/*
* Encog(tm) Core v3.4 - Java Version
* http://www.heatonresearch.com/encog/
* https://github.com/encog/encog-java-core
* 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.
*
* For more information on Heaton Research copyrights, licenses
* and trademarks visit:
* http://www.heatonresearch.com/copyright
*/
package org.encog.util.normalize.output.zaxis;
import org.encog.util.normalize.NormalizationError;
import org.encog.util.normalize.input.InputField;
import org.encog.util.normalize.output.OutputFieldGroup;
import org.encog.util.normalize.output.OutputFieldGrouped;
/**
* Both the multiplicative and z-axis normalization types allow a group of
* outputs to be adjusted so that the "vector length" is 1. Both go about it in
* different ways. Certain types of neural networks require a vector length of
* 1.
*
* Z-Axis normalization is usually a better choice than multiplicative. However,
* multiplicative can perform better than Z-Axis when all of the values are near
* zero most of the time. This can cause the "synthetic value" that z-axis uses
* to dominate and skew the answer.
*
* Z-Axis gets its name from 3D computer graphics, where there is a Z-Axis
* extending from the plane created by the X and Y axes. It has nothing to do
* with z-scores or the z-transform of signal theory.
*
* To implement Z-Axis normalization a scaling factor must be created to
* multiply each of the inputs against. Additionally, a synthetic field must be
* added. It is very important that this synthetic field be added to any z-axis
* group that you might use. The synthetic field is represented by the
* OutputFieldZAxisSynthetic class.
*
* @author jheaton
*/
public class OutputFieldZAxis extends OutputFieldGrouped {
/**
* Construct a ZAxis output field.
* @param group The group this field belongs to.
* @param field The input field this is based on.
*/
public OutputFieldZAxis(final OutputFieldGroup group,
final InputField field) {
super(group, field);
if (!(group instanceof ZAxisGroup)) {
throw new NormalizationError(
"Must use ZAxisGroup with OutputFieldZAxis.");
}
}
/**
* Calculate the current value for this field.
*
* @param subfield
* Ignored, this field type does not have subfields.
* @return The current value for this field.
*/
public double calculate(final int subfield) {
return (getSourceField().getCurrentValue() * ((ZAxisGroup) getGroup())
.getMultiplier());
}
/**
* @return The subfield count, which is one, as this field type does not
* have subfields.
*/
public int getSubfieldCount() {
return 1;
}
/**
* Not needed for this sort of output field.
*/
public void rowInit() {
}
}