template <class T> int
GA3DArrayAlleleGenome<T>::resize(int w, int h, int d){
unsigned int oldx = nx;
unsigned int oldy = ny;
unsigned int oldz = nz;
GA3DArrayGenome<T>::resize(w,h,d);
// set new elements to proper randomly selected values
if(nx > oldx && ny > oldy){
int z=GAMin(oldz,nz);
for(int k=z-1; k>=0; k--){
int j;
for(j=oldy-1; j>=0; j--)
for(unsigned int i=oldx; i<nx; i++)
a[k*ny*nx+j*nx+i] = aset[(k*ny*nx+j*nx+i) % naset].allele();
for(j=oldy; j<(int)ny; j++)
for(unsigned int i=0; i<nx; i++)
a[k*ny*nx+j*nx+i] = aset[(k*ny*nx+j*nx+i) % naset].allele();
}
}
else if(nx > oldx){
int z=GAMin(oldz,nz);
for(int k=z-1; k>=0; k--)
for(int j=ny-1; j>=0; j--)
for(unsigned int i=oldx; i<nx; i++)
a[k*ny*nx+j*nx+i] = aset[(k*ny*nx+j*nx+i) % naset].allele();
}
else if(ny > oldy){
int z=GAMin(oldz,nz);
for(int k=z-1; k>=0; k--)
for(unsigned int j=oldy; j<ny; j++)
for(unsigned int i=0; i<nx; i++)
a[k*ny*nx+j*nx+i] = aset[(k*ny*nx+j*nx+i) % naset].allele();
}
if(nz > oldz){ // change in depth is always new elements
for(unsigned int i=nx*ny*oldz; i<nx*ny*nz; i++)
a[i] = aset[i % naset].allele();
}
return sz;
}
void CCombineGenome::Initializer( GAGenome& g)
{
CCombineGenome& genome = (CCombineGenome&)g;
if (m_inputData != NULL)
{
ComRuleData* pData = (ComRuleData*)m_inputData;
size_t objNum = pData->m_inputData.size();
map<YK_ID,std::list<YK_ID>>::iterator objIter = pData->m_inputData.begin();
if (pData->m_ObjGroupLimit.empty())
{
int averageSize = objNum / genome.npaths();
if (averageSize > 0)
{
for (int i = 0; objIter != pData->m_inputData.end(); ++i,++objIter)
{
int index = (i / averageSize) < genome.npaths() ? (i / averageSize ) : (genome.npaths()-1) ;
genome.path(index).insert(objIter->first,GAListBASE::TAIL);
}
}
}else
{
for (; objIter != pData->m_inputData.end(); ++objIter)
{
YK_LLONG objId = objIter->first;
std::set<YKString> validSet = pData->m_ObjGroupLimit[objId];
if (!validSet.empty())
{
if (validSet.size() == 1)
{
genome.path(m_groupToIndexMap[*validSet.begin()]).insert(objIter->first,GAListBASE::TAIL);
}else
{
int maxIndex = GAMin(validSet.size()-1,genome.npaths()-1);
int index = GARandomInt(0,maxIndex);
std::set<YKString>::iterator indexIter = validSet.begin();
advance(indexIter,index);
if (indexIter != validSet.end())
{
int pathNum = m_groupToIndexMap[*indexIter];
genome.path(pathNum).insert(objId,GAListBASE::TAIL);
}
}
}
}
}
}
}
/// Do the scaling on the population. Like the statistics and diversity, this
/// method does not change the contents of the population, but it does change
/// the values of the status members of the object. So we allow it to work on
/// a const population.
