neuralconnection.java

MacroWeka扩展了著名数据挖掘工具weka

/*
 *    This program is free software; you can redistribute it and/or modify
 *    it under the terms of the GNU General Public License as published by
 *    the Free Software Foundation; either version 2 of the License, or
 *    (at your option) any later version.
 *
 *    This program is distributed in the hope that it will be useful,
 *    but WITHOUT ANY WARRANTY; without even the implied warranty of
 *    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 *    GNU General Public License for more details.
 *
 *    You should have received a copy of the GNU General Public License
 *    along with this program; if not, write to the Free Software
 *    Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
 */

/*
 *    NeuralConnection.java
 *    Copyright (C) 2000 Malcolm Ware
 */

package weka.classifiers.functions.neural;

import java.awt.Graphics;
import java.awt.Color;
import java.io.*;

/** 
 * Abstract unit in a NeuralNetwork.
 *
 * @author Malcolm Ware ([e-mail])
 * @version $Revision: 1.1 $
 */

public abstract class NeuralConnection implements Serializable {


  //bitwise flags for the types of unit.

  /** This unit is not connected to any others. */
  public static final int UNCONNECTED = 0;
  
  /** This unit is a pure input unit. */
  public static final int PURE_INPUT = 1;
  
  /** This unit is a pure output unit. */
  public static final int PURE_OUTPUT = 2;
  
  /** This unit is an input unit. */
  public static final int INPUT = 4;
  
  /** This unit is an output unit. */
  public static final int OUTPUT = 8;
  
  /** This flag is set once the unit has a connection. */
  public static final int CONNECTED = 16;



  /////The difference between pure and not is that pure is used to feed 
  /////the neural network the attribute values and the errors on the outputs
  /////Beyond that they do no calculations, and have certain restrictions
  /////on the connections they can make.



  /** The list of inputs to this unit. */
  protected NeuralConnection[] m_inputList;

  /** The list of outputs from this unit. */
  protected NeuralConnection[] m_outputList;

  /** The numbering for the connections at the other end of the input lines. */
  protected int[] m_inputNums;
  
  /** The numbering for the connections at the other end of the out lines. */
  protected int[] m_outputNums;

  /** The number of inputs. */
  protected int m_numInputs;

  /** The number of outputs. */
  protected int m_numOutputs;

  /** The output value for this unit, NaN if not calculated. */
  protected double m_unitValue;

  /** The error value for this unit, NaN if not calculated. */
  protected double m_unitError;
  
  /** True if the weights have already been updated. */
  protected boolean m_weightsUpdated;
  
  /** The string that uniquely (provided naming is done properly) identifies
   * this unit. */
  protected String m_id;

  /** The type of unit this is. */
  protected int m_type;

  /** The x coord of this unit purely for displaying purposes. */
  protected double m_x;
  
  /** The y coord of this unit purely for displaying purposes. */
  protected double m_y;
  

  
  
  /**
   * Constructs The unit with the basic connection information prepared for
   * use. 
   */
  public NeuralConnection(String id) {
    
    m_id = id;
    m_inputList = new NeuralConnection[0];
    m_outputList = new NeuralConnection[0];
    m_inputNums = new int[0];
    m_outputNums = new int[0];

    m_numInputs = 0;
    m_numOutputs = 0;

    m_unitValue = Double.NaN;
    m_unitError = Double.NaN;

    m_weightsUpdated = false;
    m_x = 0;
    m_y = 0;
    m_type = UNCONNECTED;
  }
  
  
  /**
   * @return The identity string of this unit.
   */
  public String getId() {
    return m_id;
  }

  /**
   * @return The type of this unit.
   */
  public int getType() {
    return m_type;
  }

  /**
   * @param t The new type of this unit.
   */
  public void setType(int t) {
    m_type = t;
  }

  /**
   * Call this to reset the unit for another run.
   * It is expected by that this unit will call the reset functions of all 
   * input units to it. It is also expected that this will not be done
   * if the unit has already been reset (or atleast appears to be).
   */
  public abstract void reset();

  /**
   * Call this to get the output value of this unit. 
   * @param calculate True if the value should be calculated if it hasn't been
   * already.
   * @return The output value, or NaN, if the value has not been calculated.
   */
  public abstract double outputValue(boolean calculate);

  /**
   * Call this to get the error value of this unit.
   * @param calculate True if the value should be calculated if it hasn't been
   * already.
   * @return The error value, or NaN, if the value has not been calculated.
   */
  public abstract double errorValue(boolean calculate);

  /**
   * Call this to get the weight value on a particular connection.
   * @param n The connection number to get the weight for, -1 if The threshold
   * weight should be returned.
   * @return This function will default to return 1. If overridden, it should
   * return the value for the specified connection or if -1 then it should 
   * return the threshold value. If no value exists for the specified 
   * connection, NaN will be returned.
   */
  public double weightValue(int n) {
    return 1;
  }

