/*
* Encog(tm) Core v3.0 - Java Version
* 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.neural.neat;
import java.io.InputStream;
import java.io.OutputStream;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import org.encog.persist.EncogFileSection;
import org.encog.persist.EncogPersistor;
import org.encog.persist.EncogReadHelper;
import org.encog.persist.EncogWriteHelper;
import org.encog.persist.PersistConst;
import org.encog.util.csv.CSVFormat;
public class PersistNEATNetwork implements EncogPersistor {
@Override
public int getFileVersion() {
return 1;
}
@Override
public String getPersistClassString() {
return "NEATNetwork";
}
@Override
public Object read(InputStream is) {
NEATNetwork result = new NEATNetwork();
EncogReadHelper in = new EncogReadHelper(is);
EncogFileSection section;
Map<Integer,NEATNeuron> neuronMap = new HashMap<Integer,NEATNeuron>();
while( (section = in.readNextSection()) != null ) {
if( section.getSectionName().equals("NEAT") && section.getSubSectionName().equals("PARAMS") ) {
Map<String,String> params = section.parseParams();
result.getProperties().putAll(params);
} if( section.getSectionName().equals("NEAT") && section.getSubSectionName().equals("NETWORK") ) {
Map<String,String> params = section.parseParams();
result.setInputCount( EncogFileSection.parseInt(params,PersistConst.INPUT_COUNT));
result.setOutputCount( EncogFileSection.parseInt(params,PersistConst.OUTPUT_COUNT));
result.setActivationFunction( EncogFileSection.parseActivationFunction(params,PersistConst.ACTIVATION_FUNCTION));
result.setOutputActivationFunction( EncogFileSection.parseActivationFunction(params,NEATPopulation.PROPERTY_OUTPUT_ACTIVATION));
result.setNetworkDepth( EncogFileSection.parseInt(params,PersistConst.DEPTH));
result.setSnapshot( EncogFileSection.parseBoolean(params, PersistConst.SNAPSHOT));
} else if( section.getSectionName().equals("NEAT") && section.getSubSectionName().equals("NEURONS") ) {
for (String line : section.getLines()) {
List<String> cols = EncogFileSection.splitColumns(line);
final long neuronID = Integer.parseInt(cols.get(0));
final NEATNeuronType neuronType = PersistNEATPopulation.stringToNeuronType(cols.get(1));
final double activationResponse = CSVFormat.EG_FORMAT.parse(cols.get(2));
final double splitY = CSVFormat.EG_FORMAT.parse(cols.get(3));
final double splitX = CSVFormat.EG_FORMAT.parse(cols.get(4));
NEATNeuron neatNeuron = new NEATNeuron(neuronType, neuronID,
splitY,splitX,activationResponse);
result.getNeurons().add(neatNeuron);
neuronMap.put((int)neuronID, neatNeuron);
}
} else if( section.getSectionName().equals("NEAT") && section.getSubSectionName().equals("LINKS") ) {
for (String line : section.getLines()) {
List<String> cols = EncogFileSection.splitColumns(line);
int fromID = Integer.parseInt(cols.get(0));
int toID = Integer.parseInt(cols.get(1));
boolean recurrent = Integer.parseInt(cols.get(2))>0;
double weight = CSVFormat.EG_FORMAT.parse(cols.get(3));
NEATNeuron fromNeuron = neuronMap.get(fromID);
NEATNeuron toNeuron = neuronMap.get(toID);
NEATLink neatLink = new NEATLink(weight,fromNeuron,toNeuron,recurrent);
fromNeuron.getOutputboundLinks().add(neatLink);
toNeuron.getInboundLinks().add(neatLink);
}
}
}
return result;
}
@Override
public void save(OutputStream os, Object obj) {
EncogWriteHelper out = new EncogWriteHelper(os);
NEATNetwork neat = (NEATNetwork)obj;
out.addSection("NEAT");
out.addSubSection("PARAMS");
out.addProperties(neat.getProperties());
out.addSubSection("NETWORK");
out.writeProperty(PersistConst.INPUT_COUNT, neat.getInputCount());
out.writeProperty(PersistConst.OUTPUT_COUNT, neat.getOutputCount());
out.writeProperty(PersistConst.ACTIVATION_FUNCTION, neat.getActivationFunction());
out.writeProperty(NEATPopulation.PROPERTY_OUTPUT_ACTIVATION, neat.getOutputActivationFunction());
out.writeProperty(PersistConst.DEPTH, neat.getNetworkDepth());
out.writeProperty(PersistConst.SNAPSHOT, neat.isSnapshot());
out.addSubSection("NEURONS");
for (NEATNeuron neatNeuron : neat.getNeurons() ) {
out.addColumn(neatNeuron.getNeuronID());
out.addColumn(PersistNEATPopulation.neuronTypeToString(neatNeuron.getNeuronType()));
out.addColumn(neatNeuron.getActivationResponse());
out.addColumn(neatNeuron.getSplitX());
out.addColumn(neatNeuron.getSplitY());
out.writeLine();
}
out.addSubSection("LINKS");
for (NEATNeuron neatNeuron : neat.getNeurons() ) {
for(NEATLink link: neatNeuron.getOutputboundLinks() ) {
writeLink(out,link);
}
}
out.flush();
}
private void writeLink(EncogWriteHelper out, NEATLink link) {
out.addColumn(link.getFromNeuron().getNeuronID());
out.addColumn(link.getToNeuron().getNeuronID());
out.addColumn(link.isRecurrent());
out.addColumn(link.getWeight());
out.writeLine();
}
}