#include <Polynomial.h>

Inheritance diagram for mirtk::Polynomial:

Collaboration diagram for mirtk::Polynomial:

Public Member Functions
void	Coefficient (int i, double c)

double	Coefficient (int i) const

void	Coefficients (const Vector &coeff)

Vector	Evaluate (const Matrix &x) const

Vector	Evaluate (const PointSet &x, bool twoD=false) const

Vector	Evaluate (const Vector &x) const

double	Evaluate (const Point &x, bool twoD=false) const

double	Evaluate (double x, double y, double z) const

double	Evaluate (double x, double y) const

double	Evaluate (double x) const

Vector	Evaluate1stOrderDerivative (int j, const Matrix &x) const

Vector	Evaluate1stOrderDerivative (int j, const PointSet &x, bool twoD=false) const

Vector	Evaluate1stOrderDerivative (int j, const Vector &x) const

double	Evaluate1stOrderDerivative (int j, const Point &x, bool twoD=false) const

double	Evaluate1stOrderDerivative (int j, double x) const

Vector	Evaluate2ndOrderDerivative (int j1, int j2, const Matrix &x) const

Vector	Evaluate2ndOrderDerivative (int j1, int j2, const PointSet &x, bool twoD=false) const

Vector	Evaluate2ndOrderDerivative (int j1, int j2, const Vector &x) const

double	Evaluate2ndOrderDerivative (int j1, int j2, const Point &x, bool twoD=false) const

double	Evaluate2ndOrderDerivative (int j1, int j2, double x) const

double	EvaluateGaussianCurvature (const Point &x) const

Vector3	EvaluateGradient (const Point &x) const

Matrix3x3	EvaluateHessian (const Point &x) const

double	EvaluateMeanCurvature (const Point &x) const

double	EvaluateTaubinDistance (const Point &x) const

int	Exponent (int i, int j=0) const

double	Fit (const Matrix &x, const Vector &y)

double	Fit (const Matrix &x, const Vector &y, const Array< int > &subset)

double	Fit (const Matrix &x, const Vector &y, const OrderedSet< int > &subset)

double	Fit (const PointSet &x, const Vector &y, bool twoD=false)

double	Fit (const Vector &x, const Vector &y)

double	FitSurface (const PointSet &x)

double	FitSurface (const PointSet &x, const Array< int > &subset)

double	FitSurface (const PointSet &x, const OrderedSet< int > &subset)

double	FitSurface (const PointSet &x, const PointSet &n, double c=1.0)

double	FitSurface (const PointSet &x, const PointSet &n, const Array< int > &subset, double c=1.0)

double	FitSurface (const PointSet &x, const PointSet &n, const OrderedSet< int > &subset, double c=1.0)

int	Initialize (int p, int order=0)

bool	IsConstant (int i) const

int	NumberOfActiveTerms () const
	Number of active model terms/coefficients.

int	NumberOfPassiveTerms () const
	Number of passive model terms/coefficients.

int	NumberOfTerms () const
	Number of model terms/coefficients.

Polynomial &	operator= (const Polynomial &)
	Assignment operator.

	Polynomial (int order=2)

	Polynomial (int p, int order, const Vector &coeff=Vector())

	Polynomial (const Polynomial &)
	Copy constructor.

ostream &	Print (ostream &os, Indent=0) const
	Print polynomial model equation.

void	Print (Indent=0) const
	Print polynomial model equation.

void	SetCoefficientsToZero ()
	Set all model coefficients to zero.

void	SetConstantCoefficient (double value, enum Status status=Passive)

enum Status	Status (int i) const

void	Status (int i, enum Status s)

virtual	~Polynomial ()
	Destructor.

Public Member Functions inherited from mirtk::Object
virtual const char *	NameOfClass () const =0
	Get name of class, which this object is an instance of.

virtual ParameterList	Parameter () const
	Get parameter name/value pairs.

bool	Parameter (const ParameterList &)
	Set parameters from name/value pairs.

virtual bool	Set (const char name, const char value)

virtual	~Object ()
	Destructor.

Additional Inherited Members
Static Public Member Functions inherited from mirtk::Object
static const char *	NameOfType ()
	Get name of this class type.