  /**
   * Call this function to update the weight values at this unit.
   * After the weights have been updated at this unit, All the
   * input connections will then be called from this to have their
   * weights updated.
   * @param l The learning Rate to use.
   * @param m The momentum to use.
   */
  public void updateWeights(double l, double m) {
    
    //the action the subclasses should perform is upto them 
    //but if they coverride they should make a call to this to
    //call the method for all their inputs.
    
    if (!m_weightsUpdated) {
      for (int noa = 0; noa < m_numInputs; noa++) {
	m_inputList[noa].updateWeights(l, m);
      }
      m_weightsUpdated = true;
    }
    
  }

  /**
   * Use this to get easy access to the inputs.
   * It is not advised to change the entries in this list
   * (use the connecting and disconnecting functions to do that)
   * @return The inputs list.
   */
  public NeuralConnection[] getInputs() {
    return m_inputList;
  }

  /**
   * Use this to get easy access to the outputs.
   * It is not advised to change the entries in this list
   * (use the connecting and disconnecting functions to do that)
   * @return The outputs list.
   */
  public NeuralConnection[] getOutputs() {
    return m_outputList;
  }

  /**
   * Use this to get easy access to the input numbers.
   * It is not advised to change the entries in this list
   * (use the connecting and disconnecting functions to do that)
   * @return The input nums list.
   */
  public int[] getInputNums() {
    return m_inputNums;
  }

  /**
   * Use this to get easy access to the output numbers.
   * It is not advised to change the entries in this list
   * (use the connecting and disconnecting functions to do that)
   * @return The outputs list.
   */
  public int[] getOutputNums() {
    return m_outputNums;
  }

  /**
   * @return the x coord.
   */
  public double getX() {
    return m_x;
  }
  
  /**
   * @return the y coord.
   */
  public double getY() {
    return m_y;
  }
  
  /**
   * @param x The new value for it's x pos.
   */
  public void setX(double x) {
    m_x = x;
  }
  
  /**
   * @param y The new value for it's y pos.
   */
  public void setY(double y) {
    m_y = y;
  }
  
  
  /**
   * Call this function to determine if the point at x,y is on the unit.
   * @param g The graphics context for font size info.
   * @param x The x coord.
   * @param y The y coord.
   * @param w The width of the display.
   * @param h The height of the display.
   * @return True if the point is on the unit, false otherwise.
   */
  public boolean onUnit(Graphics g, int x, int y, int w, int h) {

    int m = (int)(m_x * w);
    int c = (int)(m_y * h);
    if (x > m + 10 || x < m - 10 || y > c + 10 || y < c - 10) {
      return false;
    }
    return true;

  }
  
  /**
   * Call this function to draw the node.
   * @param g The graphics context.
   * @param w The width of the drawing area.
   * @param h The height of the drawing area.
   */
  public void drawNode(Graphics g, int w, int h) {
    
    if ((m_type & OUTPUT) == OUTPUT) {
      g.setColor(Color.orange);
    }
    else {
      g.setColor(Color.red);
    }
    g.fillOval((int)(m_x * w) - 9, (int)(m_y * h) - 9, 19, 19);
    g.setColor(Color.gray);
    g.fillOval((int)(m_x * w) - 5, (int)(m_y * h) - 5, 11, 11);
  }

  /**
   * Call this function to draw the node highlighted.
   * @param g The graphics context.
   * @param w The width of the drawing area.
   * @param h The height of the drawing area.
   */
  public void drawHighlight(Graphics g, int w, int h) {
   
    drawNode(g, w, h);
    g.setColor(Color.yellow);
    g.fillOval((int)(m_x * w) - 5, (int)(m_y * h) - 5, 11, 11);
  }

  /** 
   * Call this function to draw the nodes input connections.
   * @param g The graphics context.
   * @param w The width of the drawing area.
   * @param h The height of the drawing area.
   */
  public void drawInputLines(Graphics g, int w, int h) {

    g.setColor(Color.black);
    
    int px = (int)(m_x * w);
    int py = (int)(m_y * h);
    for (int noa = 0; noa < m_numInputs; noa++) {
      g.drawLine((int)(m_inputList[noa].getX() * w)
		 , (int)(m_inputList[noa].getY() * h)
		 , px, py);
    }
  }

  /**
   * Call this function to draw the nodes output connections.
   * @param g The graphics context.
   * @param w The width of the drawing area.
   * @param h The height of the drawing area.
   */
  public void drawOutputLines(Graphics g, int w, int h) {
    
    g.setColor(Color.black);