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create/src/Mod/Mesh/App/Core/Approximation.cpp

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/***************************************************************************
* Copyright (c) 2005 Imetric 3D GmbH *
* *
* This file is part of the FreeCAD CAx development system. *
* *
* This library is free software; you can redistribute it and/or *
* modify it under the terms of the GNU Library General Public *
* License as published by the Free Software Foundation; either *
* version 2 of the License, or (at your option) any later version. *
* *
* This library is distributed in the hope that it will be useful, *
* but WITHOUT ANY WARRANTY; without even the implied warranty of *
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the *
* GNU Library General Public License for more details. *
* *
* You should have received a copy of the GNU Library General Public *
* License along with this library; see the file COPYING.LIB. If not, *
* write to the Free Software Foundation, Inc., 59 Temple Place, *
* Suite 330, Boston, MA 02111-1307, USA *
* *
***************************************************************************/
#include "PreCompiled.h"
#ifndef _PreComp_
# include <algorithm>
# include <cstdlib>
# include <iterator>
#endif
#include "Approximation.h"
#include "Elements.h"
#include "Utilities.h"
#include "CylinderFit.h"
#include "SphereFit.h"
#include <Base/BoundBox.h>
#include <Base/Console.h>
#include <boost/math/special_functions/fpclassify.hpp>
#include <Mod/Mesh/App/WildMagic4/Wm4ApprQuadraticFit3.h>
#include <Mod/Mesh/App/WildMagic4/Wm4ApprPlaneFit3.h>
#include <Mod/Mesh/App/WildMagic4/Wm4DistVector3Plane3.h>
#include <Mod/Mesh/App/WildMagic4/Wm4Matrix3.h>
#include <Mod/Mesh/App/WildMagic4/Wm4ApprPolyFit3.h>
#include <Mod/Mesh/App/WildMagic4/Wm4ApprSphereFit3.h>
#include <Mod/Mesh/App/WildMagic4/Wm4Sphere3.h>
#include <Mod/Mesh/App/WildMagic4/Wm4ApprCylinderFit3.h>
//#define FC_USE_EIGEN
#include <Eigen/QR>
#include <Eigen/Eigen>
#include <unsupported/Eigen/NonLinearOptimization>
#ifdef FC_USE_EIGEN
#include <Eigen/Eigenvalues>
#endif
using namespace MeshCore;
Approximation::Approximation()
: _bIsFitted(false), _fLastResult(FLOAT_MAX)
{
}
Approximation::~Approximation()
{
Clear();
}
void Approximation::GetMgcVectorArray(std::vector< Wm4::Vector3<double> >& rcPts) const
{
std::list< Base::Vector3f >::const_iterator It;
rcPts.reserve(_vPoints.size());
for (It = _vPoints.begin(); It != _vPoints.end(); ++It) {
rcPts.push_back(Base::convertTo<Wm4::Vector3d>(*It));
}
}
void Approximation::AddPoint(const Base::Vector3f &rcVector)
{
_vPoints.push_back(rcVector);
_bIsFitted = false;
}
void Approximation::AddPoints(const std::vector<Base::Vector3f> &points)
{
std::copy(points.begin(), points.end(), std::back_inserter(_vPoints));
_bIsFitted = false;
}
void Approximation::AddPoints(const std::set<Base::Vector3f> &points)
{
std::copy(points.begin(), points.end(), std::back_inserter(_vPoints));
_bIsFitted = false;
}
void Approximation::AddPoints(const std::list<Base::Vector3f> &points)
{
std::copy(points.begin(), points.end(), std::back_inserter(_vPoints));
_bIsFitted = false;
}
void Approximation::AddPoints(const MeshPointArray &points)
{
std::copy(points.begin(), points.end(), std::back_inserter(_vPoints));
_bIsFitted = false;
}
Base::Vector3f Approximation::GetGravity() const
{
Base::Vector3f clGravity;
if (!_vPoints.empty()) {
for (std::list<Base::Vector3f>::const_iterator it = _vPoints.begin(); it!=_vPoints.end(); ++it)
clGravity += *it;
clGravity *= 1.0f / float(_vPoints.size());
}
return clGravity;
}
unsigned long Approximation::CountPoints() const
{
return _vPoints.size();
}
void Approximation::Clear()
{
_vPoints.clear();
_bIsFitted = false;
}
float Approximation::GetLastResult() const
{
return _fLastResult;
}
bool Approximation::Done() const
{
return _bIsFitted;
}
// -------------------------------------------------------------------------------
PlaneFit::PlaneFit()
: _vBase(0,0,0)
, _vDirU(1,0,0)
, _vDirV(0,1,0)
, _vDirW(0,0,1)
{
}
PlaneFit::~PlaneFit()
{
}
float PlaneFit::Fit()
{
_bIsFitted = true;
if (CountPoints() < 3)
return FLOAT_MAX;
double sxx,sxy,sxz,syy,syz,szz,mx,my,mz;
sxx=sxy=sxz=syy=syz=szz=mx=my=mz=0.0;
for (std::list<Base::Vector3f>::iterator it = _vPoints.begin(); it!=_vPoints.end(); ++it) {
sxx += double(it->x * it->x); sxy += double(it->x * it->y);