void
GAPopulation::scale(GABoolean flag) const
{
if(scaled == gaTrue && flag != gaTrue)
{
return;
}
GAPopulation* This = (GAPopulation*)this;
if(n > 0)
{
sclscm->evaluate(*This);
float tmpsum;
This->fitMin = This->fitMax = tmpsum = sind[0]->fitness();
unsigned int i;
for(i = 1; i < n; i++)
{
tmpsum += sind[i]->fitness();
This->fitMax = GAMax(fitMax, sind[i]->fitness());
This->fitMin = GAMin(fitMin, sind[i]->fitness());
}
float tmpave = tmpsum / n;
This->fitAve = tmpave;
This->fitSum = tmpsum; /// if scores are huge we'll lose data here
float tmpvar = 0.0;
if(n > 1)
{
for(i = 0; i < n; i++)
{
float s = sind[i]->fitness() - This->fitAve;
s *= s;
tmpvar += s;
}
tmpvar /= (n - 1);
}
This->fitDev = (float)sqrt(tmpvar);
This->fitVar = tmpvar; /// could lose data if huge variance
}
else
{
This->fitMin = This->fitMax = This->fitSum = 0.0;
This->fitVar = This->fitDev = 0.0;
}
This->scaled = gaTrue;
This->ssorted = gaFalse;
}
/// Evaluate each member of the population and store basic population statistics
/// in the member variables. It is OK to run this on a const object - it
/// changes to physical state of the population, but not the logical state.
/// The partial sums are normalized to the range [0,1] so that they can be
/// used whether the population is sorted as low-is-best or high-is-best.
/// Individual 0 is always the best individual, and the partial sums are
/// calculated so that the worst individual has the smallest partial sum. All
/// of the partial sums add to 1.0.
void
GAPopulation::statistics(GABoolean flag) const
{
if(statted == gaTrue && flag != gaTrue)
{
return;
}
GAPopulation * This = (GAPopulation *)this;
if(n > 0)
{
float tmpsum;
This->rawMin = This->rawMax = tmpsum = rind[0]->score();
unsigned int i;
for(i = 1; i < n; i++)
{
float scr = rind[i]->score();
tmpsum += scr;
This->rawMax = GAMax(rawMax, scr);
This->rawMin = GAMin(rawMin, scr);
}
float tmpave = tmpsum / n;
This->rawAve = tmpave;
This->rawSum = tmpsum; /// if scores are huge we'll lose data here
float tmpvar = 0.0;
if(n > 1)
{
for(i = 0; i < n; i++)
{
float s = rind[i]->score() - This->rawAve;
s *= s;
tmpvar += s;
}
tmpvar /= (n - 1);
}
This->rawDev = (float)sqrt(tmpvar);
This->rawVar = tmpvar; /// could lose data if huge variance
}
else
{
This->rawMin = This->rawMax = This->rawSum = 0.0;
This->rawDev = This->rawVar = 0.0;
}
This->statted = gaTrue;
}
template <class T> int
GA3DArrayGenome<T>::resize(int w, int h, int d)
{
if(w == (int)nx && h == (int)ny && d == (int)nz) return sz;
if(w == GAGenome::ANY_SIZE)
w = GARandomInt(minX, maxX);
else if(w < 0)
w = nx; // do nothing
else if(minX == maxX)
minX=maxX = w;
else{
if(w < (int)minX) w=minX;
if(w > (int)maxX) w=maxX;
}
if(h == GAGenome::ANY_SIZE)
h = GARandomInt(minY, maxY);
else if(h < 0)
h = ny; // do nothing
else if(minY == maxY)
minY=maxY = h;
else{
if(h < (int)minY) h=minY;
if(h > (int)maxY) h=maxY;
}
if(d == GAGenome::ANY_SIZE)
d = GARandomInt(minZ, maxZ);
else if(d < 0)
d = nz; // do nothing
else if(minZ == maxZ)
minZ=maxZ = d;
else{
if(d < (int)minZ) d=minZ;
if(d > (int)maxZ) d=maxZ;
}
if(w < (int)nx && h < (int)ny){
int z=GAMin((int)nz,d);
for(int k=0; k<z; k++)
for(int j=0; j<h; j++)
GAArray<T>::move(k*h*w+j*w,k*ny*nx+j*nx,w);
}
else if(w < (int)nx){
int z=GAMin((int)nz,d);
for(int k=0; k<z; k++)
for(int j=0; j<(int)ny; j++)
GAArray<T>::move(k*ny*w+j*w,k*ny*nx+j*nx,w);
}
else if(h < (int)ny){
int z=GAMin((int)nz,d);
for(int k=0; k<z; k++)
for(int j=0; j<h; j++)
GAArray<T>::move(k*h*nx+j*nx,k*ny*nx+j*nx,nx);
}
GAArray<T>::size(w*h*d);
if(w > (int)nx && h > (int)ny){
int z=GAMin((int)nz,d);
for(int k=z-1; k>=0; k--)
for(int j=ny-1; j>=0; j--)
GAArray<T>::move(k*h*w+j*w,k*ny*nx+j*nx,nx);
}
else if(w > (int)nx){
int z=GAMin((int)nz,d);
for(int k=z-1; k>=0; k--)
for(int j=h-1; j>=0; j--)
GAArray<T>::move(k*h*w+j*w,k*h*nx+j*nx,nx);
}
else if(h > (int)ny){
int z=GAMin((int)nz,d);
for(int k=z-1; k>=0; k--)
for(int j=ny-1; j>=0; j--)
GAArray<T>::move(k*h*w+j*w,k*ny*w+j*w,w);
}
nx = w; ny = h; nz = d;
_evaluated = gaFalse;
return sz;
}
// Pick a single point in the 3D block and grab alternating quadrants for each
// child. If the children are resizable, this crossover does clipping.
