//
//
// calculates expressions stored in a parse Tree
//
//
int evaluateOpFunc(opNode* exp, tree& symbolTable, tree& localVar, funcS& funcTable){
int rights;
int lefts ;
String s = exp->stringOp();
if(s == "NONE"){
return exp->val();
}else if(isValidVarName(s)){// if s is not an operation
if(s == "call"){
exp = exp->leftNode();
String funcName = exp->stringOp();// gets function name
param* parameter;
if(funcTable.isMember(funcName)){
parameter = funcTable.getParameters(funcName);// passing arguments
}else{
printf("WARNING: Function %s is not declared \n", funcName.c_str());
return 0;
}
int i = 0;
opNode* params = exp->leftNode();
if(params->stringOp() != "Ecall"){
while(params->stringOp() != "Ecall"){
parameter->op[i].value = evaluateOpFunc(params->rightNode(), symbolTable, localVar, funcTable);
params = params->leftNode();
i += 1;
}
}
tree* newTree = new tree;
for(int j =0; j < i ; j+=1){
newTree->insert(parameter->op[j].para, parameter->op[j].value);
}
if(funcTable.isMember(funcName)){
funcTable.addLocalVar(funcName, newTree);
evaluateFunc(funcName, symbolTable, funcTable);
return funcTable.getVal(funcName);
}else{
printf("Warning: function %s is not declared \n", funcName.c_str());
}
}
if(localVar.isMember(s)){
return localVar.getVal(s);
}else if(symbolTable.isMember(s)){
return symbolTable.getVal(s);
}
}
if(exp->leftNode()){
lefts = evaluateOpFunc(exp->leftNode(), symbolTable, localVar, funcTable);
if(s == "~" || s == "!"){return result(s, lefts, rights);}
}
if(exp->rightNode()){
rights = evaluateOpFunc(exp->rightNode(), symbolTable, localVar, funcTable);
}
return result(s,lefts,rights);
}
scalar surfaceOptimizer::optimiseSteepestDescent(const scalar tol)
{
point& pOpt = pts_[trias_[0][0]];
//- find the bounding box
const scalar avgEdge = Foam::mag(pMax_ - pMin_);
//- find the minimum value on the 5 x 5 raster
scalar K = evaluateStabilisationFactor();
scalar funcBefore, funcAfter(evaluateFunc(K));
//- start with steepest descent optimisation
vector gradF;
tensor gradGradF;
vector disp;
disp.z() = 0.0;
direction nIterations(0);
do
{
funcBefore = funcAfter;
evaluateGradients(K, gradF, gradGradF);
//- store data into a matrix
matrix2D mat;
mat[0][0] = gradGradF.xx();
mat[0][1] = gradGradF.xy();
mat[1][0] = gradGradF.yx();
mat[1][1] = gradGradF.yy();
FixedList<scalar, 2> source;
source[0] = gradF.x();
source[1] = gradF.y();
//- calculate the determinant
const scalar det = mat.determinant();
if( mag(det) < VSMALL )
{
disp = vector::zero;
}
else
{
disp.x() = mat.solveFirst(source);
disp.y() = mat.solveSecond(source);
if( mag(disp) > 0.2 * avgEdge )
{
vector dir = disp / mag(disp);
disp = dir * 0.2 * avgEdge;
}
}
# ifdef DEBUGSmooth
Info << "Second gradient " << gradGradF << endl;
Info << "Gradient " << gradF << endl;
Info << "Displacement " << disp << endl;
Info << "K = " << K << endl;
# endif
pOpt -= disp;
K = evaluateStabilisationFactor();
funcAfter = evaluateFunc(K);
if( mag(funcAfter - funcBefore) / funcBefore < tol )
break;
#ifdef DEBUGSmooth
Info << "New coordinates " << pOpt << endl;
# endif
} while( ++nIterations < 100 );
return funcAfter;
}
scalar surfaceOptimizer::optimiseDivideAndConquer(const scalar tol)
{
point& pOpt = pts_[trias_[0][0]];
pOpt = 0.5 * (pMax_ + pMin_);
point currCentre = pOpt;
scalar dx = (pMax_.x() - pMin_.x()) / 2.0;
scalar dy = (pMax_.y() - pMin_.y()) / 2.0;