sxz += double(it->x * it->z); syy += double(it->y * it->y);
syz += double(it->y * it->z); szz += double(it->z * it->z);
mx += double(it->x); my += double(it->y); mz += double(it->z);
}
size_t nSize = _vPoints.size();
sxx = sxx - mx*mx/(double(nSize));
sxy = sxy - mx*my/(double(nSize));
sxz = sxz - mx*mz/(double(nSize));
syy = syy - my*my/(double(nSize));
syz = syz - my*mz/(double(nSize));
szz = szz - mz*mz/(double(nSize));
#if defined(FC_USE_EIGEN)
Eigen::Matrix3d covMat = Eigen::Matrix3d::Zero();
covMat(0,0) = sxx;
covMat(1,1) = syy;
covMat(2,2) = szz;
covMat(0,1) = sxy; covMat(1,0) = sxy;
covMat(0,2) = sxz; covMat(2,0) = sxz;
covMat(1,2) = syz; covMat(2,1) = syz;
Eigen::SelfAdjointEigenSolver<Eigen::Matrix3d> eig(covMat);
Eigen::Vector3d u = eig.eigenvectors().col(1);
Eigen::Vector3d v = eig.eigenvectors().col(2);
Eigen::Vector3d w = eig.eigenvectors().col(0);
_vDirU.Set(u.x(), u.y(), u.z());
_vDirV.Set(v.x(), v.y(), v.z());
_vDirW.Set(w.x(), w.y(), w.z());
_vBase.Set(mx/(float)nSize, my/(float)nSize, mz/(float)nSize);
float sigma = w.dot(covMat * w);
#else
// Covariance matrix
Wm4::Matrix3<double> akMat(sxx,sxy,sxz,sxy,syy,syz,sxz,syz,szz);
Wm4::Matrix3<double> rkRot, rkDiag;
try {
akMat.EigenDecomposition(rkRot, rkDiag);
}
catch (const std::exception&) {
return FLOAT_MAX;
}
// We know the Eigenvalues are ordered
// rkDiag(0,0) <= rkDiag(1,1) <= rkDiag(2,2)
//
// points describe a line or even are identical
if (rkDiag(1,1) <= 0)
return FLOAT_MAX;
Wm4::Vector3<double> U = rkRot.GetColumn(1);
Wm4::Vector3<double> V = rkRot.GetColumn(2);
Wm4::Vector3<double> W = rkRot.GetColumn(0);
// It may happen that the result have nan values
for (int i=0; i<3; i++) {
if (boost::math::isnan(U[i]) ||
boost::math::isnan(V[i]) ||
boost::math::isnan(W[i]))
return FLOAT_MAX;
}
_vDirU.Set(float(U.X()), float(U.Y()), float(U.Z()));
_vDirV.Set(float(V.X()), float(V.Y()), float(V.Z()));
_vDirW.Set(float(W.X()), float(W.Y()), float(W.Z()));
_vBase.Set(float(mx/nSize), float(my/nSize), float(mz/nSize));
float sigma = float(W.Dot(akMat * W));
#endif
// In case sigma is nan
if (boost::math::isnan(sigma))
return FLOAT_MAX;
// This must be caused by some round-off errors. Theoretically it's impossible
// that 'sigma' becomes negative because the covariance matrix is positive semi-definite.
if (sigma < 0)
sigma = 0;
// make a right-handed system
if ((_vDirU % _vDirV) * _vDirW < 0.0f) {
Base::Vector3f tmp = _vDirU;
_vDirU = _vDirV;
_vDirV = tmp;
}
if (nSize > 3)
sigma = sqrt(sigma/(nSize-3));
else
sigma = 0;
_fLastResult = sigma;
return _fLastResult;
}
Base::Vector3f PlaneFit::GetBase() const
{
if (_bIsFitted)
return _vBase;
else
return Base::Vector3f();
}
Base::Vector3f PlaneFit::GetDirU() const
{
if (_bIsFitted)
return _vDirU;
else
return Base::Vector3f();
}
Base::Vector3f PlaneFit::GetDirV() const
{
if (_bIsFitted)
return _vDirV;
else
return Base::Vector3f();
}
Base::Vector3f PlaneFit::GetNormal() const
{
if (_bIsFitted)
return _vDirW;
else
return Base::Vector3f();
}
float PlaneFit::GetDistanceToPlane(const Base::Vector3f &rcPoint) const
{
float fResult = FLOAT_MAX;
if (_bIsFitted)
fResult = (rcPoint - _vBase) * _vDirW;
return fResult;
}
float PlaneFit::GetStdDeviation() const
{
// Mean: M=(1/N)*SUM Xi
// Variance: VAR=(N/N-1)*[(1/N)*SUM(Xi^2)-M^2]
// Standard deviation: SD=SQRT(VAR)
// Standard error of the mean: SE=SD/SQRT(N)
if (!_bIsFitted)
return FLOAT_MAX;
float fSumXi = 0.0f, fSumXi2 = 0.0f,
fMean = 0.0f, fDist = 0.0f;
float ulPtCt = float(CountPoints());
std::list< Base::Vector3f >::const_iterator cIt;
for (cIt = _vPoints.begin(); cIt != _vPoints.end(); ++cIt) {
fDist = GetDistanceToPlane( *cIt );
fSumXi += fDist;
fSumXi2 += ( fDist * fDist );
}
fMean = (1.0f / ulPtCt) * fSumXi;
return sqrt((ulPtCt / (ulPtCt - 1.0f)) * ((1.0f / ulPtCt) * fSumXi2 - fMean * fMean));
}
float PlaneFit::GetSignedStdDeviation() const
{
// if the nearest point to the gravity is at the side
// of normal direction the value will be
// positive otherwise negative
if (!_bIsFitted)
return FLOAT_MAX;
float fSumXi = 0.0f, fSumXi2 = 0.0f,
fMean = 0.0f, fDist = 0.0f;
float fMinDist = FLOAT_MAX;
float fFactor;
float ulPtCt = float(CountPoints());
Base::Vector3f clGravity, clPt;
std::list<Base::Vector3f>::const_iterator cIt;
for (cIt = _vPoints.begin(); cIt != _vPoints.end(); ++cIt)
clGravity += *cIt;
clGravity *= (1.0f / ulPtCt);
for (cIt = _vPoints.begin(); cIt != _vPoints.end(); ++cIt) {
if ((clGravity - *cIt).Length() < fMinDist) {
