/*
* Encog(tm) Workbench v3.0
* 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.
*
* For more information on Heaton Research copyrights, licenses
* and trademarks visit:
* http://www.heatonresearch.com/copyright
*/
package org.encog.workbench.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);
}
}