSet dataset = new BasicNeuralDataSet(ARRAY_2D,null); NormalizationStorageArray2D target = new NormalizationStorageArray2D(arrayOutput); DataNormalization norm = new DataNormalization(); norm.setReport(new NullStatusReportable()); norm.setTarget(target); norm.addInputField(a = new InputFieldMLDataSet(false,dataset,0)); norm.addInputField(b = new InputFieldMLDataSet(false,dataset,1)); norm.addOutputField(new OutputFieldRangeMapped(a,0.1,0.9)); norm.addOutputField(new OutputFieldRangeMapped(b,0.1,0.9)); return norm; } private void check(DataNormalization norm) { double[][] arrayOutput = ((NormalizationStorageArray2D)norm.getStorage()).getArray(); Assert.assertEquals(arrayOutput[0][0],0.1,0.1); Assert.assertEquals(arrayOutput[1][0],0.9,0.1); Assert.assertEquals(arrayOutput[0][1],0.1,0.1); Assert.assertEquals(arrayOutput[1][1],0.9,0.1); } public void testDataSet() { DataNormalization norm = create(); norm.process(); check(norm); } public void testDataSetSerial() throws Exception { DataNormalization norm = create(); norm = (DataNormalization)SerializeRoundTrip.roundTrip(norm); norm.process(); check(norm); } }