template <class T> int
GA3DArrayGenome<T>::
OnePointCrossover(const GAGenome& p1, const GAGenome& p2,
GAGenome* c1, GAGenome* c2){
GA3DArrayGenome<T> &mom=(GA3DArrayGenome<T> &)p1;
GA3DArrayGenome<T> &dad=(GA3DArrayGenome<T> &)p2;
int nc=0;
unsigned int momsitex, momlenx, momsitey, momleny, momsitez, momlenz;
unsigned int dadsitex, dadlenx, dadsitey, dadleny, dadsitez, dadlenz;
unsigned int sitex, lenx, sitey, leny, sitez, lenz;
if(c1 && c2){
GA3DArrayGenome<T> &sis=(GA3DArrayGenome<T> &)*c1;
GA3DArrayGenome<T> &bro=(GA3DArrayGenome<T> &)*c2;
if(sis.resizeBehaviour(GAGenome::WIDTH) == GAGenome::FIXED_SIZE &&
bro.resizeBehaviour(GAGenome::WIDTH) == GAGenome::FIXED_SIZE){
if(mom.width() != dad.width() ||
sis.width() != bro.width() ||
sis.width() != mom.width()){
GAErr(GA_LOC, mom.className(), "one-point cross", gaErrSameLengthReqd);
return nc;
}
sitex = momsitex = dadsitex = GARandomInt(0, mom.width());
lenx = momlenx = dadlenx = mom.width() - momsitex;
}
else if(sis.resizeBehaviour(GAGenome::WIDTH) == GAGenome::FIXED_SIZE ||
bro.resizeBehaviour(GAGenome::WIDTH) == GAGenome::FIXED_SIZE){
GAErr(GA_LOC, mom.className(), "one-point cross", gaErrSameBehavReqd);
return nc;
}
else{
momsitex = GARandomInt(0, mom.width());
dadsitex = GARandomInt(0, dad.width());
momlenx = mom.width() - momsitex;
dadlenx = dad.width() - dadsitex;
sitex = GAMin(momsitex, dadsitex);
lenx = GAMin(momlenx, dadlenx);
}
if(sis.resizeBehaviour(GAGenome::HEIGHT) == GAGenome::FIXED_SIZE &&
bro.resizeBehaviour(GAGenome::HEIGHT) == GAGenome::FIXED_SIZE){
if(mom.height() != dad.height() ||
sis.height() != bro.height() ||
sis.height() != mom.height()){
GAErr(GA_LOC, mom.className(), "one-point cross", gaErrSameLengthReqd);
return nc;
}
sitey = momsitey = dadsitey = GARandomInt(0, mom.height());
leny = momleny = dadleny = mom.height() - momsitey;
}
else if(sis.resizeBehaviour(GAGenome::HEIGHT) == GAGenome::FIXED_SIZE ||
bro.resizeBehaviour(GAGenome::HEIGHT) == GAGenome::FIXED_SIZE){
GAErr(GA_LOC, mom.className(), "one-point cross", gaErrSameBehavReqd);
return nc;
}
else{
momsitey = GARandomInt(0, mom.height());
dadsitey = GARandomInt(0, dad.height());
momleny = mom.height() - momsitey;
dadleny = dad.height() - dadsitey;
sitey = GAMin(momsitey, dadsitey);
leny = GAMin(momleny, dadleny);
}
if(sis.resizeBehaviour(GAGenome::DEPTH) == GAGenome::FIXED_SIZE &&
bro.resizeBehaviour(GAGenome::DEPTH) == GAGenome::FIXED_SIZE){
if(mom.depth() != dad.depth() ||
sis.depth() != bro.depth() ||
sis.depth() != mom.depth()){
GAErr(GA_LOC, mom.className(), "one-point cross", gaErrSameLengthReqd);
return nc;
}
sitez = momsitez = dadsitez = GARandomInt(0, mom.depth());
