From 1f7c135934b6604c5409d4b6f34861105c0a64cb Mon Sep 17 00:00:00 2001
From: Mike Buland <mike@xagasoft.com>
Date: Mon, 9 Jul 2012 12:01:50 -0600
Subject: It works well enough to solve polynomial maxima.

---
 src/explicitsimulation.cpp | 139 +++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 139 insertions(+)
 create mode 100644 src/explicitsimulation.cpp

(limited to 'src/explicitsimulation.cpp')

diff --git a/src/explicitsimulation.cpp b/src/explicitsimulation.cpp
new file mode 100644
index 0000000..281e7e5
--- /dev/null
+++ b/src/explicitsimulation.cpp
@@ -0,0 +1,139 @@
+#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();
+		}
+	}
+}
-- 
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