/*
* 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.neural.freeform.basic;
import java.io.Serializable;
import java.util.ArrayList;
import java.util.List;
import org.encog.neural.freeform.FreeformConnection;
import org.encog.neural.freeform.FreeformNeuron;
import org.encog.neural.freeform.InputSummation;
/**
* This class provides a basic implementation of a freeform neuron.
*/
public class BasicFreeformNeuron implements FreeformNeuron, Serializable {
/**
* Serial id.
*/
private static final long serialVersionUID = 1L;
/**
* The input summation.
*/
private InputSummation inputSummation;
/**
* THe output connections.
*/
private final List<FreeformConnection> outputConnections = new ArrayList<FreeformConnection>();
/**
* The activation.
*/
private double activation;
/**
* True if this neuron is a bias neuron.
*/
private boolean bias;
/**
* Temp training values.
*/
private double[] tempTraining;
public BasicFreeformNeuron(final InputSummation theInputSummation) {
this.inputSummation = theInputSummation;
}
/**
* {@inheritDoc}
*/
@Override
public void addInput(final FreeformConnection connection) {
this.inputSummation.add(connection);
}
/**
* {@inheritDoc}
*/
@Override
public void addOutput(final FreeformConnection connection) {
this.outputConnections.add(connection);
}
/**
* {@inheritDoc}
*/
@Override
public void addTempTraining(final int i, final double value) {
this.tempTraining[i] += value;
}
/**
* {@inheritDoc}
*/
@Override
public void allocateTempTraining(final int l) {
this.tempTraining = new double[l];
}
/**
* {@inheritDoc}
*/
@Override
public void clearTempTraining() {
this.tempTraining = null;
}
/**
* {@inheritDoc}
*/
@Override
public double getActivation() {
return this.activation;
}
/**
* {@inheritDoc}
*/
@Override
public InputSummation getInputSummation() {
return this.inputSummation;
}
/**
* {@inheritDoc}
*/
@Override
public List<FreeformConnection> getOutputs() {
return this.outputConnections;
}
/**
* {@inheritDoc}
*/
@Override
public double getSum() {
if (this.inputSummation == null) {
return this.activation;
} else {
return this.inputSummation.getSum();
}
}
/**
* {@inheritDoc}
*/
@Override
public double getTempTraining(final int index) {
return this.tempTraining[index];
}
/**
* {@inheritDoc}
*/
@Override
public boolean isBias() {
return this.bias;
}
/**
* {@inheritDoc}
*/
@Override
public void performCalculation() {
// no inputs? Just keep activation as is, probably a bias neuron.
if (getInputSummation() == null) {
return;
}
this.activation = this.inputSummation.calculate();
}
/**
* {@inheritDoc}
*/
@Override
public void setActivation(final double theActivation) {
this.activation = theActivation;
}
/**
* {@inheritDoc}
*/
@Override
public void setBias(final boolean bias) {
this.bias = bias;
}
/**
* {@inheritDoc}
*/
@Override
public void setInputSummation(final InputSummation theInputSummation) {
this.inputSummation = theInputSummation;
}
/**
* {@inheritDoc}
*/
@Override
public void setTempTraining(final int index, final double value) {
this.tempTraining[index] = value;
}
/**
* {@inheritDoc}
*/
@Override
public void updateContext() {
// nothing to do for a non-context neuron
}
/**
* {@inheritDoc}
*/
@Override
public String toString() {
StringBuilder result = new StringBuilder();
result.append("[BasicFreeformNeuron: ");
result.append("inputCount=");
if( this.inputSummation==null ) {
result.append("null");
} else {
result.append(this.inputSummation.list().size());
}
result.append(",outputCount=");
result.append(this.outputConnections.size());
result.append("]");
return result.toString();
}
}