fMinDist = (clGravity - *cIt).Length();
clPt = *cIt;
}
fDist = GetDistanceToPlane(*cIt);
fSumXi += fDist;
fSumXi2 += (fDist * fDist);
}
// which side
if ((clPt-clGravity)*GetNormal() > 0)
fFactor = 1.0f;
else
fFactor = -1.0f;
fMean = 1.0f / ulPtCt * fSumXi;
return fFactor * sqrt((ulPtCt / (ulPtCt - 3.0f)) * ((1.0f / ulPtCt) * fSumXi2 - fMean * fMean));
}
void PlaneFit::ProjectToPlane ()
{
Base::Vector3f cGravity(GetGravity());
Base::Vector3f cNormal (GetNormal ());
for (std::list< Base::Vector3f >::iterator it = _vPoints.begin(); it != _vPoints.end(); ++it) {
Base::Vector3f& cPnt = *it;
float fD = (cPnt - cGravity) * cNormal;
cPnt = cPnt - fD * cNormal;
}
}
void PlaneFit::Dimension(float& length, float& width) const
{
const Base::Vector3f& bs = _vBase;
const Base::Vector3f& ex = _vDirU;
const Base::Vector3f& ey = _vDirV;
Base::BoundBox3f bbox;
std::list<Base::Vector3f>::const_iterator cIt;
for (cIt = _vPoints.begin(); cIt != _vPoints.end(); ++cIt) {
Base::Vector3f pnt = *cIt;
pnt.TransformToCoordinateSystem(bs, ex, ey);
bbox.Add(pnt);
}
length = bbox.MaxX - bbox.MinX;
width = bbox.MaxY - bbox.MinY;
}
std::vector<Base::Vector3f> PlaneFit::GetLocalPoints() const
{
std::vector<Base::Vector3f> localPoints;
if (_bIsFitted && _fLastResult < FLOAT_MAX) {
Base::Vector3d bs = Base::convertTo<Base::Vector3d>(this->_vBase);
Base::Vector3d ex = Base::convertTo<Base::Vector3d>(this->_vDirU);
Base::Vector3d ey = Base::convertTo<Base::Vector3d>(this->_vDirV);
//Base::Vector3d ez = Base::convertTo<Base::Vector3d>(this->_vDirW);
localPoints.insert(localPoints.begin(), _vPoints.begin(), _vPoints.end());
for (std::vector<Base::Vector3f>::iterator it = localPoints.begin(); it != localPoints.end(); ++it) {
Base::Vector3d clPoint = Base::convertTo<Base::Vector3d>(*it);
clPoint.TransformToCoordinateSystem(bs, ex, ey);
it->Set(static_cast<float>(clPoint.x), static_cast<float>(clPoint.y), static_cast<float>(clPoint.z));
}
}
return localPoints;
}
Base::BoundBox3f PlaneFit::GetBoundings() const
{
Base::BoundBox3f bbox;
std::vector<Base::Vector3f> pts = GetLocalPoints();
for (auto it : pts)
bbox.Add(it);
return bbox;
}
// -------------------------------------------------------------------------------
bool QuadraticFit::GetCurvatureInfo(double x, double y, double z,
double &rfCurv0, double &rfCurv1,
Base::Vector3f &rkDir0, Base::Vector3f &rkDir1, double &dDistance)
{
assert( _bIsFitted );
bool bResult = false;
if (_bIsFitted) {
Wm4::Vector3<double> Dir0, Dir1;
FunctionContainer clFuncCont( _fCoeff );
bResult = clFuncCont.CurvatureInfo( x, y, z, rfCurv0, rfCurv1, Dir0, Dir1, dDistance );
dDistance = double(clFuncCont.GetGradient( x, y, z ).Length());
rkDir0 = Base::convertTo<Base::Vector3f>(Dir0);
rkDir1 = Base::convertTo<Base::Vector3f>(Dir1);
}
return bResult;
}
bool QuadraticFit::GetCurvatureInfo(double x, double y, double z, double &rfCurv0, double &rfCurv1)
{
bool bResult = false;
if (_bIsFitted) {
FunctionContainer clFuncCont( _fCoeff );
bResult = clFuncCont.CurvatureInfo( x, y, z, rfCurv0, rfCurv1 );
}
return bResult;
}
const double& QuadraticFit::GetCoeffArray() const
{
return _fCoeff[0];
}
double QuadraticFit::GetCoeff(unsigned long ulIndex) const
{
assert(ulIndex < 10);
if( _bIsFitted )
return _fCoeff[ ulIndex ];
else
return double(FLOAT_MAX);
}
float QuadraticFit::Fit()
{
float fResult = FLOAT_MAX;
if (CountPoints() > 0) {
std::vector< Wm4::Vector3<double> > cPts;
GetMgcVectorArray( cPts );
fResult = (float) Wm4::QuadraticFit3<double>( CountPoints(), &(cPts[0]), _fCoeff );
_fLastResult = fResult;
_bIsFitted = true;
}
return fResult;
}
void QuadraticFit::CalcEigenValues(double &dLambda1, double &dLambda2, double &dLambda3,
Base::Vector3f &clEV1, Base::Vector3f &clEV2, Base::Vector3f &clEV3) const
{
assert( _bIsFitted );
/*
* F(x,y,z) = a11*x*x + a22*y*y + a33*z*z +2*a12*x*y + 2*a13*x*z + 2*a23*y*z + 2*a10*x + 2*a20*y + 2*a30*z * a00 = 0
*
* Formenmatrix:
*
* ( a11 a12 a13 )
* A = ( a21 a22 a23 ) wobei gilt a[i,j] = a[j,i]
* ( a31 a32 a33 )
*
* Koeffizienten des Quadrik-Fits bezogen auf die hier verwendete Schreibweise:
*
* 0 = C[0] + C[1]*X + C[2]*Y + C[3]*Z + C[4]*X^2 + C[5]*Y^2
* + C[6]*Z^2 + C[7]*X*Y + C[8]*X*Z + C[9]*Y*Z
*
* Quadratisch: a11 := c[4], a22 := c[5], a33 := c[6]
* Gemischt: a12 := c[7]/2, a13 := c[8]/2, a23 := c[9]/2
* Linear: a10 := c[1]/2, a20 := c[2]/2, a30 := c[3]/2
* Konstant: a00 := c[0]
*
*/
Wm4::Matrix3<double> akMat(_fCoeff[4], _fCoeff[7]/2.0, _fCoeff[8]/2.0,
