/*
* Encog(tm) Core v3.3 - Java Version
* http://www.heatonresearch.com/encog/
* https://github.com/encog/encog-java-core
* Copyright 2008-2014 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.pattern;
import org.encog.engine.network.activation.ActivationFunction;
import org.encog.ml.MLMethod;
import org.encog.neural.thermal.BoltzmannMachine;
/**
* Pattern to create a Boltzmann machine.
*
*/
public class BoltzmannPattern implements NeuralNetworkPattern {
/**
* The number of neurons in the Boltzmann network.
*/
private int neuronCount;
/**
* The number of annealing cycles per run.
*/
private int annealCycles = 100;
/**
* The number of cycles per run.
*/
private int runCycles = 1000;
/**
* The current temperature.
*/
private double temperature = 0.0;
/**
* Not supported, will throw an exception, Boltzmann networks have no hidden
* layers.
*
* @param count
* Not used.
*/
public void addHiddenLayer(final int count) {
throw new PatternError("A Boltzmann network has no hidden layers.");
}
/**
* Clear any properties set on this network.
*/
public void clear() {
this.neuronCount = 0;
}
/**
* Generate the network.
*
* @return The generated network.
*/
public MLMethod generate() {
BoltzmannMachine boltz = new BoltzmannMachine(this.neuronCount);
boltz.setTemperature(this.temperature);
boltz.setRunCycles(this.runCycles);
boltz.setAnnealCycles(this.annealCycles);
return boltz;
}
/**
* @return The number of annealing cycles per run.
*/
public int getAnnealCycles() {
return this.annealCycles;
}
/**
* @return The number of cycles per run.
*/
public int getRunCycles() {
return this.runCycles;
}
/**
* @return The temperature.
*/
public double getTemperature() {
return this.temperature;
}
/**
* Not used, will throw an exception.
*
* @param activation
* Not used.
*/
public void setActivationFunction(final ActivationFunction activation) {
throw new PatternError( "A Boltzmann network will use the BiPolar activation "
+ "function, no activation function needs to be specified.");
}
/**
* Set the number of annealing cycles per run.
*
* @param annealCycles
* The new value.
*/
public void setAnnealCycles(final int annealCycles) {
this.annealCycles = annealCycles;
}
/**
* Set the number of input neurons. This is the same as the number of output
* neurons.
*
* @param count
* The number of input neurons.
*/
public void setInputNeurons(final int count) {
this.neuronCount = count;
}
/**
* Set the number of output neurons. This is the same as the number of input
* neurons.
*
* @param count
* The number of output neurons.
*/
public void setOutputNeurons(final int count) {
this.neuronCount = count;
}
/**
* Set the number of cycles per run.
*
* @param runCycles
* The new value.
*/
public void setRunCycles(final int runCycles) {
this.runCycles = runCycles;
}
/**
* Set the temperature.
*
* @param temperature
* The new value.
*/
public void setTemperature(final double temperature) {
this.temperature = temperature;
}
}