Package org.encog.neural.pattern

Source Code of org.encog.neural.pattern.ART1Pattern

/*
* 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.art.ART1;

/**
* Pattern to create an ART-1 neural network.
*/
public class ART1Pattern implements NeuralNetworkPattern {

  /**
   * The number of input neurons.
   */
  private int inputNeurons;

  /**
   * The number of output neurons.
   */
  private int outputNeurons;

  /**
   * A parameter for F1 layer.
   */
  private double a1 = 1;

  /**
   * B parameter for F1 layer.
   */
  private double b1 = 1.5;

  /**
   * C parameter for F1 layer.
   */
  private double c1 = 5;

  /**
   * D parameter for F1 layer.
   */
  private double d1 = 0.9;

  /**
   * L parameter for net.
   */
  private double l = 3;

  /**
   * The vigilance parameter.
   */
  private double vigilance = 0.9;

  /**
   * This will fail, hidden layers are not supported for this type of network.
   *
   * @param count
   *            Not used.
   */
  public void addHiddenLayer(final int count) {
    throw new PatternError("A ART1 network has no hidden layers.");
  }

  /**
   * Clear any properties set for this network.
   */
  public void clear() {
    this.inputNeurons = 0;
    this.outputNeurons = 0;

  }

  /**
   * Generate the neural network.
   *
   * @return The generated neural network.
   */
  public MLMethod generate() {

    ART1 art = new ART1(this.inputNeurons, this.outputNeurons);
    art.setA1(this.a1);
    art.setB1(this.b1);
    art.setC1(this.c1);
    art.setD1(this.d1);
    art.setL(this.l);
    art.setVigilance(this.vigilance);
    return art;
  }

  /**
   * @return The A1 parameter.
   */
  public double getA1() {
    return this.a1;
  }

  /**
   * @return The B1 parameter.
   */
  public double getB1() {
    return this.b1;
  }

  /**
   * @return The C1 parameter.
   */
  public double getC1() {
    return this.c1;
  }

  /**
   * @return The D1 parameter.
   */
  public double getD1() {
    return this.d1;
  }

  /**
   * @return The L parameter.
   */
  public double getL() {
    return this.l;
  }

  /**
   * @return The vigilance for the network.
   */
  public double getVigilance() {
    return this.vigilance;
  }

  /**
   * Set the A1 parameter.
   *
   * @param a1
   *            The new value.
   */
  public void setA1(final double a1) {
    this.a1 = a1;
  }

  /**
   * This method will throw an error, you can't set the activation function
   * for an ART1. type network.
   *
   * @param activation
   *            The activation function.
   */
  public void setActivationFunction(final ActivationFunction activation) {
    throw new PatternError("Can't set the activation function for an ART1.");
  }

  /**
   * Set the B1 parameter.
   *
   * @param b1
   *            The new value.
   */
  public void setB1(final double b1) {
    this.b1 = b1;
  }

  /**
   * Set the C1 parameter.
   *
   * @param c1
   *            The new value.
   */
  public void setC1(final double c1) {
    this.c1 = c1;
  }

  /**
   * Set the D1 parameter.
   *
   * @param d1
   *            The new value.
   */
  public void setD1(final double d1) {
    this.d1 = d1;
  }

  /**
   * Set the input neuron (F1 layer) count.
   *
   * @param count
   *            The input neuron count.
   */
  public void setInputNeurons(final int count) {
    this.inputNeurons = count;
  }

  /**
   * Set the L parameter.
   *
   * @param l
   *            The new value.
   */
  public void setL(final double l) {
    this.l = l;
  }

  /**
   * Set the output neuron (F2 layer) count.
   *
   * @param count
   *            The output neuron count.
   */
  public void setOutputNeurons(final int count) {
    this.outputNeurons = count;
  }

  /**
   * Set the vigilance for the network.
   *
   * @param vigilance
   *            The new value.
   */
  public void setVigilance(final double vigilance) {
    this.vigilance = vigilance;
  }
}
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