Protected Member Functions inherited from mirtk::Object
template<typename... Args>
void	Throw (ErrorType err, const char *func, Args... args) const

Static Protected Member Functions inherited from mirtk::Object
template<typename... Args>
static void	ThrowStatic (ErrorType err, const char cls, const char func, Args... args)

Detailed Description

N-dimensional polynomial regression model.

This implementation is based on the polyfitn and polyvaln MATLAB functions written and distributed on MathCentral by John D'Errico.

See also: http://uk.mathworks.com/matlabcentral/fileexchange/34765-polyfitn

Definition at line 47 of file Polynomial.h.

Constructor & Destructor Documentation

§ Polynomial() [1/2]

mirtk::Polynomial::Polynomial ( int order = 2 )

Constructor

Parameters

[in] order Order of the polynomial, i.e., highest model term exponent.

§ Polynomial() [2/2]

mirtk::Polynomial::Polynomial	(	int	p,
		int	order,
		const Vector &	coeff = `Vector()`
	)

Construct complete polynomial

Parameters

[in]	p	Dimension of independent variable space.
[in]	order	Order of the polynomial, i.e., highest model term exponent.
[in]	coeff	Coefficients of each model term. If not specified, the coefficients are initialized to zero. Use Coefficients(const Vector &) in this case to set the coefficients of the model terms after model construction.

Member Function Documentation

§ Coefficient() [1/2]

void mirtk::Polynomial::Coefficient	(	int	i,
		double	c
	)

inline

Set coefficient of i-th term

Parameters

[in]	i	Index of model term.
[in]	c	Model term coefficient.

Definition at line 587 of file Polynomial.h.

§ Coefficient() [2/2]

double mirtk::Polynomial::Coefficient ( int i ) const

inline

Get coefficient of i-th term

Parameters

[in] i Index of model term.

Returns: Coefficient of i-th term.

Definition at line 594 of file Polynomial.h.

§ Coefficients()

void mirtk::Polynomial::Coefficients ( const Vector & coeff )

inline

Set coefficients of polynomial model terms

Parameters

[in] coeff Coefficient vector of length NumberOfTerms().

Definition at line 580 of file Polynomial.h.

§ Evaluate() [1/7]

Vector mirtk::Polynomial::Evaluate ( const Matrix & x ) const

Evaluates polynomial for n p-dimensional data points

Parameters

[in] x Matrix of size (n x p), where n is the number of data points to evaluate, and p is the dimension of the independent variable space of the polynomial model.

Returns: Regressed value.

§ Evaluate() [2/7]

Vector mirtk::Polynomial::Evaluate	(	const PointSet &	x,
		bool	twoD = `false`
	)		const

inline

Evaluates polynomial for n 2- or 3-dimensional data points

Parameters

[in]	x	Data points. The dimension of the model must be 2 or 3.
[in]	twoD	Whether to ignore z coordinate.

Returns: Regressed value.

Definition at line 641 of file Polynomial.h.

§ Evaluate() [3/7]

Vector mirtk::Polynomial::Evaluate ( const Vector & x ) const

inline

Evaluates polynomial for n 1-dimensional data points

Parameters

[in] x Values of independent variable. The dimension of the model must be 1.

Returns: Regressed values.

Definition at line 649 of file Polynomial.h.

§ Evaluate() [4/7]

double mirtk::Polynomial::Evaluate	(	const Point &	x,
		bool	twoD = `false`
	)		const

inline

Evaluates polynomial for one 3D point

Parameters

[in]	x	Data point. The dimension of the model must be 2 or 3.
[in]	twoD	Whether to ignore z coordinate.

Returns: Regressed value.

Definition at line 656 of file Polynomial.h.

§ Evaluate() [5/7]

double mirtk::Polynomial::Evaluate	(	double	x,
		double	y,
		double	z
	)		const

inline

Evaluates polynomial for one 3D point

Parameters

[in]	x	First point coordinate.
[in]	y	Second point coordinate.
[in]	z	Third point coordinate.

Returns: Regressed value.

Definition at line 668 of file Polynomial.h.

§ Evaluate() [6/7]

double mirtk::Polynomial::Evaluate	(	double	x,
		double	y
	)		const

inline

Evaluates polynomial for one 2D point

Parameters

[in]	x	First point coordinate.
[in]	y	Second point coordinate.

Returns: Regressed value.

Definition at line 679 of file Polynomial.h.

§ Evaluate() [7/7]

double mirtk::Polynomial::Evaluate ( double x ) const

inline

Evaluates polynomial for one independent variable value

Parameters

[in] x Data point. The dimension of the model must be 1.

