/*
* Encog(tm) Core Unit Tests v3.0 - Java Version
* http://www.heatonresearch.com/encog/
* http://code.google.com/p/encog-java/
* Copyright 2008-2011 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.neural.networks;
import junit.framework.TestCase;
import org.encog.ml.data.MLDataSet;
import org.encog.ml.data.basic.BasicMLDataSet;
import org.encog.neural.networks.training.propagation.resilient.ResilientPropagation;
import org.junit.Assert;
public class TestLimited extends TestCase {
public void testLimited()
{
MLDataSet trainingData = new BasicMLDataSet(XOR.XOR_INPUT,XOR.XOR_IDEAL);
BasicNetwork network = NetworkUtil.createXORNetworkUntrained();
ResilientPropagation rprop = new ResilientPropagation(network,trainingData);
rprop.iteration();
rprop.iteration();
network.enableConnection(1, 0, 0, false);
network.enableConnection(1, 1, 0, false);
Assert.assertTrue(network.getStructure().isConnectionLimited());
Assert.assertEquals(0.0, network.getStructure().getFlat().getWeights()[0], 0.01);
Assert.assertEquals(0.0, network.getStructure().getFlat().getWeights()[1], 0.01);
rprop.iteration();
rprop.iteration();
rprop.iteration();
rprop.iteration();
// these connections were removed, and should not have been "trained"
Assert.assertEquals(0.0, network.getStructure().getFlat().getWeights()[0], 0.01);
Assert.assertEquals(0.0, network.getStructure().getFlat().getWeights()[1], 0.01);
rprop.finishTraining();
}
}