/*
* 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.
*
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* and trademarks visit:
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*/
package org.encog.neural.data.bipolar;
import junit.framework.TestCase;
import org.encog.ml.data.specific.BiPolarNeuralData;
import org.junit.Assert;
public class TestBiPolarNeuralData extends TestCase {
public void testConstruct()
{
boolean[] d = { true, false };
BiPolarNeuralData data = new BiPolarNeuralData(d);
Assert.assertEquals("[T,F]",data.toString());
Assert.assertEquals(1,data.getData(0),0.5);
Assert.assertEquals(-1,data.getData(1),0.5);
Assert.assertEquals(true, data.getBoolean(0));
Assert.assertEquals(false, data.getBoolean(1));
Assert.assertEquals(data.getData().length,2);
}
public void testClone()
{
boolean[] d = { true, false };
BiPolarNeuralData data2 = new BiPolarNeuralData(d);
BiPolarNeuralData data = (BiPolarNeuralData)data2.clone();
Assert.assertEquals("[T,F]",data.toString());
Assert.assertEquals(1,data.getData(0),0.5);
Assert.assertEquals(-1,data.getData(1),0.5);
Assert.assertEquals(true, data.getBoolean(0));
Assert.assertEquals(false, data.getBoolean(1));
Assert.assertEquals(data.getData().length,2);
}
public void testError()
{
BiPolarNeuralData data = new BiPolarNeuralData(2);
Assert.assertEquals(2, data.size());
try
{
data.add(0, 0);
Assert.assertTrue(false);
}
catch(Exception e)
{
}
}
public void testClear()
{
double[] d = {1,1};
BiPolarNeuralData data = new BiPolarNeuralData(2);
data.setData(d);
data.clear();
Assert.assertEquals(-1,data.getData(0),0.5);
data.setData(0,true);
Assert.assertEquals(true,data.getBoolean(0));
}
}