_fCoeff[7]/2.0, _fCoeff[5], _fCoeff[9]/2.0,
_fCoeff[8]/2.0, _fCoeff[9]/2.0, _fCoeff[6] );
Wm4::Matrix3<double> rkRot, rkDiag;
akMat.EigenDecomposition( rkRot, rkDiag );
Wm4::Vector3<double> vEigenU = rkRot.GetColumn(0);
Wm4::Vector3<double> vEigenV = rkRot.GetColumn(1);
Wm4::Vector3<double> vEigenW = rkRot.GetColumn(2);
clEV1 = Base::convertTo<Base::Vector3f>(vEigenU);
clEV2 = Base::convertTo<Base::Vector3f>(vEigenV);
clEV3 = Base::convertTo<Base::Vector3f>(vEigenW);
dLambda1 = rkDiag[0][0];
dLambda2 = rkDiag[1][1];
dLambda3 = rkDiag[2][2];
}
void QuadraticFit::CalcZValues( double x, double y, double &dZ1, double &dZ2 ) const
{
assert( _bIsFitted );
double dDisk = _fCoeff[3]*_fCoeff[3]+2*_fCoeff[3]*_fCoeff[8]*x+2*_fCoeff[3]*_fCoeff[9]*y+
_fCoeff[8]*_fCoeff[8]*x*x+2*_fCoeff[8]*x*_fCoeff[9]*y+_fCoeff[9]*_fCoeff[9]*y*y-
4*_fCoeff[6]*_fCoeff[0]-4*_fCoeff[6]*_fCoeff[1]*x-4*_fCoeff[6]*_fCoeff[2]*y-
4*_fCoeff[6]*_fCoeff[7]*x*y-4*_fCoeff[6]*_fCoeff[4]*x*x-4*_fCoeff[6]*_fCoeff[5]*y*y;
if (fabs( _fCoeff[6] ) < 0.000005) {
dZ1 = double(FLOAT_MAX);
dZ2 = double(FLOAT_MAX);
return;
}
if (dDisk < 0.0) {
dZ1 = double(FLOAT_MAX);
dZ2 = double(FLOAT_MAX);
return;
}
else
dDisk = sqrt( dDisk );
dZ1 = 0.5 * ( ( -_fCoeff[3] - _fCoeff[8]*x - _fCoeff[9]*y + dDisk ) / _fCoeff[6] );
dZ2 = 0.5 * ( ( -_fCoeff[3] - _fCoeff[8]*x - _fCoeff[9]*y - dDisk ) / _fCoeff[6] );
}
// -------------------------------------------------------------------------------
SurfaceFit::SurfaceFit()
: PlaneFit()
{
_fCoeff[0] = 0.0;
_fCoeff[1] = 0.0;
_fCoeff[2] = 0.0;
_fCoeff[3] = 0.0;
_fCoeff[4] = 0.0;
_fCoeff[5] = 0.0;
_fCoeff[6] = 0.0;
_fCoeff[7] = 0.0;
_fCoeff[8] = 0.0;
_fCoeff[9] = 0.0;
}
float SurfaceFit::Fit()
{
float fResult = FLOAT_MAX;
if (CountPoints() > 0) {
fResult = float(PolynomFit());
_fLastResult = fResult;
_bIsFitted = true;
}
return fResult;
}
bool SurfaceFit::GetCurvatureInfo(double x, double y, double z, double &rfCurv0, double &rfCurv1,
Base::Vector3f &rkDir0, Base::Vector3f &rkDir1, double &dDistance )
{
bool bResult = false;
if (_bIsFitted) {
Wm4::Vector3<double> Dir0, Dir1;
FunctionContainer clFuncCont( _fCoeff );
bResult = clFuncCont.CurvatureInfo( x, y, z, rfCurv0, rfCurv1, Dir0, Dir1, dDistance );
dDistance = double(clFuncCont.GetGradient( x, y, z ).Length());
rkDir0 = Base::convertTo<Base::Vector3f>(Dir0);
rkDir1 = Base::convertTo<Base::Vector3f>(Dir1);
}
return bResult;
}
bool SurfaceFit::GetCurvatureInfo(double x, double y, double z, double &rfCurv0, double &rfCurv1)
{
assert( _bIsFitted );
bool bResult = false;
if (_bIsFitted) {
FunctionContainer clFuncCont( _fCoeff );
bResult = clFuncCont.CurvatureInfo( x, y, z, rfCurv0, rfCurv1 );
}
return bResult;
}
double SurfaceFit::PolynomFit()
{
if (PlaneFit::Fit() >= FLOAT_MAX)
return double(FLOAT_MAX);
Base::Vector3d bs = Base::convertTo<Base::Vector3d>(this->_vBase);
Base::Vector3d ex = Base::convertTo<Base::Vector3d>(this->_vDirU);
Base::Vector3d ey = Base::convertTo<Base::Vector3d>(this->_vDirV);
//Base::Vector3d ez = Base::convertTo<Base::Vector3d>(this->_vDirW);
// A*x = b
// See also www.cs.jhu.edu/~misha/Fall05/10.23.05.pdf
// z = f(x,y) = a*x^2 + b*y^2 + c*x*y + d*x + e*y + f
// z = P * Vi with Vi=(xi^2,yi^2,xiyi,xi,yi,1) and P=(a,b,c,d,e,f)
// To get the best-fit values the sum needs to be minimized:
// S = sum[(z-zi)^2} -> min with zi=z coordinates of the given points
// <=> S = sum[z^2 - 2*z*zi + zi^2] -> min
// <=> S(P) = sum[(P*Vi)^2 - 2*(P*Vi)*zi + zi^2] -> min
// To get the optimum the gradient of the expression must be the null vector
// Note: grad F(P) = (P*Vi)^2 = 2*(P*Vi)*Vi
// grad G(P) = -2*(P*Vi)*zi = -2*Vi*zi
// grad H(P) = zi^2 = 0
// => grad S(P) = sum[2*(P*Vi)*Vi - 2*Vi*zi] = 0
// <=> sum[(P*Vi)*Vi] = sum[Vi*zi]
// <=> sum[(Vi*Vi^t)*P] = sum[Vi*zi] where (Vi*Vi^t) is a symmetric matrix
// <=> sum[(Vi*Vi^t)]*P = sum[Vi*zi]
Eigen::Matrix<double,6,6> A = Eigen::Matrix<double,6,6>::Zero();
Eigen::Matrix<double,6,1> b = Eigen::Matrix<double,6,1>::Zero();
Eigen::Matrix<double,6,1> x = Eigen::Matrix<double,6,1>::Zero();
std::vector<Base::Vector3d> transform;
transform.reserve(_vPoints.size());
double dW2 = 0;
for (std::list<Base::Vector3f>::const_iterator it = _vPoints.begin(); it != _vPoints.end(); ++it) {
Base::Vector3d clPoint = Base::convertTo<Base::Vector3d>(*it);
clPoint.TransformToCoordinateSystem(bs, ex, ey);
transform.push_back(clPoint);
double dU = clPoint.x;
