cinnovation.cpp

人工神经网络neat实现vc++6.0编译

#include "CInnovation.h"

//---------------------------------- ctor --------------------------------
//
//  given a series of start genes and start neurons this ctor adds
//  all the appropriate innovations.
//------------------------------------------------------------------------
CInnovation::CInnovation(vector<SLinkGene>   start_genes,
                         vector<SNeuronGene> start_neurons)
{
	m_NextNeuronID		  = 0;
	m_NextInnovationNum = 0;

	//add the neurons
  for (int nd=0; nd<start_neurons.size(); ++nd)
  {
    m_vecInnovs.push_back(SInnovation(start_neurons[nd],
                                      m_NextInnovationNum++,
                                      m_NextNeuronID++));
  }

  //add the links
  for (int cGen = 0; cGen<start_genes.size(); ++cGen) 
	{
		SInnovation NewInnov(start_genes[cGen].FromNeuron,
                         start_genes[cGen].ToNeuron,
                         new_link,
                         m_NextInnovationNum);

		m_vecInnovs.push_back(NewInnov);

    ++m_NextInnovationNum;

	}
}

//---------------------------CheckInnovation------------------------------
//
//	checks to see if this innovation has already occurred. If it has it
//	returns the innovation ID. If not it returns a negative value. 
//------------------------------------------------------------------------
int CInnovation::CheckInnovation(int in, int out, innov_type type)
{
  //iterate through the innovations looking for a match on all
  //three parameters
	for (int inv=0; inv<m_vecInnovs.size(); ++inv)
	{
    if ( (m_vecInnovs[inv].NeuronIn == in)   && 
         (m_vecInnovs[inv].NeuronOut == out) && 
         (m_vecInnovs[inv].InnovationType == type))
		{			
			//found a match so assign this innovation number to id
			return m_vecInnovs[inv].InnovationID;
		}
	}
	
	//if no match return a negative value
  return -1;
}

//--------------------------CreateNewInnovation---------------------------
//
//	creates a new innovation and returns its ID
//------------------------------------------------------------------------
int CInnovation::CreateNewInnovation(int in, int out, innov_type type)
{
	SInnovation new_innov(in, out, type, m_NextInnovationNum);
	
	if (type == new_neuron)
	{
		new_innov.NeuronID = m_NextNeuronID;
		
		++m_NextNeuronID;
	}

  m_vecInnovs.push_back(new_innov);

  ++m_NextInnovationNum;
	
	return (m_NextNeuronID-1);
}

//------------------------------------------------------------------------
//
//  as above but includes adding x/y position of new neuron
//------------------------------------------------------------------------
int CInnovation::CreateNewInnovation(int          from,
                                     int          to,
                                     innov_type   InnovType,
                                     neuron_type  NeuronType,
                                     double       x,
                                     double       y)
{ 

	SInnovation new_innov(from, to, InnovType, m_NextInnovationNum, NeuronType, x, y);
	
	if (InnovType == new_neuron)
	{
		new_innov.NeuronID = m_NextNeuronID;
		
		++m_NextNeuronID;
	}

  m_vecInnovs.push_back(new_innov);

  ++m_NextInnovationNum;
	
	return (m_NextNeuronID-1);

}


//------------------------------- CreateNeuronFromID -----------------------
//
//  given a neuron ID this function returns a clone of that neuron
//------------------------------------------------------------------------
SNeuronGene CInnovation::CreateNeuronFromID(int NeuronID)
{
  SNeuronGene temp(hidden,0,0,0);

  for (int inv=0; inv<m_vecInnovs.size(); ++inv)
  {
    if (m_vecInnovs[inv].NeuronID == NeuronID)
    {
      temp.NeuronType = m_vecInnovs[inv].NeuronType;
      temp.iID      = m_vecInnovs[inv].NeuronID;
      temp.dSplitY  = m_vecInnovs[inv].dSplitY;
      temp.dSplitX  = m_vecInnovs[inv].dSplitX;

      return temp;
    }
  }

  return temp;
}