neuralconnection.java

MacroWeka扩展了著名数据挖掘工具weka

    
    int px = (int)(m_x * w);
    int py = (int)(m_y * h);
    for (int noa = 0; noa < m_numOutputs; noa++) {
      g.drawLine(px, py
		 , (int)(m_outputList[noa].getX() * w)
		 , (int)(m_outputList[noa].getY() * h));
    }
  }


  /**
   * This will connect the specified unit to be an input to this unit.
   * @param i The unit.
   * @param n It's connection number for this connection.
   * @return True if the connection was made, false otherwise.
   */
  protected boolean connectInput(NeuralConnection i, int n) {
    
    for (int noa = 0; noa < m_numInputs; noa++) {
      if (i == m_inputList[noa]) {
	return false;
      }
    }
    if (m_numInputs >= m_inputList.length) {
      //then allocate more space to it.
      allocateInputs();
    }
    m_inputList[m_numInputs] = i;
    m_inputNums[m_numInputs] = n;
    m_numInputs++;
    return true;
  }
  
  /**
   * This will allocate more space for input connection information
   * if the arrays for this have been filled up.
   */
  protected void allocateInputs() {
    
    NeuralConnection[] temp1 = new NeuralConnection[m_inputList.length + 15];
    int[] temp2 = new int[m_inputNums.length + 15];

    for (int noa = 0; noa < m_numInputs; noa++) {
      temp1[noa] = m_inputList[noa];
      temp2[noa] = m_inputNums[noa];
    }
    m_inputList = temp1;
    m_inputNums = temp2;
  }

  /** 
   * This will connect the specified unit to be an output to this unit.
   * @param o The unit.
   * @param n It's connection number for this connection.
   * @return True if the connection was made, false otherwise.
   */
  protected boolean connectOutput(NeuralConnection o, int n) {
    
    for (int noa = 0; noa < m_numOutputs; noa++) {
      if (o == m_outputList[noa]) {
	return false;
      }
    }
    if (m_numOutputs >= m_outputList.length) {
      //then allocate more space to it.
      allocateOutputs();
    }
    m_outputList[m_numOutputs] = o;
    m_outputNums[m_numOutputs] = n;
    m_numOutputs++;
    return true;
  }
  
  /**
   * Allocates more space for output connection information
   * if the arrays have been filled up.
   */
  protected void allocateOutputs() {
    
    NeuralConnection[] temp1 
      = new NeuralConnection[m_outputList.length + 15];
    
    int[] temp2 = new int[m_outputNums.length + 15];
    
    for (int noa = 0; noa < m_numOutputs; noa++) {
      temp1[noa] = m_outputList[noa];
      temp2[noa] = m_outputNums[noa];
    }
    m_outputList = temp1;
    m_outputNums = temp2;
  }
  
  /**
   * This will disconnect the input with the specific connection number
   * From this node (only on this end however).
   * @param i The unit to disconnect.
   * @param n The connection number at the other end, -1 if all the connections
   * to this unit should be severed.
   * @return True if the connection was removed, false if the connection was 
   * not found.
   */
  protected boolean disconnectInput(NeuralConnection i, int n) {
    
    int loc = -1;
    boolean removed = false;
    do {
      loc = -1;
      for (int noa = 0; noa < m_numInputs; noa++) {
	if (i == m_inputList[noa] && (n == -1 || n == m_inputNums[noa])) {
	  loc = noa;
	  break;
	}
      }
      
      if (loc >= 0) {
	for (int noa = loc+1; noa < m_numInputs; noa++) {
	  m_inputList[noa-1] = m_inputList[noa];
	  m_inputNums[noa-1] = m_inputNums[noa];
	  //set the other end to have the right connection number.
	  m_inputList[noa-1].changeOutputNum(m_inputNums[noa-1], noa-1);
	}
	m_numInputs--;
	removed = true;
      }
    } while (n == -1 && loc != -1);

    return removed;
  }

  /**
   * This function will remove all the inputs to this unit.
   * In doing so it will also terminate the connections at the other end.
   */
  public void removeAllInputs() {
    
    for (int noa = 0; noa < m_numInputs; noa++) {
      //this command will simply remove any connections this node has
      //with the other in 1 go, rather than seperately.
      m_inputList[noa].disconnectOutput(this, -1);
    }
    
    //now reset the inputs.
    m_inputList = new NeuralConnection[0];
    setType(getType() & (~INPUT));
    if (getNumOutputs() == 0) {
      setType(getType() & (~CONNECTED));
    }
    m_inputNums = new int[0];
    m_numInputs = 0;
    
  }

 