Returns: Regressed value.

Definition at line 689 of file Polynomial.h.

§ Evaluate1stOrderDerivative() [1/5]

Vector mirtk::Polynomial::Evaluate1stOrderDerivative	(	int	j,
		const Matrix &	x
	)		const

Evaluate 1st order partial derivative of polynomial

Parameters

[in]	j	Index of independent variable w.r.t. which the derivative is taken.
[in]	x	Matrix of size (n x p), where n is the number of data points to evaluate, and p is the dimension of the independent variable space of the polynomial model.

Returns: Values of 1st order derivative evaluated at given data points.

§ Evaluate1stOrderDerivative() [2/5]

Vector mirtk::Polynomial::Evaluate1stOrderDerivative	(	int	j,
		const PointSet &	x,
		bool	twoD = `false`
	)		const

inline

Evaluate 1st order partial derivative of polynomial

Parameters

[in]	j	Index of independent variable w.r.t. which the derivative is taken.
[in]	x	Data points. The dimension of the model must be 2 or 3.
[in]	twoD	Whether to ignore z coordinate.

Returns: Values of 1st order derivative evaluated at given data points.

Definition at line 702 of file Polynomial.h.

§ Evaluate1stOrderDerivative() [3/5]

Vector mirtk::Polynomial::Evaluate1stOrderDerivative	(	int	j,
		const Vector &	x
	)		const

inline

Evaluate 1st order partial derivative of polynomial

Parameters

[in]	j	Index of independent variable w.r.t. which the derivative is taken.
[in]	x	Values of independent variable. The dimension of the model must be 1.

Returns: Values of 1st order derivative evaluated at given data points.

Definition at line 710 of file Polynomial.h.

§ Evaluate1stOrderDerivative() [4/5]

double mirtk::Polynomial::Evaluate1stOrderDerivative	(	int	j,
		const Point &	x,
		bool	twoD = `false`
	)		const

inline

Evaluate 1st order partial derivative of polynomial

Parameters

[in]	j	Index of independent variable w.r.t. which the derivative is taken.
[in]	x	Data point. The dimension of the model must be 2 or 3.
[in]	twoD	Whether to ignore z coordinate.

Returns: Value of 1st order derivative evaluated at given data point.

Definition at line 717 of file Polynomial.h.

§ Evaluate1stOrderDerivative() [5/5]

double mirtk::Polynomial::Evaluate1stOrderDerivative	(	int	j,
		double	x
	)		const

inline

Evaluate 1st order partial derivative of polynomial

Parameters

[in]	j	Index of independent variable w.r.t. which the derivative is taken.
[in]	x	Data point. The dimension of the model must be 1.

Returns: Value of 1st order derivative evaluated at given data point.

Definition at line 729 of file Polynomial.h.

§ Evaluate2ndOrderDerivative() [1/5]

Vector mirtk::Polynomial::Evaluate2ndOrderDerivative	(	int	j1,
		int	j2,
		const Matrix &	x
	)		const

Evaluate 2nd order partial derivative of polynomial

Parameters

[in]	x	Matrix of size (n x p), where n is the number of data points to evaluate, and p is the dimension of the independent variable space of the polynomial model.
[in]	j1	Index of independent variable w.r.t. which the 1st derivative is taken.
[in]	j2	Index of independent variable w.r.t. which the 2nd derivative is taken.

Returns: Values of 2nd order derivative evaluated at given data points.

§ Evaluate2ndOrderDerivative() [2/5]

Vector mirtk::Polynomial::Evaluate2ndOrderDerivative	(	int	j1,
		int	j2,
		const PointSet &	x,
		bool	twoD = `false`
	)		const

inline

Evaluate 2nd order partial derivative of polynomial

Parameters

[in]	j1	Index of independent variable w.r.t. which the 1st derivative is taken.
[in]	j2	Index of independent variable w.r.t. which the 2nd derivative is taken.
[in]	x	Data points. The dimension of the model must be 2 or 3.
[in]	twoD	Whether to ignore z coordinate.

Returns: Values of 2nd order derivative evaluated at given data points.

Definition at line 742 of file Polynomial.h.