lenz = momlenz = dadlenz = mom.depth() - momsitez;
}
else if(sis.resizeBehaviour(GAGenome::DEPTH) == GAGenome::FIXED_SIZE ||
bro.resizeBehaviour(GAGenome::DEPTH) == GAGenome::FIXED_SIZE){
GAErr(GA_LOC, mom.className(), "one-point cross", gaErrSameBehavReqd);
return nc;
}
else{
momsitez = GARandomInt(0, mom.depth());
dadsitez = GARandomInt(0, dad.depth());
momlenz = mom.depth() - momsitez;
dadlenz = dad.depth() - dadsitez;
sitez = GAMin(momsitez, dadsitez);
lenz = GAMin(momlenz, dadlenz);
}
sis.resize(sitex+lenx, sitey+leny, sitez+lenz);
bro.resize(sitex+lenx, sitey+leny, sitez+lenz);
sis.copy(mom,
0, 0, 0,
momsitex-sitex, momsitey-sitey, momsitez-sitez,
sitex, sitey, sitez);
sis.copy(dad,
sitex, 0, 0,
dadsitex, dadsitey-sitey, dadsitez-sitez,
lenx, sitey, sitez);
sis.copy(dad,
0, sitey, 0,
dadsitex-sitex, dadsitey, dadsitez-sitez,
sitex, leny, sitez);
sis.copy(mom,
sitex, sitey, 0,
momsitex, momsitey, momsitez-sitez,
lenx, leny, sitez);
sis.copy(dad,
0, 0, sitez,
dadsitex-sitex, dadsitey-sitey, dadsitez,
sitex, sitey, lenz);
sis.copy(mom,
sitex, 0, sitez,
momsitex, momsitey-sitey, momsitez,
lenx, sitey, lenz);
sis.copy(mom,
0, sitey, sitez,
momsitex-sitex, momsitey, momsitez,
sitex, leny, lenz);
sis.copy(dad,
sitex, sitey, sitez,
dadsitex, dadsitey, dadsitez,
lenx, leny, lenz);
bro.copy(dad,
0, 0, 0,
dadsitex-sitex, dadsitey-sitey, dadsitez-sitez,
sitex, sitey, sitez);
bro.copy(mom,
sitex, 0, 0,
momsitex, momsitey-sitey, momsitez-sitez,
lenx, sitey, sitez);
bro.copy(mom,
0, sitey, 0,
momsitex-sitex, momsitey, momsitez-sitez,
sitex, leny, sitez);
bro.copy(dad,
sitex, sitey, 0,
dadsitex, dadsitey, dadsitez-sitez,
lenx, leny, sitez);
bro.copy(mom,
0, 0, sitez,
momsitex-sitex, momsitey-sitey, momsitez,
sitex, sitey, lenz);
bro.copy(dad,
sitex, 0, sitez,
dadsitex, dadsitey-sitey, dadsitez,
lenx, sitey, lenz);
bro.copy(dad,
0, sitey, sitez,
dadsitex-sitex, dadsitey, dadsitez,
sitex, leny, lenz);
bro.copy(mom,
sitex, sitey, sitez,
momsitex, momsitey, momsitez,
lenx, leny, lenz);
nc = 2;
}
else if(c1){
GA3DArrayGenome<T> &sis=(GA3DArrayGenome<T> &)*c1;
if(sis.resizeBehaviour(GAGenome::WIDTH) == GAGenome::FIXED_SIZE){
if(mom.width() != dad.width() || sis.width() != mom.width()){
GAErr(GA_LOC, mom.className(), "one-point cross", gaErrSameLengthReqd);
return nc;
}
sitex = momsitex = dadsitex = GARandomInt(0, mom.width());
lenx = momlenx = dadlenx = mom.width() - momsitex;
}
else{
momsitex = GARandomInt(0, mom.width());
dadsitex = GARandomInt(0, dad.width());
momlenx = mom.width() - momsitex;
dadlenx = dad.width() - dadsitex;
sitex = GAMin(momsitex, dadsitex);