double dV = clPoint.y;
double dW = clPoint.z;
double dU2 = dU*dU;
double dV2 = dV*dV;
double dUV = dU*dV;
dW2 += dW*dW;
A(0,0) = A(0,0) + dU2*dU2;
A(0,1) = A(0,1) + dU2*dV2;
A(0,2) = A(0,2) + dU2*dUV;
A(0,3) = A(0,3) + dU2*dU ;
A(0,4) = A(0,4) + dU2*dV ;
A(0,5) = A(0,5) + dU2 ;
b(0) = b(0) + dU2*dW ;
A(1,1) = A(1,1) + dV2*dV2;
A(1,2) = A(1,2) + dV2*dUV;
A(1,3) = A(1,3) + dV2*dU ;
A(1,4) = A(1,4) + dV2*dV ;
A(1,5) = A(1,5) + dV2 ;
b(1) = b(1) + dV2*dW ;
A(2,2) = A(2,2) + dUV*dUV;
A(2,3) = A(2,3) + dUV*dU ;
A(2,4) = A(2,4) + dUV*dV ;
A(2,5) = A(2,5) + dUV ;
b(3) = b(3) + dUV*dW ;
A(3,3) = A(3,3) + dU *dU ;
A(3,4) = A(3,4) + dU *dV ;
A(3,5) = A(3,5) + dU ;
b(3) = b(3) + dU *dW ;
A(4,4) = A(4,4) + dV *dV ;
A(4,5) = A(4,5) + dV ;
b(5) = b(5) + dV *dW ;
A(5,5) = A(5,5) + 1 ;
b(5) = b(5) + 1 *dW ;
}
// Mat is symmetric
//
A(1,0) = A(0,1);
A(2,0) = A(0,2);
A(3,0) = A(0,3);
A(4,0) = A(0,4);
A(5,0) = A(0,5);
A(2,1) = A(1,2);
A(3,1) = A(1,3);
A(4,1) = A(1,4);
A(5,1) = A(1,5);
A(3,2) = A(2,3);
A(4,2) = A(2,4);
A(5,2) = A(2,5);
A(4,3) = A(3,4);
A(5,3) = A(3,5);
A(5,4) = A(4,5);
Eigen::HouseholderQR< Eigen::Matrix<double,6,6> > qr(A);
x = qr.solve(b);
// FunctionContainer gets an implicit function F(x,y,z) = 0 of this form
// _fCoeff[0] +
// _fCoeff[1]*x + _fCoeff[2]*y + _fCoeff[3]*z +
// _fCoeff[4]*x^2 + _fCoeff[5]*y^2 + _fCoeff[6]*z^2 +
// _fCoeff[7]*x*y + _fCoeff[8]*x*z + _fCoeff[9]*y*z
//
// The bivariate polynomial surface we get here is of the form
// z = f(x,y) = a*x^2 + b*y^2 + c*x*y + d*x + e*y + f
// Writing it as implicit surface F(x,y,z) = 0 gives this form
// F(x,y,z) = f(x,y) - z = a*x^2 + b*y^2 + c*x*y + d*x + e*y - z + f
// Thus:
// _fCoeff[0] = f
// _fCoeff[1] = d
// _fCoeff[2] = e
// _fCoeff[3] = -1
// _fCoeff[4] = a
// _fCoeff[5] = b
// _fCoeff[6] = 0
// _fCoeff[7] = c
// _fCoeff[8] = 0
// _fCoeff[9] = 0
_fCoeff[0] = x(5);
_fCoeff[1] = x(3);
_fCoeff[2] = x(4);
_fCoeff[3] = -1.0;
_fCoeff[4] = x(0);
_fCoeff[5] = x(1);
_fCoeff[6] = 0.0;
_fCoeff[7] = x(2);
_fCoeff[8] = 0.0;
_fCoeff[9] = 0.0;
// Get S(P) = sum[(P*Vi)^2 - 2*(P*Vi)*zi + zi^2]
double sigma = 0;
FunctionContainer clFuncCont(_fCoeff);
for (std::vector<Base::Vector3d>::const_iterator it = transform.begin(); it != transform.end(); ++it) {
double u = it->x;
double v = it->y;
double z = clFuncCont.F(u, v, 0.0);
sigma += z*z;
}
sigma += dW2 - 2 * x.dot(b);
// This must be caused by some round-off errors. Theoretically it's impossible
// that 'sigma' becomes negative.
if (sigma < 0)
sigma = 0;
if (!_vPoints.empty())
sigma = sqrt(sigma/_vPoints.size());
_fLastResult = static_cast<float>(sigma);
return double(_fLastResult);
}
double SurfaceFit::Value(double x, double y) const
{
double z = 0.0;
if (_bIsFitted) {
FunctionContainer clFuncCont(_fCoeff);
z = clFuncCont.F(x, y, 0.0);
}
return z;
}
void SurfaceFit::GetCoefficients(double& a,double& b,double& c,double& d,double& e,double& f) const
{
a = _fCoeff[4];
b = _fCoeff[5];
c = _fCoeff[7];
d = _fCoeff[1];
e = _fCoeff[2];
f = _fCoeff[0];
}
void SurfaceFit::Transform(std::vector<Base::Vector3f>& pts) const
{
Base::Vector3d bs = Base::convertTo<Base::Vector3d>(this->_vBase);
Base::Vector3d ex = Base::convertTo<Base::Vector3d>(this->_vDirU);
Base::Vector3d ey = Base::convertTo<Base::Vector3d>(this->_vDirV);
Base::Vector3d ez = Base::convertTo<Base::Vector3d>(this->_vDirW);
Base::Matrix4D mat;
mat[0][0] = ex.x;
mat[0][1] = ey.x;
mat[0][2] = ez.x;
mat[0][3] = bs.x;
mat[1][0] = ex.y;
mat[1][1] = ey.y;
mat[1][2] = ez.y;
mat[1][3] = bs.y;
mat[2][0] = ex.z;
mat[2][1] = ey.z;
mat[2][2] = ez.z;
mat[2][3] = bs.z;
std::transform(pts.begin(), pts.end(), pts.begin(), [&mat](const Base::Vector3f& pt) {
Base::Vector3f v(pt);
mat.multVec(v, v);
return v;
});
}
void SurfaceFit::Transform(std::vector<Base::Vector3d>& pts) const
{
Base::Vector3d bs = Base::convertTo<Base::Vector3d>(this->_vBase);
Base::Vector3d ex = Base::convertTo<Base::Vector3d>(this->_vDirU);
Base::Vector3d ey = Base::convertTo<Base::Vector3d>(this->_vDirV);
Base::Vector3d ez = Base::convertTo<Base::Vector3d>(this->_vDirW);
Base::Matrix4D mat;
mat[0][0] = ex.x;
mat[0][1] = ey.x;
mat[0][2] = ez.x;
mat[0][3] = bs.x;
mat[1][0] = ex.y;
mat[1][1] = ey.y;
mat[1][2] = ez.y;
mat[1][3] = bs.y;
mat[2][0] = ex.z;
mat[2][1] = ey.z;
mat[2][2] = ez.z;
mat[2][3] = bs.z;
std::transform(pts.begin(), pts.end(), pts.begin(), [&mat](const Base::Vector3d& pt) {
Base::Vector3d v(pt);
mat.multVec(v, v);
return v;
});
}
/*!
