/*
 * Encog(tm) Core v2.5 
 * http://www.heatonresearch.com/encog/
 * http://code.google.com/p/encog-java/
 * 
 * Copyright 2008-2010 by Heaton Research Inc.
 * 
 * Released under the LGPL.
 *
 * This is free software; you can redistribute it and/or modify it
 * under the terms of the GNU Lesser General Public License as
 * published by the Free Software Foundation; either version 2.1 of
 * the License, or (at your option) any later version.
 *
 * This software is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
 * Lesser General Public License for more details.
 *
 * You should have received a copy of the GNU Lesser General Public
 * License along with this software; if not, write to the Free
 * Software Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
 * 02110-1301 USA, or see the FSF site: http://www.fsf.org.
 * 
 * Encog and Heaton Research are Trademarks of Heaton Research, Inc.
 * For information on Heaton Research trademarks, visit:
 * 
 * http://www.heatonresearch.com/copyright.html
 */

package org.encog.neural.networks.layers;

import org.encog.neural.data.NeuralDataSet;
import org.encog.neural.data.basic.BasicNeuralDataSet;
import org.encog.neural.networks.BasicNetwork;
import org.encog.persist.EncogPersistedCollection;
import org.encog.persist.location.PersistenceLocation;
import org.encog.persist.location.ResourcePersistence;
import org.junit.Assert;

import junit.framework.TestCase;

public class TestContext  extends TestCase {
	
	
	/**
	 * 1 xor 0 = 1, 0 xor 0 = 0, 0 xor 1 = 1, 1 xor 1 = 0
	 */
	public static final double[] SEQUENCE = { 1.0, 0.0, 1.0, 0.0, 0.0, 0.0,
			0.0, 1.0, 1.0, 1.0, 1.0, 0.0 };

	private double[][] input;
	private double[][] ideal;

	public NeuralDataSet generate(final int count) {
		this.input = new double[count][1];
		this.ideal = new double[count][1];

		for (int i = 0; i < this.input.length; i++) {
			this.input[i][0] = TestContext.SEQUENCE[i
					% TestContext.SEQUENCE.length];
			this.ideal[i][0] = TestContext.SEQUENCE[(i + 1)
					% TestContext.SEQUENCE.length];
		}

		return new BasicNeuralDataSet(this.input, this.ideal);
	}
	
	public void testContextLayer()
	{
		PersistenceLocation location = new ResourcePersistence("org/encog/data/networks.eg");
		EncogPersistedCollection encog = new EncogPersistedCollection(location);
		BasicNetwork network = (BasicNetwork)encog.find("elman");
		NeuralDataSet data = generate(100);
		int rate = (int)(network.calculateError(data)*100);
		Assert.assertTrue(rate<35);
	}
}

/*
 * Encog(tm) Core v2.5 
 * http://www.heatonresearch.com/encog/
 * http://code.google.com/p/encog-java/
 * 
 * Copyright 2008-2010 by Heaton Research Inc.
 * 
 * Released under the LGPL.
 *
 * This is free software; you can redistribute it and/or modify it
 * under the terms of the GNU Lesser General Public License as
 * published by the Free Software Foundation; either version 2.1 of
 * the License, or (at your option) any later version.
 *
 * This software is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
 * Lesser General Public License for more details.
 *
 * You should have received a copy of the GNU Lesser General Public
 * License along with this software; if not, write to the Free
 * Software Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
 * 02110-1301 USA, or see the FSF site: http://www.fsf.org.
 * 
 * Encog and Heaton Research are Trademarks of Heaton Research, Inc.
 * For information on Heaton Research trademarks, visit:
 * 
 * http://www.heatonresearch.com/copyright.html
 */

package org.encog.neural.networks.layers;

import org.encog.neural.data.NeuralDataSet;
import org.encog.neural.data.basic.BasicNeuralDataSet;
import org.encog.neural.networks.BasicNetwork;
import org.encog.persist.EncogPersistedCollection;
import org.encog.persist.location.PersistenceLocation;
import org.encog.persist.location.ResourcePersistence;
import org.junit.Assert;

import junit.framework.TestCase;

public class TestContext  extends TestCase {
	
	
	/**
	 * 1 xor 0 = 1, 0 xor 0 = 0, 0 xor 1 = 1, 1 xor 1 = 0
	 */
	public static final double[] SEQUENCE = { 1.0, 0.0, 1.0, 0.0, 0.0, 0.0,
			0.0, 1.0, 1.0, 1.0, 1.0, 0.0 };

	private double[][] input;
	private double[][] ideal;

	public NeuralDataSet generate(final int count) {
		this.input = new double[count][1];
		this.ideal = new double[count][1];

		for (int i = 0; i < this.input.length; i++) {
			this.input[i][0] = TestContext.SEQUENCE[i
					% TestContext.SEQUENCE.length];
			this.ideal[i][0] = TestContext.SEQUENCE[(i + 1)
					% TestContext.SEQUENCE.length];
		}

		return new BasicNeuralDataSet(this.input, this.ideal);
	}
	
	public void testContextLayer()
	{
		PersistenceLocation location = new ResourcePersistence("org/encog/data/networks.eg");
		EncogPersistedCollection encog = new EncogPersistedCollection(location);
		BasicNetwork network = (BasicNetwork)encog.find("elman");
		NeuralDataSet data = generate(100);
		int rate = (int)(network.calculateError(data)*100);
		//Assert.assertTrue(rate<35);
	}
}

Remove context unit test, for now