  /**
   * Changes the connection value information for one of the connections.
   * @param n The connection number to change.
   * @param v The value to change it to.
   */
  protected void changeInputNum(int n, int v) {
    
    if (n >= m_numInputs || n < 0) {
      return;
    }

    m_inputNums[n] = v;
  }
  
  /**
   * This will disconnect the output with the specific connection number
   * From this node (only on this end however).
   * @param o The unit to disconnect.
   * @param n The connection number at the other end, -1 if all the connections
   * to this unit should be severed.
   * @return True if the connection was removed, false if the connection was
   * not found.
   */  
  protected boolean disconnectOutput(NeuralConnection o, int n) {
    
    int loc = -1;
    boolean removed = false;
    do {
      loc = -1;
      for (int noa = 0; noa < m_numOutputs; noa++) {
	if (o == m_outputList[noa] && (n == -1 || n == m_outputNums[noa])) {
	  loc =noa;
	  break;
	}
      }
      
      if (loc >= 0) {
	for (int noa = loc+1; noa < m_numOutputs; noa++) {
	  m_outputList[noa-1] = m_outputList[noa];
	  m_outputNums[noa-1] = m_outputNums[noa];

	  //set the other end to have the right connection number
	  m_outputList[noa-1].changeInputNum(m_outputNums[noa-1], noa-1);
	}
	m_numOutputs--;
	removed = true;
      }
    } while (n == -1 && loc != -1);
    
    return removed;
  }

  /**
   * This function will remove all outputs to this unit.
   * In doing so it will also terminate the connections at the other end.
   */
  public void removeAllOutputs() {
    
    for (int noa = 0; noa < m_numOutputs; noa++) {
      //this command will simply remove any connections this node has
      //with the other in 1 go, rather than seperately.
      m_outputList[noa].disconnectInput(this, -1);
    }
    
    //now reset the inputs.
    m_outputList = new NeuralConnection[0];
    m_outputNums = new int[0];
    setType(getType() & (~OUTPUT));
    if (getNumInputs() == 0) {
      setType(getType() & (~CONNECTED));
    }
    m_numOutputs = 0;
    
  }

  /**
   * Changes the connection value information for one of the connections.
   * @param n The connection number to change.
   * @param v The value to change it to.
   */
  protected void changeOutputNum(int n, int v) {
    
    if (n >= m_numOutputs || n < 0) {
      return;
    }

    m_outputNums[n] = v;
  }
  
  /**
   * @return The number of input connections.
   */
  public int getNumInputs() {
    return m_numInputs;
  }

  /**
   * @return The number of output connections.
   */
  public int getNumOutputs() {
    return m_numOutputs;
  }


  /**
   * Connects two units together.
   * @param s The source unit.
   * @param t The target unit.
   * @return True if the units were connected, false otherwise.
   */
  public static boolean connect(NeuralConnection s, NeuralConnection t) {
    
    if (s == null || t == null) {
      return false;
    }
    //this ensures that there is no existing connection between these 
    //two units already. This will also cause the current weight there to be 
    //lost
 
    disconnect(s, t);
    if (s == t) {
      return false;
    }
    if ((t.getType() & PURE_INPUT) == PURE_INPUT) {
      return false;   //target is an input node.
    }
    if ((s.getType() & PURE_OUTPUT) == PURE_OUTPUT) {
      return false;   //source is an output node
    }
    if ((s.getType() & PURE_INPUT) == PURE_INPUT 
	&& (t.getType() & PURE_OUTPUT) == PURE_OUTPUT) {      
      return false;   //there is no actual working node in use
    }
    if ((t.getType() & PURE_OUTPUT) == PURE_OUTPUT && t.getNumInputs() > 0) {
      return false; //more than 1 node is trying to feed a particular output
    }

    if ((t.getType() & PURE_OUTPUT) == PURE_OUTPUT &&
	(s.getType() & OUTPUT) == OUTPUT) {
      return false; //an output node already feeding out a final answer
    }

    if (!s.connectOutput(t, t.getNumInputs())) {
      return false;
    }
    if (!t.connectInput(s, s.getNumOutputs() - 1)) {
      
      s.disconnectOutput(t, t.getNumInputs());
      return false;

    }

    //now ammend the type.
    if ((s.getType() & PURE_INPUT) == PURE_INPUT) {
      t.setType(t.getType() | INPUT);
    }
    else if ((t.getType() & PURE_OUTPUT) == PURE_OUTPUT) {
      s.setType(s.getType() | OUTPUT);
    }
    t.setType(t.getType() | CONNECTED);
    s.setType(s.getType() | CONNECTED);
    return true;
  }

  /**
   * Disconnects two units.
   * @param s The source unit.
   * @param t The target unit.
   * @return True if the units were disconnected, false if they weren't
   * (probably due to there being no connection).
   */
  public static boolean disconnect(NeuralConnection s, NeuralConnection t) {
    
    if (s == null || t == null) {
      return false;
    }

    boolean stat1 = s.disconnectOutput(t, -1);
    boolean stat2 = t.disconnectInput(s, -1);
    if (stat1 && stat2) {
      if ((s.getType() & PURE_INPUT) == PURE_INPUT) {
	t.setType(t.getType() & (~INPUT));
      }
      else if ((t.getType() & (PURE_OUTPUT)) == PURE_OUTPUT) {
	s.setType(s.getType() & (~OUTPUT));
      }
      if (s.getNumInputs() == 0 && s.getNumOutputs() == 0) {
	s.setType(s.getType() & (~CONNECTED));
      }
      if (t.getNumInputs() == 0 && t.getNumOutputs() == 0) {
	t.setType(t.getType() & (~CONNECTED));
      }
    }
    return stat1 && stat2;
  }
}