* \brief SurfaceFit::toBezier
* This function computes the Bezier representation of the polynomial surface of the form
* f(x,y) = a*x*x + b*y*y + c*x*y + d*y + e*f + f
* by getting the 3x3 control points.
*/
std::vector<Base::Vector3d> SurfaceFit::toBezier(double umin, double umax, double vmin, double vmax) const
{
std::vector<Base::Vector3d> pts;
pts.reserve(9);
// the Bezier surface is defined by the 3x3 control points
// P11 P21 P31
// P12 P22 P32
// P13 P23 P33
//
// The surface goes through the points P11, P31, P31 and P33
// To get the four control points P21, P12, P32 and P23 we inverse
// the de-Casteljau algorithm used for Bezier curves of degree 2
// as we already know the points for the parameters
// (0, 0.5), (0.5, 0), (0.5, 1.0) and (1.0, 0.5)
// To get the control point P22 we inverse the de-Casteljau algorithm
// for the surface point on (0.5, 0.5)
double umid = 0.5 * (umin + umax);
double vmid = 0.5 * (vmin + vmax);
// first row
double z11 = Value(umin, vmin);
double v21 = Value(umid, vmin);
double z31 = Value(umax, vmin);
double z21 = 2.0 * v21 - 0.5 * (z11 + z31);
// third row
double z13 = Value(umin, vmax);
double v23 = Value(umid, vmax);
double z33 = Value(umax, vmax);
double z23 = 2.0 * v23 - 0.5 * (z13 + z33);
// second row
double v12 = Value(umin, vmid);
double z12 = 2.0 * v12 - 0.5 * (z11 + z13);
double v32 = Value(umax, vmid);
double z32 = 2.0 * v32 - 0.5 * (z31 + z33);
double v22 = Value(umid, vmid);
double z22 = 4.0 * v22 - 0.25 * (z11 + z31 + z13 + z33 + 2.0 * (z12 + z21 + z32 + z23));
// first row
pts.emplace_back(umin, vmin, z11);
pts.emplace_back(umid, vmin, z21);
pts.emplace_back(umax, vmin, z31);
// second row
pts.emplace_back(umin, vmid, z12);
pts.emplace_back(umid, vmid, z22);
pts.emplace_back(umax, vmid, z32);
// third row
pts.emplace_back(umin, vmax, z13);
pts.emplace_back(umid, vmax, z23);
pts.emplace_back(umax, vmax, z33);
return pts;
}
// -------------------------------------------------------------------------------
namespace MeshCore {
struct LMCylinderFunctor
{
Eigen::MatrixXd measuredValues;
// Compute 'm' errors, one for each data point, for the given parameter values in 'x'
int operator()(const Eigen::VectorXd &x, Eigen::VectorXd &fvec) const
{
// 'x' has dimensions n x 1
// It contains the current estimates for the parameters.
// 'fvec' has dimensions m x 1
// It will contain the error for each data point.
double aParam = x(0); // dir_x
double bParam = x(1); // dir_y
double cParam = x(2); // dir_z
double dParam = x(3); // cnt_x
double eParam = x(4); // cnt_y
double fParam = x(5); // cnt_z
double gParam = x(6); // radius
// use distance functions (fvec(i)) for cylinders as defined in the paper:
// Least-Squares Fitting Algorithms of the NIST Algorithm Testing System
for (int i = 0; i < values(); i++) {
double xValue = measuredValues(i, 0);
double yValue = measuredValues(i, 1);
double zValue = measuredValues(i, 2);
double a = aParam/(sqrt(aParam*aParam + bParam*bParam + cParam*cParam));
double b = bParam/(sqrt(aParam*aParam + bParam*bParam + cParam*cParam));
double c = cParam/(sqrt(aParam*aParam + bParam*bParam + cParam*cParam));
double x = dParam;
double y = eParam;
double z = fParam;
double u = c * (yValue - y) - b * (zValue - z);
double v = a * (zValue - z) - c * (xValue - x);
double w = b * (xValue - x) - a * (yValue - y);
fvec(i) = sqrt(u*u + v*v + w*w) - gParam;
}
return 0;
}
// Compute the jacobian of the errors
int df(const Eigen::VectorXd &x, Eigen::MatrixXd &fjac) const
{
// 'x' has dimensions n x 1
// It contains the current estimates for the parameters.
// 'fjac' has dimensions m x n
// It will contain the jacobian of the errors, calculated numerically in this case.
double epsilon;
epsilon = 1e-5;
for (int i = 0; i < x.size(); i++) {
Eigen::VectorXd xPlus(x);
xPlus(i) += epsilon;
Eigen::VectorXd xMinus(x);
xMinus(i) -= epsilon;
Eigen::VectorXd fvecPlus(values());
operator()(xPlus, fvecPlus);
Eigen::VectorXd fvecMinus(values());
operator()(xMinus, fvecMinus);
Eigen::VectorXd fvecDiff(values());
fvecDiff = (fvecPlus - fvecMinus) / (2.0f * epsilon);
fjac.block(0, i, values(), 1) = fvecDiff;
}
return 0;
}
// Number of data points, i.e. values.
int m;
// Returns 'm', the number of values.
int values() const { return m; }
// The number of parameters, i.e. inputs.
int n;
// Returns 'n', the number of inputs.
