Vector values Gauss distribution. More...

#include <gogausspdf.h>

Public Member Functions
	MultiGaussPDF (const input_vector &mean, const goMath::Matrix< scalar_type > &cov, scalar_type normFactor=scalar_type(1))

virtual scalar_type	operator() (const input_vector &input) const

void	reset (goSize_t N=1)
	Resets sample count, covariance matrix, etc., before using update() to learn a distribution from samples. More...

void	update (const input_vector &v)
	Update current mean and covariance. More...

void	updateFlush ()
	Ending learning from samples. More...

void	setCovariance (const goMath::Matrix< scalar_type > &cov)

const goMath::Matrix< scalar_type > &	getCovarianceInv () const

const goMath::Matrix< scalar_type > &	getCovariance () const

void	setMean (const input_vector &m)

const input_vector &	getMean () const

Public Member Functions inherited from goObjectBase
	goObjectBase ()
	Constructor.

virtual	~goObjectBase ()
	Destructor. More...

const char *	getClassName () const
	Returns the class name. More...

int	getClassID () const

virtual goSize_t	memoryUsage () const
	Returns the size of this object or some measure of its memory consumption. More...

void	setObjectName (const char *name)
	Set name string for an object. More...

void	setObjectName (const goString &name)
	Set name string for an object. More...

const goString &	getObjectName () const
	Get the object name. More...

virtual bool	writeObjectFile (FILE *) const
	Write object to a file. More...

virtual bool	readObjectFile (FILE *)
	Read object from a file. More...

void	connectObject (goObjectBase *object)
	Connects an object to this object. More...

void	disconnectObject (const goObjectBase *object)
	Disconnects an object from this object.

virtual bool	callObjectMethod (int methodID, goObjectMethodParameters *param=NULL)
	Call an object method by identifier. More...

virtual bool	queueObjectMethod (int methodID, goObjectMethodParameters *param=NULL, bool blocking=false)
	Enqueue a method call to an internal list of methods. More...

bool	callQueuedMethods ()
	Call all queued methods. More...

Additional Inherited Members
Protected Member Functions inherited from goObjectBase
void	setClassID (int id)
	Sets the class name.

void	printClassMessage (const char *msg)
	Sets the class name. More...

void	printClassMessage (goString &msg)
	Prints an informational message to the calling console. More...

void	sendObjectMessage (int messageID, void *data=NULL)
	Sends a message to all connected objects.

void	sendObjectMessage (goObjectBase object, int messageID, void data=NULL)
	Sends a message to a specific object.

virtual void	receiveObjectMessage (const goObjectMessage &message)
	Receive a message. More...

Detailed Description

template<class input_vector, class scalar_type>
class goMath::MultiGaussPDF< input_vector, scalar_type >

Vector values Gauss distribution.

You can use reset(), update(), and updateFlush() to learn a distribution from samples.

See the latex documentation in doc/gogausspdf for details.

Todo:: Normalisation factor.

Member Function Documentation

◆ reset()

template<class input_vector , class scalar_type >

void goMath::MultiGaussPDF< input_vector, scalar_type >::reset ( goSize_t N = 1 )

Resets sample count, covariance matrix, etc., before using update() to learn a distribution from samples.

Parameters

N	Vector length of samples. You may leave this open, the first update() call will set the sizes then.

◆ update()

template<class input_vector , class scalar_type >

void goMath::MultiGaussPDF< input_vector, scalar_type >::update ( const input_vector & input )

Update current mean and covariance.

You have to call reset() before starting to learn a distribution with this function. When you are done, you must call updateFlush() to calculate the inverse covariance and the like.

Parameters

input Sample vector.

◆ updateFlush()

template<class input_vector , class scalar_type >

void goMath::MultiGaussPDF< input_vector, scalar_type >::updateFlush ( )

Ending learning from samples.

You must call this function when you are done learning a distribution from samples with update(). Note that you can always call update() after updateFlush(), but in order to use the new, updated distribution, you must call updateFlush() before use.

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

gogausspdf.h
gogausspdf.cpp

Public Member Functions

Additional Inherited Members

Detailed Description

template<class input_vector, class scalar_type> class goMath::MultiGaussPDF< input_vector, scalar_type >

Member Function Documentation

◆ reset()

◆ update()

◆ updateFlush()

template<class input_vector, class scalar_type>
class goMath::MultiGaussPDF< input_vector, scalar_type >