TemporalXOR.java

/*
 * Encog(tm) Java Examples v3.4
 * http://www.heatonresearch.com/encog/
 * https://github.com/encog/encog-java-examples
 *
 * 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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 */
package org.encog.examples.neural.util;

import org.encog.ml.data.MLDataSet;
import org.encog.ml.data.basic.BasicMLDataSet;

/**
 * Utility class that presents the XOR operator as a serial stream of values.
 * This is used to predict the next value in the XOR sequence. This provides a
 * simple stream of numbers that can be predicted.
 * 
 * @author jeff
 * 
 */
public class TemporalXOR {

	/**
	 * 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 MLDataSet 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] = TemporalXOR.SEQUENCE[i
					% TemporalXOR.SEQUENCE.length];
			this.ideal[i][0] = TemporalXOR.SEQUENCE[(i + 1)
					% TemporalXOR.SEQUENCE.length];
		}

		return new BasicMLDataSet(this.input, this.ideal);
	}
}