/*
* 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.neural.networks.training.cross;
import org.encog.neural.flat.FlatNetwork;
import org.encog.util.EngineArray;
/**
* The network for one fold of a cross validation.
*/
public class NetworkFold {
/**
* The weights for this fold.
*/
private final double[] weights;
/**
* The output for this fold.
*/
private final double[] output;
/**
* Construct a fold from the specified flat network.
* @param flat THe flat network.
*/
public NetworkFold(final FlatNetwork flat) {
this.weights = EngineArray.arrayCopy(flat.getWeights());
this.output = EngineArray.arrayCopy(flat.getLayerOutput());
}
/**
* Copy weights and output to the network.
* @param target The network to copy to.
*/
public final void copyToNetwork(final FlatNetwork target) {
EngineArray.arrayCopy(this.weights, target.getWeights());
EngineArray.arrayCopy(this.output, target.getLayerOutput());
}
/**
* Copy the weights and output from the network.
* @param source The network to copy from.
*/
public final void copyFromNetwork(final FlatNetwork source) {
EngineArray.arrayCopy(source.getWeights(), this.weights);
EngineArray.arrayCopy(source.getLayerOutput(), this.output);
}
/**
* @return The network weights.
*/
public final double[] getWeights() {
return weights;
}
/**
* @return The network output.
*/
public final double[] getOutput() {
return output;
}
}