§ Evaluate2ndOrderDerivative() [3/5]

Vector mirtk::Polynomial::Evaluate2ndOrderDerivative	(	int	j1,
		int	j2,
		const Vector &	x
	)		const

inline

Evaluate 2nd order partial derivative of polynomial

Parameters

[in]	j1	Index of independent variable w.r.t. which the 1st derivative is taken.
[in]	j2	Index of independent variable w.r.t. which the 2nd derivative is taken.
[in]	x	Values of independent variable. The dimension of the model must be 1.

Returns: Values of 2nd order derivative evaluated at given data points.

Definition at line 750 of file Polynomial.h.

§ Evaluate2ndOrderDerivative() [4/5]

double mirtk::Polynomial::Evaluate2ndOrderDerivative	(	int	j1,
		int	j2,
		const Point &	x,
		bool	twoD = `false`
	)		const

inline

Evaluate 2nd order partial derivative of polynomial

Parameters

[in]	j1	Index of independent variable w.r.t. which the 1st derivative is taken.
[in]	j2	Index of independent variable w.r.t. which the 2nd derivative is taken.
[in]	x	Data point. The dimension of the model must be 2 or 3.
[in]	twoD	Whether to ignore z coordinate.

Returns: Value of 2nd order derivative evaluated at given data point.

Definition at line 757 of file Polynomial.h.

§ Evaluate2ndOrderDerivative() [5/5]

double mirtk::Polynomial::Evaluate2ndOrderDerivative	(	int	j1,
		int	j2,
		double	x
	)		const

inline

Evaluate 2nd order partial derivative of polynomial

Parameters

[in]	j1	Index of independent variable w.r.t. which the 1st derivative is taken.
[in]	j2	Index of independent variable w.r.t. which the 2nd derivative is taken.
[in]	x	Data point. The dimension of the model must be 1.

Returns: Value of 2nd order derivative evaluated at given data point.

Definition at line 769 of file Polynomial.h.

§ EvaluateGaussianCurvature()

double mirtk::Polynomial::EvaluateGaussianCurvature ( const Point & x ) const

Evaluate Gaussian curvature of implicit polynomial surface

Ron Goldman, Curvature formulas for implicit curves and surfaces, Computer Aided Geometric Design 22 (2005) 632–658.

See also: http://www.cgeo.ulg.ac.be/CAO/Goldman_Curvature_formulas_implicit.pdf

Parameters

[in] x Data point. The dimension of the model must be 3.

Returns: Gaussian curvature of implicit surface at x.

§ EvaluateGradient()

Vector3 mirtk::Polynomial::EvaluateGradient ( const Point & x ) const

Evaluate gradient of 3D polynomial

Parameters

[in] x Data point. The dimension of the model must be 3.

Returns: Values of 1st order derivatives evaluated at given data point.

§ EvaluateHessian()

Matrix3x3 mirtk::Polynomial::EvaluateHessian ( const Point & x ) const

Evaluate Hessian of 3D polynomial

Parameters

[in] x Data point. The dimension of the model must be 3.

Returns: Values of 2nd order derivatives evaluated at given data point.

§ EvaluateMeanCurvature()

double mirtk::Polynomial::EvaluateMeanCurvature ( const Point & x ) const

Evaluate mean curvature of implicit polynomial surface

Ron Goldman, Curvature formulas for implicit curves and surfaces, Computer Aided Geometric Design 22 (2005) 632–658.

See also: http://www.cgeo.ulg.ac.be/CAO/Goldman_Curvature_formulas_implicit.pdf

Parameters

[in] x Data point. The dimension of the model must be 3.

Returns: Mean curvature of implicit surface at x.

§ EvaluateTaubinDistance()

double mirtk::Polynomial::EvaluateTaubinDistance ( const Point & x ) const

Compute Taubin distance of a point to the implicit polynomial surface

The Taubin distance is the agebraic distance, i.e., the value of the implicit polynomial function at x, divided the norm of its gradient. It is a first-order approximation to the Euclidean distance of the point to the closest point on the surface.

Parameters

[in] x Data point. The dimension of the model must be 3.

Returns: Taubin distance of the point to the surface.

§ Exponent()

int mirtk::Polynomial::Exponent	(	int	i,
		int	j = `0`
	)		const

inline

Get exponent of independent variable in specified model term

Parameters

[in]	i	Index of model term.
[in]	j	Index of independent variable.

Returns: Exponent of j-th independent variable in i-th model term.

Definition at line 565 of file Polynomial.h.