lenx = GAMin(momlenx, dadlenx);
}
if(sis.resizeBehaviour(GAGenome::HEIGHT) == GAGenome::FIXED_SIZE){
if(mom.height() != dad.height() || sis.height() != mom.height()){
GAErr(GA_LOC, mom.className(), "one-point cross", gaErrSameLengthReqd);
return nc;
}
sitey = momsitey = dadsitey = GARandomInt(0, mom.height());
leny = momleny = dadleny = mom.height() - momsitey;
}
else{
momsitey = GARandomInt(0, mom.height());
dadsitey = GARandomInt(0, dad.height());
momleny = mom.height() - momsitey;
dadleny = dad.height() - dadsitey;
sitey = GAMin(momsitey, dadsitey);
leny = GAMin(momleny, dadleny);
}
if(sis.resizeBehaviour(GAGenome::DEPTH) == GAGenome::FIXED_SIZE){
if(mom.depth() != dad.depth() || sis.depth() != mom.depth()){
GAErr(GA_LOC, mom.className(), "one-point cross", gaErrSameLengthReqd);
return nc;
}
sitez = momsitez = dadsitez = GARandomInt(0, mom.depth());
lenz = momlenz = dadlenz = mom.depth() - momsitez;
}
else{
momsitez = GARandomInt(0, mom.depth());
dadsitez = GARandomInt(0, dad.depth());
momlenz = mom.depth() - momsitez;
dadlenz = dad.depth() - dadsitez;
sitez = GAMin(momsitez, dadsitez);
lenz = GAMin(momlenz, dadlenz);
}
sis.resize(sitex+lenx, sitey+leny, sitez+lenz);
if(GARandomBit()){
sis.copy(mom,
0, 0, 0,
momsitex-sitex, momsitey-sitey, momsitez-sitez,
sitex, sitey, sitez);
sis.copy(dad,
sitex, 0, 0,
dadsitex, dadsitey-sitey, dadsitez-sitez,
lenx, sitey, sitez);
sis.copy(dad,
0, sitey, 0,
dadsitex-sitex, dadsitey, dadsitez-sitez,
sitex, leny, sitez);
sis.copy(mom,
sitex, sitey, 0,
momsitex, momsitey, momsitez-sitez,
lenx, leny, sitez);
sis.copy(dad,
0, 0, sitez,
dadsitex-sitex, dadsitey-sitey, dadsitez,
sitex, sitey, lenz);
sis.copy(mom,
sitex, 0, sitez,
momsitex, momsitey-sitey, momsitez,
lenx, sitey, lenz);
sis.copy(mom,
0, sitey, sitez,
momsitex-sitex, momsitey, momsitez,
sitex, leny, lenz);
sis.copy(dad,
sitex, sitey, sitez,
dadsitex, dadsitey, dadsitez,
lenx, leny, lenz);
}
else{
sis.copy(dad,
0, 0, 0,
dadsitex-sitex, dadsitey-sitey, dadsitez-sitez,
sitex, sitey, sitez);
sis.copy(mom,
sitex, 0, 0,
momsitex, momsitey-sitey, momsitez-sitez,
lenx, sitey, sitez);
sis.copy(mom,
0, sitey, 0,
momsitex-sitex, momsitey, momsitez-sitez,
sitex, leny, sitez);
sis.copy(dad,
sitex, sitey, 0,
dadsitex, dadsitey, dadsitez-sitez,
lenx, leny, sitez);
sis.copy(mom,
0, 0, sitez,
momsitex-sitex, momsitey-sitey, momsitez,
sitex, sitey, lenz);
sis.copy(dad,
sitex, 0, sitez,
dadsitex, dadsitey-sitey, dadsitez,
lenx, sitey, lenz);
sis.copy(dad,
0, sitey, sitez,
dadsitex-sitex, dadsitey, dadsitez,
sitex, leny, lenz);
sis.copy(mom,
sitex, sitey, sitez,
momsitex, momsitey, momsitez,
lenx, leny, lenz);