int inputs() const { return n; }
};
}
CylinderFit::CylinderFit()
: _vBase(0,0,0)
, _vAxis(0,0,1)
, _fRadius(0)
, _initialGuess(false)
{
}
CylinderFit::~CylinderFit()
{
}
Base::Vector3f CylinderFit::GetInitialAxisFromNormals(const std::vector<Base::Vector3f>& n) const
{
PlaneFit planeFit;
planeFit.AddPoints(n);
planeFit.Fit();
return planeFit.GetNormal();
}
void CylinderFit::SetInitialValues(const Base::Vector3f& b, const Base::Vector3f& n)
{
_vBase = b;
_vAxis = n;
_initialGuess = true;
}
float CylinderFit::Fit()
{
if (CountPoints() < 7)
return FLOAT_MAX;
_bIsFitted = true;
#if 1
std::vector<Wm4::Vector3d> input;
std::transform(_vPoints.begin(), _vPoints.end(), std::back_inserter(input),
[](const Base::Vector3f& v) { return Wm4::Vector3d(v.x, v.y, v.z); });
Wm4::Vector3d cnt, axis;
if (_initialGuess) {
cnt = Base::convertTo<Wm4::Vector3d>(_vBase);
axis = Base::convertTo<Wm4::Vector3d>(_vAxis);
}
double radius, height;
Wm4::CylinderFit3<double> fit(input.size(), input.data(), cnt, axis, radius, height, _initialGuess);
_initialGuess = false;
_vBase = Base::convertTo<Base::Vector3f>(cnt);
_vAxis = Base::convertTo<Base::Vector3f>(axis);
_fRadius = float(radius);
_fLastResult = double(fit);
#if defined(FC_DEBUG)
Base::Console().Message(" WildMagic Cylinder Fit: Base: (%0.4f, %0.4f, %0.4f), Axis: (%0.6f, %0.6f, %0.6f), Radius: %0.4f, Std Dev: %0.4f\n",
_vBase.x, _vBase.y, _vBase.z, _vAxis.x, _vAxis.y, _vAxis.z, _fRadius, GetStdDeviation());
#endif
MeshCoreFit::CylinderFit cylFit;
cylFit.AddPoints(_vPoints);
//cylFit.SetApproximations(_fRadius, Base::Vector3d(_vBase.x, _vBase.y, _vBase.z), Base::Vector3d(_vAxis.x, _vAxis.y, _vAxis.z));
// Do the cylinder fit
float result = cylFit.Fit();
if (result < FLOAT_MAX) {
Base::Vector3d base = cylFit.GetBase();
Base::Vector3d dir = cylFit.GetAxis();
#if defined(FC_DEBUG)
Base::Console().Message("MeshCoreFit::Cylinder Fit: Base: (%0.4f, %0.4f, %0.4f), Axis: (%0.6f, %0.6f, %0.6f), Radius: %0.4f, Std Dev: %0.4f, Iterations: %d\n",
base.x, base.y, base.z, dir.x, dir.y, dir.z, cylFit.GetRadius(), cylFit.GetStdDeviation(), cylFit.GetNumIterations());
#endif
_vBase = Base::convertTo<Base::Vector3f>(base);
_vAxis = Base::convertTo<Base::Vector3f>(dir);
_fRadius = (float)cylFit.GetRadius();
_fLastResult = result;
}
#else
int m = static_cast<int>(_vPoints.size());
int n = 7;
Eigen::MatrixXd measuredValues(m, 3);
int index = 0;
for (const auto& it : _vPoints) {
measuredValues(index, 0) = it.x;
measuredValues(index, 1) = it.y;
measuredValues(index, 2) = it.z;
index++;
}
Eigen::VectorXd x(n);
x(0) = 1.0; // initial value for dir_x
x(1) = 1.0; // initial value for dir_y
x(2) = 1.0; // initial value for dir_z
x(3) = 0.0; // initial value for cnt_x
x(4) = 0.0; // initial value for cnt_y
x(5) = 0.0; // initial value for cnt_z
x(6) = 0.0; // initial value for radius
//
// Run the LM optimization
// Create a LevenbergMarquardt object and pass it the functor.
//
LMCylinderFunctor functor;
functor.measuredValues = measuredValues;
functor.m = m;
functor.n = n;
Eigen::LevenbergMarquardt<LMCylinderFunctor, double> lm(functor);
int status = lm.minimize(x);
Base::Console().Log("Cylinder fit: %d, iterations: %d, gradient norm: %f\n", status, lm.iter, lm.gnorm);
_vAxis.x = x(0);
_vAxis.y = x(1);
_vAxis.z = x(2);
_vAxis.Normalize();
_vBase.x = x(3);
_vBase.y = x(4);
_vBase.z = x(5);
_fRadius = x(6);
_fLastResult = lm.gnorm;
#endif
return _fLastResult;
}
float CylinderFit::GetRadius() const
{
return _fRadius;
}
Base::Vector3f CylinderFit::GetBase() const
{
if (_bIsFitted)
return _vBase;
else
return Base::Vector3f();
}
Base::Vector3f CylinderFit::GetAxis() const
{
if (_bIsFitted)
return _vAxis;
else
return Base::Vector3f();
}
float CylinderFit::GetDistanceToCylinder(const Base::Vector3f &rcPoint) const
{
float fResult = FLOAT_MAX;
if (_bIsFitted)
fResult = rcPoint.DistanceToLine(_vBase, _vAxis) - _fRadius;
return fResult;
}
float CylinderFit::GetStdDeviation() const
{
// Mean: M=(1/N)*SUM Xi
// Variance: VAR=(N/N-1)*[(1/N)*SUM(Xi^2)-M^2]
// Standard deviation: SD=SQRT(VAR)
// Standard error of the mean: SE=SD/SQRT(N)
if (!_bIsFitted)
return FLOAT_MAX;
float fSumXi = 0.0f, fSumXi2 = 0.0f,
fMean = 0.0f, fDist = 0.0f;
float ulPtCt = float(CountPoints());
std::list< Base::Vector3f >::const_iterator cIt;
for (cIt = _vPoints.begin(); cIt != _vPoints.end(); ++cIt) {
fDist = GetDistanceToCylinder( *cIt );
fSumXi += fDist;
fSumXi2 += ( fDist * fDist );
}
fMean = (1.0f / ulPtCt) * fSumXi;
return sqrt((ulPtCt / (ulPtCt - 1.0f)) * ((1.0f / ulPtCt) * fSumXi2 - fMean * fMean));
}
void CylinderFit::GetBounding(Base::Vector3f& bottom, Base::Vector3f& top) const
{
float distMin = FLT_MAX;
float distMax = FLT_MIN;
std::list<Base::Vector3f>::const_iterator cIt;
for (cIt = _vPoints.begin(); cIt != _vPoints.end(); ++cIt) {
float dist = cIt->DistanceToPlane(_vBase, _vAxis);
if (dist < distMin) {
distMin = dist;
bottom = *cIt;
}
if (dist > distMax) {
distMax = dist;
top = *cIt;
}
}
// Project the points onto the cylinder axis
bottom = bottom.Perpendicular(_vBase, _vAxis);
top = top.Perpendicular(_vBase, _vAxis);
}
void CylinderFit::ProjectToCylinder()
{