§ Fit() [1/5]

double mirtk::Polynomial::Fit	(	const Matrix &	x,
		const Vector &	y
	)

Fits polynomial regression model to one or more independent variables

Parameters

[in]	x	Values of independent variables, a matrix of size (n x p), where n is the number of data points and p is the dimension of the independent variable space.
[in]	y	Values of dependent variable.

Returns: RMS error of the regression.

§ Fit() [2/5]

double mirtk::Polynomial::Fit	(	const Matrix &	x,
		const Vector &	y,
		const Array< int > &	subset
	)

Fits polynomial regression model to one or more independent variables

Parameters

[in]	x	Values of independent variables, a matrix of size (n x p), where n is the number of data points and p is the dimension of the independent variable space.
[in]	subset	Indices of points to use for fitting.
[in]	y	Values of dependent variable.

Returns: RMS error of the regression.

§ Fit() [3/5]

double mirtk::Polynomial::Fit	(	const Matrix &	x,
		const Vector &	y,
		const OrderedSet< int > &	subset
	)

Fits polynomial regression model to one or more independent variables

Parameters

[in]	x	Values of independent variables, a matrix of size (n x p), where n is the number of data points and p is the dimension of the independent variable space.
[in]	subset	Indices of points to use for fitting.
[in]	y	Values of dependent variable.

Returns: RMS error of the regression.

§ Fit() [4/5]

double mirtk::Polynomial::Fit	(	const PointSet &	x,
		const Vector &	y,
		bool	twoD = `false`
	)

inline

Fits polynomial regression model to one or more independent variables

Parameters

[in]	x	Values of independent variables. The dimension of the independent variable space is 2 or 3.
[in]	y	Values of dependent variable.
[in]	twoD	Whether to ignore z coordinate.

Returns: RMS error of the regression.

Definition at line 625 of file Polynomial.h.

§ Fit() [5/5]

double mirtk::Polynomial::Fit	(	const Vector &	x,
		const Vector &	y
	)

inline

Fits polynomial regression model to one independent variable

Parameters

[in]	x	Values of independent variable.
[in]	y	Values of dependent variable.

Returns: RMS error of the regression.

Definition at line 631 of file Polynomial.h.

§ FitSurface() [1/6]

double mirtk::Polynomial::FitSurface ( const PointSet & x )

Fits polynomial surface model to 3D point cloud

The dependent variable of the surface model is the algebraic distance of a point from the surface. This function sets the coefficients of constant model term(s) to 1 and excludes them from the fit to avoid the trivial solution of the homogeneous linear system of equations.

Parameters

[in] x Points on surface.

Returns: RMS error of the regression.

§ FitSurface() [2/6]

double mirtk::Polynomial::FitSurface	(	const PointSet &	x,
		const Array< int > &	subset
	)

Fits polynomial surface model to subset of 3D point cloud

The dependent variable of the surface model is the algebraic distance of a point from the surface. This function sets the coefficients of constant model term(s) to 1 and excludes them from the fit to avoid the trivial solution of the homogeneous linear system of equations.

Parameters

[in]	x	Points on surface.
[in]	subset	Indices of points to use for fitting.

Returns: RMS error of the regression.

§ FitSurface() [3/6]

double mirtk::Polynomial::FitSurface	(	const PointSet &	x,
		const OrderedSet< int > &	subset
	)

Fits polynomial surface model to subset of 3D point cloud

The dependent variable of the surface model is the algebraic distance of a point from the surface. This function sets the coefficients of constant model term(s) to 1 and excludes them from the fit to avoid the trivial solution of the homogeneous linear system of equations.

Parameters

[in]	x	Points on surface.
[in]	subset	Indices of points to use for fitting.

Returns: RMS error of the regression.

§ FitSurface() [4/6]

double mirtk::Polynomial::FitSurface	(	const PointSet &	x,
		const PointSet &	n,
		double	c = `1.0`
	)

Fits polynomial surface model to 3D point cloud

The dependent variable of the surface model is the algebraic distance of a point from the surface.

Parameters

[in]	x	Points on surface.
[in]	n	Surface normals at input points.
[in]	c	Offset along normal direction for points inside and outside the surface to be modelled.

Returns: RMS error of the regression.

