/* * 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.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 int getInputSize() { return inputSize; } /** * {@inheritDoc} */ @Override public int getIdealSize() { return idealSize; } /** * {@inheritDoc} */ @Override public 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 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 void prepareWrite(final int recordCount, final int theInputSize, final int theIdealSize) { this.inputSize = theInputSize; this.idealSize = theIdealSize; } /** * {@inheritDoc} */ @Override public void prepareRead() { this.iterator = this.dataset.iterator(); } /** * {@inheritDoc} */ @Override public void close() { } }