}
nc = 1;
}
return nc;
}
int
GA3DBinaryStringGenome::resize(int w, int h, int d)
{
if(w == (int)nx && h == (int)ny && d == (int)nz) return sz;
if(w == GAGenome::ANY_SIZE)
w = GARandomInt(minX, maxX);
else if(w < 0)
w = nx; // do nothing
else if(minX == maxX)
minX=maxX = w;
else{
if(w < (int)minX) w=minX;
if(w > (int)maxX) w=maxX;
}
if(h == GAGenome::ANY_SIZE)
h = GARandomInt(minY, maxY);
else if(h < 0)
h = ny; // do nothing
else if(minY == maxY)
minY=maxY = h;
else{
if(h < (int)minY) h=minY;
if(h > (int)maxY) h=maxY;
}
if(d == GAGenome::ANY_SIZE)
d = GARandomInt(minZ, maxZ);
else if(d < 0)
d = nz; // do nothing
else if(minZ == maxZ)
minZ=maxZ = d;
else{
if(d < (int)minZ) d=minZ;
if(d > (int)maxZ) d=maxZ;
}
if(w < (int)nx && h < (int)ny){
int z=GAMin((int)nz,d);
for(int k=0; k<z; k++)
for(int j=0; j<h; j++)
GABinaryString::move(k*h*w+j*w,k*ny*nx+j*nx,w);
}
else if(w < (int)nx){
int z=GAMin((int)nz,d);
for(int k=0; k<z; k++)
for(int j=0; j<(int)ny; j++)
GABinaryString::move(k*ny*w+j*w,k*ny*nx+j*nx,w);
}
else if(h < (int)ny){
int z=GAMin((int)nz,d);
for(int k=0; k<z; k++)
for(int j=0; j<h; j++)
GABinaryString::move(k*h*nx+j*nx,k*ny*nx+j*nx,nx);
}
GABinaryString::resize(w*h*d);
if(w > (int)nx && h > (int)ny){ // adjust the existing bits
int z=GAMin((int)nz,d);
for(int k=z-1; k>=0; k--){
int j;
for(j=ny-1; j>=0; j--){
GABinaryString::move(k*h*w+j*w,k*ny*nx+j*nx,nx);
for(int i=nx; i<w; i++)
bit(k*h*w+j*w+i, GARandomBit());
}
for(j=ny; j<h; j++)
for(int i=0; i<w; i++)
bit(k*h*w+j*w+i, GARandomBit());
}
}
else if(w > (int)nx){
int z=GAMin((int)nz,d);
for(int k=z-1; k>=0; k--){
for(int j=h-1; j>=0; j--){
GABinaryString::move(k*h*w+j*w,k*h*nx+j*nx,nx);
for(int i=nx; i<w; i++)
bit(k*h*w+j*w+i, GARandomBit());
}
}
}
else if(h > (int)ny){
int z=GAMin((int)nz,d);
for(int k=z-1; k>=0; k--){
int j;
for(j=ny-1; j>=0; j--)
GABinaryString::move(k*h*w+j*w,k*ny*w+j*w,w);
for(j=ny; j<h; j++)
for(int i=0; i<w; i++)
bit(k*h*w+j*w+i, GARandomBit());
}
}
if(d > (int)nz){ // change in depth is always new bits
for(int i=w*h*nz; i<w*h*d; i++)
bit(i, GARandomBit());
}
nx = w; ny = h; nz = d;
_evaluated = gaFalse;
return sz;
}
// For even crossover we take the even bits from the mother (for the daughter)
// and the odd bits from the father. Just the opposite for the son.
// This is designed only for genomes that are the same length. If the child
// is not the same length as the parent, or if the children are not the same
// size, we don't do the crossover.
// In the interest of speed we do not do any checks for size. Do not use
// this crossover method when the parents and children may be different sizes.
