Package org.encog.neural.pattern

Source Code of org.encog.neural.pattern.CPNPattern

/*
* Encog(tm) Core v3.3 - Java Version
* http://www.heatonresearch.com/encog/
* https://github.com/encog/encog-java-core
* Copyright 2008-2014 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.pattern;

import org.encog.engine.network.activation.ActivationFunction;
import org.encog.ml.MLMethod;
import org.encog.neural.cpn.CPN;

/**
* Pattern that creates a CPN neural network.
*/
public class CPNPattern implements NeuralNetworkPattern {

  /**
   * The tag for the INSTAR layer.
   */
  public static final String TAG_INSTAR = "INSTAR";

  /**
   * The tag for the OUTSTAR layer.
   */
  public static final String TAG_OUTSTAR = "OUTSTAR";

  /**
   * The number of neurons in the instar layer.
   */
  private int instarCount;

  /**
   * The number of neurons in the outstar layer.
   */
  private int outstarCount;

  /**
   * The number of neurons in the hidden layer.
   */
  private int inputCount;


  /**
   * Not used, will throw an error. CPN networks already have a predefined
   * hidden layer called the instar layer.
   *
   * @param count
   *            NOT USED
   */
  public void addHiddenLayer(final int count) {
    throw new PatternError("A CPN already has a predefined hidden layer.  No additional"
        + "specification is needed.");
  }

  /**
   * Clear any parameters that were set.
   */
  public void clear() {
    this.inputCount = 0;
    this.instarCount = 0;
    this.outstarCount = 0;
  }

  /**
   * Generate the network.
   *
   * @return The generated network.
   */
  public MLMethod generate() {
    return new CPN(inputCount,instarCount,outstarCount,1);
  }

  /**
   * This method will throw an error. The CPN network uses predefined
   * activation functions.
   *
   * @param activation
   *            NOT USED
   */
  public void setActivationFunction(final ActivationFunction activation) {
    throw new PatternError("A CPN network will use the BiPolar & competitive activation "
        + "functions, no activation function needs to be specified.");
  }

  /**
   * Set the number of input neurons.
   *
   * @param count
   *            The input neuron count.
   */
  public void setInputNeurons(final int count) {
    this.inputCount = count;

  }

  /**
   * Set the number of neurons in the instar layer. This level is essentially
   * a hidden layer.
   *
   * @param instarCount
   *            The instar count.
   */
  public void setInstarCount(final int instarCount) {
    this.instarCount = instarCount;
  }

  /**
   * Set the number of output neurons. Calling this method maps to setting the
   * number of neurons in the outstar layer.
   *
   * @param count
   *            The count.
   */
  public void setOutputNeurons(final int count) {
    this.outstarCount = count;

  }

  /**
   * Set the number of neurons in the outstar level, this level is mapped to
   * the "output" level.
   *
   * @param outstarCount
   *            The outstar count.
   */
  public void setOutstarCount(final int outstarCount) {
    this.outstarCount = outstarCount;
  }

}
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