Base::Vector3f cBase(GetBase());
Base::Vector3f cAxis(GetAxis());
for (std::list< Base::Vector3f >::iterator it = _vPoints.begin(); it != _vPoints.end(); ++it) {
Base::Vector3f& cPnt = *it;
if (cPnt.DistanceToLine(cBase, cAxis) > 0) {
Base::Vector3f proj;
cBase.ProjectToPlane(cPnt, cAxis, proj);
Base::Vector3f diff = cPnt - proj;
diff.Normalize();
cPnt = proj + diff * _fRadius;
}
else {
// Point is on the cylinder axis, so it can be moved in
// any direction perpendicular to the cylinder axis
Base::Vector3f cMov(cPnt);
do {
float x = (float(rand()) / float(RAND_MAX));
float y = (float(rand()) / float(RAND_MAX));
float z = (float(rand()) / float(RAND_MAX));
cMov.Move(x,y,z);
}
while (cMov.DistanceToLine(cBase, cAxis) == 0);
Base::Vector3f proj;
cMov.ProjectToPlane(cPnt, cAxis, proj);
Base::Vector3f diff = cPnt - proj;
diff.Normalize();
cPnt = proj + diff * _fRadius;
}
}
}
// -----------------------------------------------------------------------------
SphereFit::SphereFit()
: _vCenter(0,0,0)
, _fRadius(0)
{
}
SphereFit::~SphereFit()
{
}
float SphereFit::GetRadius() const
{
if (_bIsFitted)
return _fRadius;
else
return FLOAT_MAX;
}
Base::Vector3f SphereFit::GetCenter() const
{
if (_bIsFitted)
return _vCenter;
else
return Base::Vector3f();
}
float SphereFit::Fit()
{
_bIsFitted = true;
if (CountPoints() < 4)
return FLOAT_MAX;
std::vector<Wm4::Vector3d> input;
std::transform(_vPoints.begin(), _vPoints.end(), std::back_inserter(input),
[](const Base::Vector3f& v) { return Wm4::Vector3d(v.x, v.y, v.z); });
Wm4::Sphere3d sphere;
Wm4::SphereFit3<double>(input.size(), input.data(), 10, sphere, false);
_vCenter = Base::convertTo<Base::Vector3f>(sphere.Center);
_fRadius = float(sphere.Radius);
// TODO
_fLastResult = 0;
#if defined(_DEBUG)
Base::Console().Message(" WildMagic Sphere Fit: Center: (%0.4f, %0.4f, %0.4f), Radius: %0.4f, Std Dev: %0.4f\n",
_vCenter.x, _vCenter.y, _vCenter.z, _fRadius, GetStdDeviation());
#endif
MeshCoreFit::SphereFit sphereFit;
sphereFit.AddPoints(_vPoints);
sphereFit.ComputeApproximations();
float result = sphereFit.Fit();
if (result < FLOAT_MAX) {
Base::Vector3d center = sphereFit.GetCenter();
#if defined(_DEBUG)
Base::Console().Message("MeshCoreFit::Sphere Fit: Center: (%0.4f, %0.4f, %0.4f), Radius: %0.4f, Std Dev: %0.4f, Iterations: %d\n",
center.x, center.y, center.z, sphereFit.GetRadius(), sphereFit.GetStdDeviation(), sphereFit.GetNumIterations());
#endif
_vCenter = Base::convertTo<Base::Vector3f>(center);
_fRadius = (float)sphereFit.GetRadius();
_fLastResult = result;
}
return _fLastResult;
}
float SphereFit::GetDistanceToSphere(const Base::Vector3f& rcPoint) const
{
float fResult = FLOAT_MAX;
if (_bIsFitted) {
fResult = Base::Vector3f(rcPoint - _vCenter).Length() - _fRadius;
}
return fResult;
}
float SphereFit::GetStdDeviation() const
{
// Mean: M=(1/N)*SUM Xi
// Variance: VAR=(N/N-1)*[(1/N)*SUM(Xi^2)-M^2]
// Standard deviation: SD=SQRT(VAR)
// Standard error of the mean: SE=SD/SQRT(N)
if (!_bIsFitted)
return FLOAT_MAX;
float fSumXi = 0.0f, fSumXi2 = 0.0f,
fMean = 0.0f, fDist = 0.0f;
float ulPtCt = float(CountPoints());
std::list< Base::Vector3f >::const_iterator cIt;
for (cIt = _vPoints.begin(); cIt != _vPoints.end(); ++cIt) {
fDist = GetDistanceToSphere( *cIt );
fSumXi += fDist;
fSumXi2 += ( fDist * fDist );
}
fMean = (1.0f / ulPtCt) * fSumXi;
return sqrt((ulPtCt / (ulPtCt - 1.0f)) * ((1.0f / ulPtCt) * fSumXi2 - fMean * fMean));
}
void SphereFit::ProjectToSphere()
{
for (std::list< Base::Vector3f >::iterator it = _vPoints.begin(); it != _vPoints.end(); ++it) {
Base::Vector3f& cPnt = *it;
// Compute unit vector from sphere centre to point.
// Because this vector is orthogonal to the sphere's surface at the
// intersection point we can easily compute the projection point on the
// closest surface point using the radius of the sphere
Base::Vector3f diff = cPnt - _vCenter;
double length = diff.Length();
if (length == 0.0)
{
// Point is exactly at the sphere center, so it can be projected in any direction onto the sphere!
// So here just project in +Z direction
cPnt.z += _fRadius;
}
else
{
diff /= length; // normalizing the vector
cPnt = _vCenter + diff * _fRadius;
}
}
}
// -------------------------------------------------------------------------------
PolynomialFit::PolynomialFit()
{
for (int i=0; i<9; i++)
_fCoeff[i] = 0.0f;
}
PolynomialFit::~PolynomialFit()
{
}
float PolynomialFit::Fit()
{
std::vector<float> x, y, z;
x.reserve(_vPoints.size());
y.reserve(_vPoints.size());
z.reserve(_vPoints.size());
for (std::list<Base::Vector3f>::const_iterator it = _vPoints.begin(); it != _vPoints.end(); ++it) {
x.push_back(it->x);
y.push_back(it->y);
z.push_back(it->z);
}
try {
float* coeff = Wm4::PolyFit3<float>(_vPoints.size(), &(x[0]), &(y[0]), &(z[0]), 2, 2);
for (int i=0; i<9; i++)
_fCoeff[i] = coeff[i];
}
catch (const std::exception&) {
return FLOAT_MAX;
}
return 0.0f;
}
float PolynomialFit::Value(float x, float y) const
{
float fValue =
_fCoeff[0] +
_fCoeff[1] * x +
_fCoeff[2] * x * x +
_fCoeff[3] * y +
_fCoeff[4] * x * y +
_fCoeff[5] * x * x * y +
_fCoeff[6] * y * y +
_fCoeff[7] * x * y * y +
_fCoeff[8] * x * x * y * y;
return fValue;
}