// It might break!
int
GA3DBinaryStringGenome::
EvenOddCrossover(const GAGenome& p1, const GAGenome& p2,
GAGenome* c1, GAGenome* c2){
GA3DBinaryStringGenome &mom=(GA3DBinaryStringGenome &)p1;
GA3DBinaryStringGenome &dad=(GA3DBinaryStringGenome &)p2;
int nc=0;
int i,j,k;
if(c1 && c2){
GA3DBinaryStringGenome &sis=(GA3DBinaryStringGenome &)*c1;
GA3DBinaryStringGenome &bro=(GA3DBinaryStringGenome &)*c2;
if(sis.width() == bro.width() && sis.height() == bro.height() &&
sis.depth() == bro.depth() &&
mom.width() == dad.width() && mom.height() == dad.height() &&
mom.depth() == dad.depth() &&
sis.width() == mom.width() && sis.height() == mom.height() &&
sis.depth() == mom.depth()){
int count=0;
for(i=sis.width()-1; i>=0; i--){
for(j=sis.height()-1; j>=0; j--){
for(k=sis.depth()-1; k>=0; k--){
if(count%2 == 0){
sis.gene(i,j,k, mom.gene(i,j,k));
bro.gene(i,j,k, dad.gene(i,j,k));
}
else{
sis.gene(i,j,k, dad.gene(i,j,k));
bro.gene(i,j,k, mom.gene(i,j,k));
}
count++;
}
}
}
}
else{
int minx = GAMin(mom.width(), dad.width());
int miny = GAMin(mom.height(), dad.height());
int minz = GAMin(mom.depth(), dad.depth());
minx = GAMin(sis.width(), minx);
miny = GAMin(sis.height(), miny);
minz = GAMin(sis.depth(), minz);
for(i=minx-1; i>=0; i--)
for(j=miny-1; j>=0; j--)
for(k=minz-1; k>=0; k--)
sis.gene(i,j,k, (((i*miny*minz+j*minz+k)%2 == 0) ?
mom.gene(i,j,k) : dad.gene(i,j,k)));
minx = (bro.width() < minx) ? bro.width() : minx;
miny = (bro.height() < miny) ? bro.height() : miny;
minz = (bro.depth() < minz) ? bro.depth() : minz;
for(i=minx-1; i>=0; i--)
for(j=miny-1; j>=0; j--)
for(k=minz-1; k>=0; k--)
bro.gene(i,j,k, (((i*miny*minz+j*minz+k)%2 == 0) ?
dad.gene(i,j,k) : mom.gene(i,j,k)));
}
nc = 2;
}
else if(c1 || c2){
GA3DBinaryStringGenome &sis =
(c1 ? (GA3DBinaryStringGenome &)*c1 : (GA3DBinaryStringGenome &)*c2);
if(mom.width() == dad.width() && mom.height() == dad.height() &&
mom.depth() == dad.depth() &&
sis.width() == mom.width() && sis.height() == mom.height() &&
sis.depth() == mom.depth()){
int count=0;
for(i=sis.width()-1; i>=0; i--){
for(j=sis.height()-1; j>=0; j--){
for(k=sis.depth()-1; k>=0; k--){
sis.gene(i,j,k,((count%2 == 0) ? mom.gene(i,j,k):dad.gene(i,j,k)));
count++;
}
}
}
}
else{
int minx = GAMin(mom.width(), dad.width());
int miny = GAMin(mom.height(), dad.height());
int minz = GAMin(mom.depth(), dad.depth());
minx = GAMin(sis.width(), minx);
miny = GAMin(sis.height(), miny);
minz = GAMin(sis.depth(), minz);
for(i=minx-1; i>=0; i--)
for(j=miny-1; j>=0; j--)
for(k=minz-1; k>=0; k--)
sis.gene(i,j, (((i*miny*minz+j*minz+k)%2 == 0) ?
mom.gene(i,j,k) : dad.gene(i,j,k)));
}
nc = 1;
}
return nc;
}
// Make sure our bitmask is big enough, generate a mask, then use it to
// extract the information from each parent to stuff the two children.
// We don't deallocate any space for the masks under the assumption that we'll
// have to use them again in the future.
