#include "genetic/explicitsimulation.h"
#include "genetic/operator.h"
#include "genetic/fitnessfunction.h"

#include <bu/random.h>
#include <bu/sio.h>

using namespace Bu;

Genetic::ExplicitSimulation::ExplicitSimulation( Genetic::Operator *pOper,
		Genetic::FitnessFunction *pFunc, int iPopSize, float fKeep,
		float fRandom, bool bKeepBest ) :
	pOper( pOper ),
	pFunc( pFunc ),
	iPopSize( iPopSize ),
	fKeep( fKeep ),
	fRandom( fRandom ),
	bKeepBest( bKeepBest )
{
	for( int j = 0; j < iPopSize; j++ )
	{
		xPop.addPhenotype( pOper->random() );
	}

	updateFitness();
}

Genetic::ExplicitSimulation::~ExplicitSimulation()
{
	delete pOper;
	delete pFunc;
}

void Genetic::ExplicitSimulation::timestep()
{
	PhenotypeList lNew;
	
	int iChildren = iPopSize*(1.0-fKeep-fRandom);

	// Create children
	for( int j = 0; j < iChildren; j++ )
	{
		PhenotypeList lParents;
		for( int k = 0; k < pOper->parentCount(); k++ )
			lParents.append( xPop.getPhenotype( selectWeighted() ) );
		lNew.append( pOper->mate( lParents ) );
	}

	// Select phenotypes for keeping
	int iKeep = iPopSize*fKeep;
	FitnessHash hTempFitness;
	for( int j = 0; j < iKeep; j++ )
	{
		Genetic::PhenotypeId id = selectWeighted();
		lNew.append( xPop.takePhenotype( id ) );
		hTempFitness.insert( id, hFitness.get( id ) );
		hFitness.erase( id );
		dTotalFitness -= hTempFitness.get( id );
	}

	if( bKeepBest && hFitness.has( uMaxFitness ) )
	{
		lNew.append( xPop.takePhenotype( uMaxFitness ) );
		hTempFitness.insert( uMaxFitness, hFitness.get( uMaxFitness ) );
		hFitness.erase( uMaxFitness );
		dTotalFitness -= hTempFitness.get( uMaxFitness );
	}

	// Fill in the remainder with random phenotypes
	while( lNew.getSize() < iPopSize )
	{
		lNew.append( pOper->random() );
	}

	// Refill the population
	hFitness = hTempFitness;
	xPop.clear();
	xPop.timestep();
	for( PhenotypeList::iterator i = lNew.begin(); i; i++ )
	{
		xPop.addPhenotype( *i );
	}

	updateFitness();
}

Genetic::PhenotypeId Genetic::ExplicitSimulation::selectWeighted()
{
	double dSel = Bu::Random::randNorm()*dTotalFitness;
	double dRun = 0.0;

	for( FitnessHash::iterator i = hFitness.begin(); i; i++ )
	{
		dRun += *i;
		if( dSel < dRun )
			return i.getKey();
	}

	sio << "Genetic::ExplicitSimulation::selectWeighted() - failed, picked max"
		<< sio.nl;

	return uMaxFitness;
}

void Genetic::ExplicitSimulation::updateFitness()
{
	dMinFitness = -1.0;
	dTotalFitness = 0.0;
	for( Population::iterator i = xPop.begin(); i; i++ )
	{
		double dFitness;
		if( hFitness.has( i.getKey() ) )
		{
			dFitness = hFitness.get( i.getKey() );
		}
		else
		{
			dFitness = (*pFunc)( *i );
			if( dFitness < 0.0 )
				dFitness = 0.0;
			hFitness.insert( i.getKey(), dFitness );
		}
		dTotalFitness += dFitness;
		if( dMinFitness < 0.0 )
		{
			dMinFitness = dMaxFitness = dFitness;
			uMaxFitness = i.getKey();
		}
		else if( dMinFitness > dFitness )
		{
			dMinFitness = dFitness;
		}
		else if( dMaxFitness < dFitness )
		{
			dMaxFitness = dFitness;
			uMaxFitness = i.getKey();
		}
	}
}