/*
* 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.hyperneat.substrate;
/**
* Produce substrates for various topologies. Currently provides the sandwich
* topology. You can create any topology you wish, this is simply a convienance
* method.
*
* -----------------------------------------------------------------------------
* http://www.cs.ucf.edu/~kstanley/ Encog's NEAT implementation was drawn from
* the following three Journal Articles. For more complete BibTeX sources, see
* NEATNetwork.java.
*
* Evolving Neural Networks Through Augmenting Topologies
*
* Generating Large-Scale Neural Networks Through Discovering Geometric
* Regularities
*
* Automatic feature selection in neuroevolution
*/
public class SubstrateFactory {
/**
* Create a sandwich substrate. A sandwich has an input layer connected
* directly to an output layer, both are square.
*
* @param inputEdgeSize The input edge size.
* @param outputEdgeSize The output edge size.
* @return The substrate.
*/
public static Substrate factorSandwichSubstrate(int inputEdgeSize,
int outputEdgeSize) {
Substrate result = new Substrate(3);
double inputTick = 2.0 / inputEdgeSize;
double outputTick = 2.0 / outputEdgeSize;
double inputOrig = -1.0 + (inputTick / 2.0);
double outputOrig = -1.0 + (outputTick / 2.0);
// create the input layer
for (int row = 0; row < inputEdgeSize; row++) {
for (int col = 0; col < inputEdgeSize; col++) {
SubstrateNode inputNode = result.createInputNode();
inputNode.getLocation()[0] = -1;
inputNode.getLocation()[1] = inputOrig + (row * inputTick);
inputNode.getLocation()[2] = inputOrig + (col * inputTick);
}
}
// create the output layer (and connect to input layer)
for (int orow = 0; orow < outputEdgeSize; orow++) {
for (int ocol = 0; ocol < outputEdgeSize; ocol++) {
SubstrateNode outputNode = result.createOutputNode();
outputNode.getLocation()[0] = 1;
outputNode.getLocation()[1] = outputOrig + (orow * outputTick);
outputNode.getLocation()[2] = outputOrig + (ocol * outputTick);
// link this output node to every input node
for (SubstrateNode inputNode : result.getInputNodes()) {
result.createLink(inputNode, outputNode);
}
}
}
return result;
}
}