/*
* 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.ml.data.buffer.codec;
import java.util.Iterator;
import org.encog.ml.data.MLDataPair;
import org.encog.ml.data.MLDataSet;
import org.encog.ml.data.basic.BasicMLDataPair;
import org.encog.util.EngineArray;
/**
* A CODEC that works with the NeuralDataSet class.
*/
public class NeuralDataSetCODEC implements DataSetCODEC {
/**
* The number of input elements.
*/
private int inputSize;
/**
* The number of ideal elements.
*/
private int idealSize;
/**
* The dataset.
*/
private MLDataSet dataset;
/**
* The iterator used to read through the dataset.
*/
private Iterator<MLDataPair> iterator;
/**
* Construct a CODEC.
* @param theDataset The dataset to use.
*/
public NeuralDataSetCODEC(final MLDataSet theDataset) {
this.dataset = theDataset;
this.inputSize = theDataset.getInputSize();
this.idealSize = theDataset.getIdealSize();
}
/**
* {@inheritDoc}
*/
@Override
public final int getInputSize() {
return inputSize;
}
/**
* {@inheritDoc}
*/
@Override
public final int getIdealSize() {
return idealSize;
}
/**
* {@inheritDoc}
*/
@Override
public final boolean read(final double[] input, final double[] ideal, final double[] significance) {
if (!iterator.hasNext()) {
return false;
} else {
MLDataPair pair = iterator.next();
EngineArray.arrayCopy(pair.getInputArray(), input);
EngineArray.arrayCopy(pair.getIdealArray(), ideal);
significance[0] = pair.getSignificance();
return true;
}
}
/**
* {@inheritDoc}
*/
@Override
public final void write(final double[] input, final double[] ideal, double significance) {
MLDataPair pair = BasicMLDataPair.createPair(inputSize,
idealSize);
EngineArray.arrayCopy(input, pair.getIdealArray());
EngineArray.arrayCopy(ideal, pair.getIdealArray());
pair.setSignificance(significance);
}
/**
* {@inheritDoc}
*/
@Override
public final void prepareWrite(final int recordCount,
final int theInputSize, final int theIdealSize) {
this.inputSize = theInputSize;
this.idealSize = theIdealSize;
}
/**
* {@inheritDoc}
*/
@Override
public final void prepareRead() {
this.iterator = this.dataset.iterator();
}
/**
* {@inheritDoc}
*/
@Override
public void close() {
}
}