#include <TransformationApproximationError.h>

Inheritance diagram for mirtk::TransformationApproximationError:

Collaboration diagram for mirtk::TransformationApproximationError:

Public Member Functions
void	CenterPoints ()
	Subtract centroid from each point set.

virtual double	Get (int i) const

virtual void	Get (double *x) const

virtual void	Gradient (double dx, double step=.0, bool sgn_chg=NULL)

virtual double	GradientNorm (const double *dx) const

virtual int	NumberOfDOFs () const

virtual void	Put (const double *x)

virtual double	Step (double *dx)

	TransformationApproximationError (class Transformation , const double , const double , const double , const double , const double , const double , const double , int)
	Constructor.

virtual void	Update (bool gradient=true)

virtual double	Value ()
	Evaluate objective function value.

virtual	~TransformationApproximationError ()
	Destructor.

Public Member Functions inherited from mirtk::ObjectiveFunction
virtual void	AddConstraintGradient (double dx, double step=.0, bool sgn_chg=nullptr)

virtual void	DataFidelityGradient (double dx, double step=.0, bool sgn_chg=nullptr)

virtual double	Evaluate (double dx=NULL, double step=.0, bool sgn_chg=NULL)

virtual void	GradientStep (const double *dx, double &min, double &max) const

virtual bool	Upgrade ()

virtual	~ObjectiveFunction ()=0
	Destructor.

Public Member Functions inherited from mirtk::Observable
void	AddObserver (Observer &)
	Add observer.

void	Broadcast (Event, const void *=NULL)
	Broadcast event to observers.

void	ClearObservers ()
	Delete all observers.

void	DeleteObserver (Observer &)
	Delete observer.

void	NotifyObservers (Event, const void *=NULL)
	Notify all observers about given event if this object has changed.

int	NumberOfObservers () const
	Number of current observers.

virtual	~Observable ()
	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::ObjectiveFunction
	mirtkAttributeMacro (double, StepLength)
	Default step length used for gradient approximation.

Protected Member Functions inherited from mirtk::Observable
	Observable ()
	Default constructor.

	Observable (const Observable &)
	Copy constructor.

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

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

Mean-squared-error of transformation approximation

This objective function is minimized by Transformation::ApproximateDOFs to find the transformation parameters which minimize the mean squared error of the approximation.

Definition at line 40 of file TransformationApproximationError.h.

Member Function Documentation

§ Get() [1/2]

virtual double mirtk::TransformationApproximationError::Get ( int i ) const

virtual

Get function parameter value

Parameters

[in] i Function parameter (DoF) index.

Returns: Value of specified function parameter (DoF).

Implements mirtk::ObjectiveFunction.

§ Get() [2/2]

virtual void mirtk::TransformationApproximationError::Get ( double * x ) const

virtual

Get function parameter values

This function can be used to store a backup of the current funtion parameter values before an update such that these can be restored using the Put member function if the update did not result in the desired change of the overall objective function value.

Parameters

[in] x Function parameter (DoF) values.

Implements mirtk::ObjectiveFunction.

§ Gradient()

virtual void mirtk::TransformationApproximationError::Gradient	(	double *	dx,
		double	step = `.0`,
		bool *	sgn_chg = `NULL`
	)

virtual

Evaluate gradient of objective function w.r.t its DoFs

Parameters

[in]	step	Step length for finite differences.
[out]	dx	Gradient of objective function.
[out]	sgn_chg	Whether function parameter value is allowed to change sign when stepping along the computed gradient.

Implements mirtk::ObjectiveFunction.

§ GradientNorm()

virtual double mirtk::TransformationApproximationError::GradientNorm ( const double * dx ) const

virtual

Compute norm of gradient of objective function

This norm is used to define a unit for the step length used by gradient descent methods. It is, for example, the maximum absolute value norm for linear transformations and the maximum control point displacement for FFDs. The computation of the norm may be done after conjugating the gradient vector obtained using the Gradient member function.

Parameters

[in] dx Gradient of objective function.

Implements mirtk::ObjectiveFunction.

§ NumberOfDOFs()

virtual int mirtk::TransformationApproximationError::NumberOfDOFs ( ) const

virtual

Get number of DoFs

Returns: Number of free function parameters.

Implements mirtk::ObjectiveFunction.

§ Put()

virtual void mirtk::TransformationApproximationError::Put ( const double * x )

virtual

Set function parameter values

This is function can be used to set the parameters of the objective function to particular values. In particular, it can be used to restore the function parameters after a failed incremental update which did not result in the desired improvement.

Parameters

[in] x Function parameter (DoF) values.

Implements mirtk::ObjectiveFunction.

§ Step()

virtual double mirtk::TransformationApproximationError::Step ( double * dx )

virtual

Add change (i.e., scaled gradient) to each parameter value

This function updates each DoF of the objective function given a vector of corresponding changes, i.e., the computed gradient of the objective function w.r.t. these parameters or a desired change computed otherwise.

Parameters

[in] dx Change of each function parameter (DoF) as computed by the Gradient member function and scaled by a chosen step length.

Returns: Maximum change of function parameter.

Implements mirtk::ObjectiveFunction.

§ Update()

virtual void mirtk::TransformationApproximationError::Update ( bool gradient = true )

virtual

Update internal state after change of parameters

Parameters

[in] gradient Update also internal state required for evaluation of gradient of objective function.

Reimplemented from mirtk::ObjectiveFunction.

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

TransformationApproximationError.h

Public Member Functions

Additional Inherited Members

Detailed Description

Member Function Documentation

§ Get() [1/2]

§ Get() [2/2]

§ Gradient()

§ GradientNorm()

§ NumberOfDOFs()

§ Put()

§ Step()

§ Update()