// For now we'll implement this only for fixed length genomes. If you use
// this crossover method on genomes of different sizes it might break!
int
GA3DBinaryStringGenome::
UniformCrossover(const GAGenome& p1, const GAGenome& p2,
GAGenome* c1, GAGenome* c2){
GA3DBinaryStringGenome &mom=(GA3DBinaryStringGenome &)p1;
GA3DBinaryStringGenome &dad=(GA3DBinaryStringGenome &)p2;
int i,j,k, nc=0;;
if(c1 && c2){
GA3DBinaryStringGenome &sis=(GA3DBinaryStringGenome &)*c1;
GA3DBinaryStringGenome &bro=(GA3DBinaryStringGenome &)*c2;
if(sis.width() == bro.width() && sis.height() == bro.height() &&
sis.depth() == bro.depth() &&
mom.width() == dad.width() && mom.height() == dad.height() &&
mom.depth() == dad.depth() &&
sis.width() == mom.width() && sis.height() == mom.height() &&
sis.depth() == mom.depth()){
for(i=sis.width()-1; i>=0; i--){
for(j=sis.height()-1; j>=0; j--){
for(k=sis.depth()-1; k>=0; k--){
if(GARandomBit()){
sis.gene(i,j,k, mom.gene(i,j,k));
bro.gene(i,j,k, dad.gene(i,j,k));
}
else{
sis.gene(i,j,k, dad.gene(i,j,k));
bro.gene(i,j,k, mom.gene(i,j,k));
}
}
}
}
}
else{
GAMask mask;
int maxx = GAMax(sis.width(), bro.width());
int minx = GAMin(mom.width(), dad.width());
int maxy = GAMax(sis.height(), bro.height());
int miny = GAMin(mom.height(), dad.height());
int maxz = GAMax(sis.depth(), bro.depth());
int minz = GAMin(mom.depth(), dad.depth());
mask.size(maxx*maxy*maxz);
for(i=0; i<maxx; i++)
for(j=0; j<maxy; j++)
for(k=0; k<maxz; k++)
mask[i*maxy*maxz+j*maxz+k] = GARandomBit();
minx = GAMin(sis.width(), minx);
miny = GAMin(sis.height(), miny);
minz = GAMin(sis.depth(), minz);
for(i=minx-1; i>=0; i--)
for(j=miny-1; j>=0; j--)
for(k=minz-1; k>=0; k--)
sis.gene(i,j,k, (mask[i*miny*minz+j*minz+k] ?
mom.gene(i,j,k) : dad.gene(i,j,k)));
minx = GAMin(bro.width(), minx);
miny = GAMin(bro.height(), miny);
minz = GAMin(bro.depth(), minz);
for(i=minx-1; i>=0; i--)
for(j=miny-1; j>=0; j--)
for(k=minz-1; k>=0; k--)
bro.gene(i,j,k, (mask[i*miny*minz+j*minz+k] ?
dad.gene(i,j,k) : mom.gene(i,j,k)));
}
nc = 2;
}
else if(c1 || c2){
GA3DBinaryStringGenome &sis =
(c1 ? (GA3DBinaryStringGenome&)*c1 : (GA3DBinaryStringGenome&)*c2);
if(mom.width() == dad.width() && mom.height() == dad.height() &&
mom.depth() == dad.depth() &&
sis.width() == mom.width() && sis.height() == mom.height() &&
sis.depth() == mom.depth()){
for(i=sis.width()-1; i>=0; i--)
for(j=sis.height()-1; j>=0; j--)
for(k=sis.depth()-1; k>=0; k--)
sis.gene(i,j,k, (GARandomBit() ? mom.gene(i,j,k):dad.gene(i,j,k)));
}
else{
int minx = GAMin(mom.width(), dad.width());
int miny = GAMin(mom.height(), dad.height());
int minz = GAMin(mom.depth(), dad.depth());
minx = GAMin(sis.width(), minx);
miny = GAMin(sis.height(), miny);
minz = GAMin(sis.depth(), minz);
for(i=minx-1; i>=0; i--)
for(j=miny-1; j>=0; j--)
for(k=minz-1; k>=0; k--)
sis.gene(i,j,k, (GARandomBit() ? mom.gene(i,j,k):dad.gene(i,j,k)));
}
nc = 1;
}
return nc;
}
