/*
* Encog(tm) Core v2.5 - Java Version
* http://www.heatonresearch.com/encog/
* http://code.google.com/p/encog-java/
* Copyright 2008-2010 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.persist.persistors;
import java.util.ArrayList;
import java.util.List;
import java.util.Map;
import org.encog.engine.network.activation.ActivationFunction;
import org.encog.engine.network.rbf.RadialBasisFunction;
import org.encog.mathutil.rbf.GaussianFunction;
import org.encog.neural.NeuralNetworkError;
import org.encog.neural.networks.layers.RadialBasisFunctionLayer;
import org.encog.parse.tags.read.ReadXML;
import org.encog.parse.tags.write.WriteXML;
import org.encog.persist.EncogPersistedCollection;
import org.encog.persist.EncogPersistedObject;
import org.encog.persist.PersistError;
import org.encog.persist.Persistor;
import org.encog.persist.persistors.generic.Object2XML;
import org.encog.util.csv.CSVFormat;
import org.encog.util.csv.NumberList;
import org.encog.util.obj.ReflectionUtil;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
/**
* The Encog persistor used to persist the RadialBasisFunctionLayer class.
*
* @author jheaton
*/
public class RadialBasisFunctionLayerPersistor implements Persistor {
/**
* XML tag for the radial functions collection.
*/
public static final String PROPERTY_RBF = "rbf";
/**
* The centers.
*/
public static final String PROPERTY_CENTERS = "centers";
/**
* The peak.
*/
public static final String PROPERTY_PEAK = "peak";
/**
* The width.
*/
public static final String PROPERTY_WIDTH = "width";
/**
* The logging object.
*/
@SuppressWarnings("unused")
private final Logger logger = LoggerFactory.getLogger(this.getClass());
/**
* Load a RBF layer.
*
* @param in
* The XML to read from.
* @return The object that was loaded.
*/
public EncogPersistedObject load(final ReadXML in) {
int neuronCount = 0;
int x = 0;
int y = 0;
int dimensions = 1;
RadialBasisFunction[] rbfs = new RadialBasisFunction[0];
final String end = in.getTag().getName();
while (in.readToTag()) {
if (in.is(BasicLayerPersistor.PROPERTY_NEURONS, true)) {
neuronCount = in.readIntToTag();
} else if (in.is(BasicLayerPersistor.PROPERTY_X, true)) {
x = in.readIntToTag();
} else if (in.is(BasicLayerPersistor.PROPERTY_Y, true)) {
y = in.readIntToTag();
} else if (in.is(RadialBasisFunctionLayerPersistor.PROPERTY_RBF,
true)) {
rbfs = loadAllRBF(in);
} else if (in.is(end, false)) {
break;
}
}
RadialBasisFunctionLayer layer = new RadialBasisFunctionLayer(neuronCount);
layer.setRadialBasisFunction(rbfs);
layer.setX(x);
layer.setY(y);
return layer;
}
private RadialBasisFunction[] loadAllRBF(final ReadXML in) {
List<RadialBasisFunction> rbfs = new ArrayList<RadialBasisFunction>();
while (in.readToTag()) {
if (in.is(PROPERTY_RBF, false)) {
break;
} else {
String name = in.getTag().getName();
RadialBasisFunction rbf = loadRBF(name,in);
rbfs.add(rbf);
}
}
RadialBasisFunction[] result = new RadialBasisFunction[rbfs.size()];
for(int i=0;i<rbfs.size();i++)
result[i] = rbfs.get(i);
return result;
}
private RadialBasisFunction loadRBF(final String name,final ReadXML in) {
Class<?> clazz = ReflectionUtil.resolveEncogClass(name);
if( clazz==null ) {
throw new NeuralNetworkError("Unknown activation function type: " + name);
}
RadialBasisFunction result;
try {
result = (RadialBasisFunction) clazz
.newInstance();
} catch (InstantiationException e) {
throw new PersistError(e);
} catch (IllegalAccessException e) {
throw new PersistError(e);
}
while (in.readToTag()) {
if (in.is(name, false)) {
break;
} else if (in.is(PROPERTY_CENTERS, true)) {
String str = in.readTextToTag();
double[] centers = NumberList.fromList(CSVFormat.EG_FORMAT, str);
result.setCenters(centers);
} else if (in.is(PROPERTY_PEAK, true)) {
String str = in.readTextToTag();
double d = Double.parseDouble(str);
result.setPeak(d);
} else if (in.is(PROPERTY_WIDTH,
true)) {
String str = in.readTextToTag();
double d = Double.parseDouble(str);
result.setWidth(d);
}
}
return result;
}
/**
* Save a RBF layer.
*
* @param obj
* The object to save.
* @param out
* XML stream to write to.
*/
public void save(final EncogPersistedObject obj, final WriteXML out) {
PersistorUtil.beginEncogObject(
EncogPersistedCollection.TYPE_RADIAL_BASIS_LAYER, out, obj,
false);
final RadialBasisFunctionLayer layer = (RadialBasisFunctionLayer) obj;
out.addProperty(BasicLayerPersistor.PROPERTY_NEURONS, layer
.getNeuronCount());
out.addProperty(BasicLayerPersistor.PROPERTY_X, layer.getX());
out.addProperty(BasicLayerPersistor.PROPERTY_Y, layer.getY());
saveRBF(out, layer);
out.endTag();
}
private void saveRBF(WriteXML out, RadialBasisFunctionLayer layer) {
out.beginTag(RadialBasisFunctionLayerPersistor.PROPERTY_RBF);
for (RadialBasisFunction rbf : layer.getRadialBasisFunction()) {
out.beginTag(rbf.getClass().getSimpleName());
out.addProperty(PROPERTY_CENTERS, rbf.getCenters(), rbf.getCenters().length);
out.addProperty(PROPERTY_PEAK, rbf.getPeak());
out.addProperty(PROPERTY_WIDTH, rbf.getWidth());
out.endTag();
}
out.endTag();
}
}