/*
* Encog(tm) Unit Tests v2.5 - Java Version
* http://www.heatonresearch.com/encog/
* http://code.google.com/p/encog-java/
* Copyright 2008-2010 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.
*
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*/
package org.encog.normalize;
import junit.framework.TestCase;
import org.encog.NullStatusReportable;
import org.encog.neural.data.basic.BasicNeuralDataSet;
import org.encog.normalize.input.InputField;
import org.encog.normalize.input.InputFieldArray2D;
import org.encog.normalize.input.InputFieldNeuralDataSet;
import org.encog.normalize.output.OutputFieldRangeMapped;
import org.encog.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} };
public void testDataSet()
{
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 InputFieldNeuralDataSet(false,dataset,0));
norm.addInputField(b = new InputFieldNeuralDataSet(false,dataset,1));
norm.addOutputField(new OutputFieldRangeMapped(a,0.1,0.9));
norm.addOutputField(new OutputFieldRangeMapped(b,0.1,0.9));
norm.process();
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);
}
}