§ FitSurface() [5/6]

double mirtk::Polynomial::FitSurface	(	const PointSet &	x,
		const PointSet &	n,
		const Array< int > &	subset,
		double	c = `1.0`
	)

Fits polynomial surface model to subset of 3D point cloud

The dependent variable of the surface model is the distance of a point from the surface.

Parameters

[in]	x	Points on surface.
[in]	n	Surface normals at input points.
[in]	subset	Indices of points to use for fitting.
[in]	c	Offset along normal direction for points inside and outside the surface to be modelled.

Returns: RMS error of the regression.

§ FitSurface() [6/6]

double mirtk::Polynomial::FitSurface	(	const PointSet &	x,
		const PointSet &	n,
		const OrderedSet< int > &	subset,
		double	c = `1.0`
	)

Fits polynomial surface model to subset of 3D point cloud

The dependent variable of the surface model is the distance of a point from the surface.

Parameters

[in]	x	Points on surface.
[in]	n	Surface normals at input points.
[in]	subset	Indices of points to use for fitting.
[in]	c	Offset along normal direction for points inside and outside the surface to be modelled.

Returns: RMS error of the regression.

§ Initialize()

int mirtk::Polynomial::Initialize	(	int	p,
		int	order = `0`
	)

Build complete polynomial regression model of given order

Parameters

[in]	p	Dimension of independent variable space.
[in]	order	Order of polynomial model, i.e., highest model term exponent. When non-positive, the current order of the model is used.

Returns: Number of model terms.

§ IsConstant()

bool mirtk::Polynomial::IsConstant ( int i ) const

inline

Whether i-th term is a constant term

Parameters

[in] i Index of model term.

Returns: Whether all exponents of i-th term are zero.

Definition at line 573 of file Polynomial.h.

§ SetConstantCoefficient()

void mirtk::Polynomial::SetConstantCoefficient	(	double	value,
		enum Status	status = `Passive`
	)

Sets coefficient(s) of constant model terms

Parameters

[in]	value	Coefficient value.
[in]	status	Status of constant model terms. Set to Passive by default, i.e., constant terms are fixed for model fitting.

§ Status() [1/2]

void mirtk::Polynomial::Status	(	int	i,
		enum Status	s
	)

inline

Set status of i-th coefficient

Parameters

[in]	i	Index of coefficient.
[in]	s	Status of coefficient.

Definition at line 601 of file Polynomial.h.

§ Status() [2/2]

enum Status mirtk::Polynomial::Status ( int i ) const

inline

Get status of i-th coefficient

Parameters

[in] i Index of coefficient.

Returns: Status of i-th coefficient.

Definition at line 608 of file Polynomial.h.

The documentation for this class was generated from the following file:

Polynomial.h

Public Member Functions

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

§ Polynomial() [1/2]

§ Polynomial() [2/2]

Member Function Documentation

§ Coefficient() [1/2]

§ Coefficient() [2/2]

§ Coefficients()

§ Evaluate() [1/7]

§ Evaluate() [2/7]

§ Evaluate() [3/7]

§ Evaluate() [4/7]

§ Evaluate() [5/7]

§ Evaluate() [6/7]

§ Evaluate() [7/7]

§ Evaluate1stOrderDerivative() [1/5]

§ Evaluate1stOrderDerivative() [2/5]

§ Evaluate1stOrderDerivative() [3/5]

§ Evaluate1stOrderDerivative() [4/5]

§ Evaluate1stOrderDerivative() [5/5]

§ Evaluate2ndOrderDerivative() [1/5]

§ Evaluate2ndOrderDerivative() [2/5]

§ Evaluate2ndOrderDerivative() [3/5]

§ Evaluate2ndOrderDerivative() [4/5]

§ Evaluate2ndOrderDerivative() [5/5]

§ EvaluateGaussianCurvature()

§ EvaluateGradient()

§ EvaluateHessian()

§ EvaluateMeanCurvature()

§ EvaluateTaubinDistance()

§ Exponent()

§ Fit() [1/5]

§ Fit() [2/5]

§ Fit() [3/5]

§ Fit() [4/5]

§ Fit() [5/5]

§ FitSurface() [1/6]

§ FitSurface() [2/6]

§ FitSurface() [3/6]

§ FitSurface() [4/6]

§ FitSurface() [5/6]

§ FitSurface() [6/6]

§ Initialize()

§ IsConstant()

§ SetConstantCoefficient()

§ Status() [1/2]

§ Status() [2/2]