/*
* 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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* and trademarks visit:
* http://www.heatonresearch.com/copyright
*/
package org.encog.neural.networks;
import org.encog.mathutil.randomize.FanInRandomizer;
import org.encog.mathutil.randomize.RangeRandomizer;
import org.encog.util.EngineArray;
import org.encog.util.simple.EncogUtility;
import junit.framework.Assert;
import junit.framework.TestCase;
public class TestWeightAccess extends TestCase {
public void testTracks()
{
BasicNetwork network = EncogUtility.simpleFeedForward(5,10,15,20, true);
double[] weights = network.getStructure().getFlat().getWeights();
EngineArray.fill(weights, 100);
(new RangeRandomizer(-1,1)).randomize(network);
for(int i=0;i<weights.length;i++ )
{
Assert.assertTrue(weights[i]<10);
}
}
public void testFanIn()
{
BasicNetwork network = EncogUtility.simpleFeedForward(5,10,15,20, true);
double[] weights = network.getStructure().getFlat().getWeights();
EngineArray.fill(weights, 100);
(new FanInRandomizer()).randomize(network);
System.out.println(network.dumpWeights());
for(int i=0;i<weights.length;i++ )
{
Assert.assertTrue(weights[i]<10);
}
}
public void testWeights()
{
BasicNetwork network = EncogUtility.simpleFeedForward(2, 3, 0, 1, true);
double[] weights = network.getStructure().getFlat().getWeights();
Assert.assertEquals(weights.length, 13);
for(int i=0;i<weights.length;i++)
{
weights[i] = i;
}
Assert.assertEquals(0.0, network.getWeight(1, 0, 0) );
Assert.assertEquals(1.0, network.getWeight(1, 1, 0) );
Assert.assertEquals(2.0, network.getWeight(1, 2, 0) );
Assert.assertEquals(3.0, network.getWeight(1, 3, 0) );
Assert.assertEquals(4.0, network.getWeight(0, 0, 0) );
Assert.assertEquals(5.0, network.getWeight(0, 1, 0) );
Assert.assertEquals(6.0, network.getWeight(0, 2, 0) );
Assert.assertEquals(7.0, network.getWeight(0, 0, 1) );
Assert.assertEquals(8.0, network.getWeight(0, 1, 1) );
Assert.assertEquals(9.0, network.getWeight(0, 2, 1) );
Assert.assertEquals(10.0, network.getWeight(0, 0, 2) );
Assert.assertEquals(11.0, network.getWeight(0, 1, 2) );
Assert.assertEquals(12.0, network.getWeight(0, 2, 2) );
}
}