label iter(0);
//- find the value of the functional in the centre of the bnd box
scalar K = evaluateStabilisationFactor();
scalar funcBefore, funcAfter(evaluateFunc(K));
do
{
funcBefore = funcAfter;
funcAfter = VGREAT;
point minCentre(vector::zero);
for(label i=0;i<4;++i)
{
pOpt.x() = currCentre.x() + 0.5 * dirVecs[i].x() * dx;
pOpt.y() = currCentre.y() + 0.5 * dirVecs[i].y() * dy;
K = evaluateStabilisationFactor();
const scalar func = evaluateFunc(K);
if( func < funcAfter )
{
minCentre = pOpt;
funcAfter = func;
}
}
//- set the centre with the minimum value
//- as the centre for future search
currCentre = minCentre;
pOpt = minCentre;
//- halve the search range
dx *= 0.5;
dy *= 0.5;
//- calculate the tolerence
const scalar t = mag(funcAfter - funcBefore) / funcAfter;
# ifdef DEBUGSmooth
Info << "Point position " << pOpt << endl;
Info << "Func before " << funcBefore << endl;
Info << "Func after " << funcAfter << endl;
Info << "Normalised difference " << t << endl;
# endif
if( t < tol )
break;
} while( ++iter < 100 );
return funcAfter;
}
scalar volumeOptimizer::optimiseSteepestDescent(const scalar tol)
{
label iter(0);
point& p = points_[pointI_];
# ifdef DEBUGSmooth
Info << nl << "Smoothing point " << pointI_
<< " with coordinates " << p << endl;
scalar Vmina(VGREAT);
forAll(tets_, tetI)
Vmina = Foam::min(Vmina, tets_[tetI].mag(points_));
Info << "Vmin before " << Vmina << endl;
# endif
vector gradF;
vector disp(vector::zero);
tensor gradGradF;
point pOrig;
scalar funcBefore, funcAfter(evaluateFunc());
bool finished;
do
{
finished = false;
pOrig = p;
funcBefore = funcAfter;
evaluateGradientsExact(gradF, gradGradF);
const scalar determinant = Foam::det(gradGradF);
if( determinant > SMALL )
{
disp = (inv(gradGradF, determinant) & gradF);
p -= disp;
funcAfter = evaluateFunc();
# ifdef DEBUGSmooth
Info << nl << "gradF " << gradF << endl;
Info << "gradGradF " << gradGradF << endl;
Info << "det(gradGradF) " << determinant << endl;
Info << "disp " << disp << endl;
Info << "Func before " << funcBefore << endl;
Info << "Func after " << funcAfter << endl;
# endif
scalar relax(0.8);
label nLoops(0);
while( funcAfter > funcBefore )
{
p = pOrig - relax * disp;
relax *= 0.5;
funcAfter = evaluateFunc();
if( funcAfter < funcBefore )
continue;
if( ++nLoops == 5 )
{
//- it seems that this direction is wrong, stop the loop
p = pOrig;
disp = vector::zero;
finished = true;
funcAfter = funcBefore;
}
}
if( mag(funcBefore - funcAfter) / funcBefore < tol )
finished = true;
}
else
{
//- move in random direction
//- this is usually needed to move the point off the zero volume
disp = vector::zero;
forAll(tets_, tetI)
{
const partTet& tet = tets_[tetI];
const scalar Vtri = tet.mag(points_);
if( Vtri < SMALL )
{
triangle<point, point> tri
(
points_[tet.a()],
points_[tet.b()],
points_[tet.c()]
);
vector n = tri.normal();
const scalar d = mag(n);
if( d > VSMALL )
disp += 0.01 * (n / d);
}
}
p += disp;
funcAfter = evaluateFunc();
}
} while( (++iter < 100) && !finished );
# ifdef DEBUGSmooth
scalar Vmin(VGREAT);
forAll(tets_, tetI)
Vmin = Foam::min(Vmin, tets_[tetI].mag(points_));
Info << nl << "New coordinates for point "
<< pointI_ << " are " << p << endl;
Info << "Num iterations " << iter << " gradient " << gradF << endl;
Info << "Vmin " << Vmin << endl;
# endif
return funcAfter;
}