inline
BBOX
bface_bbox(QuadtreeNode* face)
{
BBOX ret = BBOX();
ret.update(face->v1());
ret.update(face->v2());
ret.update(face->v3());
return ret;
}
inline
BBOX
bface_bbox(Bface* face)
{
BBOX ret = BBOX();
ret.update(face->v1()->loc());
ret.update(face->v2()->loc());
ret.update(face->v3()->loc());
return ret;
}
void
LMESH::fit(vector<Lvert*>& verts, bool do_gauss_seidel)
{
static bool debug = Config::get_var_bool("DEBUG_LMESH_FIT",false);
static bool move_along_normal =
Config::get_var_bool("FITTING_MOVE_ALONG_NORMAL",false);
if (verts.empty())
return;
// calculate the bounding box of the vertices
BBOX box;
size_t i;
for (i=0; i<verts.size(); i++)
box.update(verts[i]->loc());
double max_err = box.dim().length() * 1e-5;
size_t n = verts.size();
// get original control point locations
vector<Wpt> C(n); // original control points
vector<Wpt> L(n); // current limit points
for (i=0; i<n; i++) {
C[i] = verts[i]->loc();
L[i] = Wpt::Origin();
}
if(debug) {
cerr << "LMESH::fit- fitting " << n << " vertices"<<endl;
cerr << "Max_err = " << max_err <<endl;
}
// do 50 iterations...
double prev_err = 0;
vector<double> errors;
for (int k=0; k<50; k++) {
errors.clear();
double err = 0;
if (do_gauss_seidel) {
// Gauss-Seidel iteration: use updated values from the
// current iteration as they are computed...
for (size_t j=0; j<n; j++) {
// don't need that L[] array...
Wpt limit;
verts[j]->limit_loc(limit);
Wvec delt = C[j] - limit;
errors.push_back(delt.length());
err += delt.length();
if(move_along_normal)
delt = delt*verts[j]->norm()*verts[j]->norm();
verts[j]->offset_loc(delt);
}
} else {
// compute the new offsets from the offsets computed in the
// previous iteration
size_t j;
for (j=0; j<n; j++)
verts[j]->limit_loc(L[j]);
for (j=0; j<n; j++) {
Wvec delt = C[j] - L[j];
err += delt.length();
errors.push_back(delt.length());
if(move_along_normal)
delt = delt*verts[j]->norm()*verts[j]->norm();
verts[j]->offset_loc(delt);
}
}
// compute the average error:
err /= n;
double avg,std_d,max,min;
if (debug) {
if (prev_err != 0) {
err_msg("Iter %d: avg error: %f, reduction: %f",
k, err, err/prev_err);
statistics(errors,true,&avg,&std_d,&max,&min);
} else {
err_msg("Iter %d: avg error: %f", k, err);
statistics(errors,true,&avg,&std_d,&max,&min);
}
} else
statistics(errors,false,&avg,&std_d,&max,&min);
prev_err = err;
if (max < max_err) {
if(debug) cerr << "Terminating at " << k <<" th iterations"<<endl;
return;
}
}
}