Detailed Description

A gaussian distribution for 3D points.

Also a method for bayesian fusion is provided.

See also: CPointPDF

Definition at line 26 of file CPointPDFGaussian.h.

#include <mrpt/poses/CPointPDFGaussian.h>

Inheritance diagram for mrpt::poses::CPointPDFGaussian:

Public Types
enum	{ is_3D_val = 1 }

enum	{ is_PDF_val = 1 }

typedef CPoint3D	type_value
	The type of the state the PDF represents. More...

typedef CProbabilityDensityFunction< CPoint3D, STATE_LEN >	self_t

Public Member Functions
void *	operator new (size_t size)

void *	operator new[] (size_t size)

void	operator delete (void *ptr) throw ()

void	operator delete[] (void *ptr) throw ()

void	operator delete (void memory, void ptr) throw ()

void *	operator new (size_t size, const std::nothrow_t &) throw ()

void	operator delete (void *ptr, const std::nothrow_t &) throw ()

	CPointPDFGaussian ()
	Default constructor. More...

	CPointPDFGaussian (const CPoint3D &init_Mean)
	Constructor. More...

	CPointPDFGaussian (const CPoint3D &init_Mean, const mrpt::math::CMatrixDouble33 &init_Cov)
	Constructor. More...

void	getMean (CPoint3D &p) const MRPT_OVERRIDE
	Returns an estimate of the point, (the mean, or mathematical expectation of the PDF) More...

void	getCovarianceAndMean (mrpt::math::CMatrixDouble33 &cov, CPoint3D &mean_point) const MRPT_OVERRIDE
	Returns an estimate of the point covariance matrix (3x3 cov matrix) and the mean, both at once. More...

void	copyFrom (const CPointPDF &o) MRPT_OVERRIDE
	Copy operator, translating if necesary (for example, between particles and gaussian representations) More...

void	saveToTextFile (const std::string &file) const MRPT_OVERRIDE
	Save PDF's particles to a text file, containing the 2D pose in the first line, then the covariance matrix in next 3 lines. More...

void	changeCoordinatesReference (const CPose3D &newReferenceBase) MRPT_OVERRIDE
	this = p (+) this. More...

void	bayesianFusion (const CPointPDFGaussian &p1, const CPointPDFGaussian &p2)
	Bayesian fusion of two points gauss. More...

double	productIntegralWith (const CPointPDFGaussian &p) const
	Computes the "correspondence likelihood" of this PDF with another one: This is implemented as the integral from -inf to +inf of the product of both PDF. More...

double	productIntegralWith2D (const CPointPDFGaussian &p) const
	Computes the "correspondence likelihood" of this PDF with another one: This is implemented as the integral from -inf to +inf of the product of both PDF. More...

double	productIntegralNormalizedWith (const CPointPDFGaussian &p) const
	Computes the "correspondence likelihood" of this PDF with another one: This is implemented as the integral from -inf to +inf of the product of both PDF. More...

double	productIntegralNormalizedWith2D (const CPointPDFGaussian &p) const
	Computes the "correspondence likelihood" of this PDF with another one: This is implemented as the integral from -inf to +inf of the product of both PDF. More...

void	drawSingleSample (CPoint3D &outSample) const MRPT_OVERRIDE
	Draw a sample from the pdf. More...

void	bayesianFusion (const CPointPDF &p1, const CPointPDF &p2, const double &minMahalanobisDistToDrop=0) MRPT_OVERRIDE
	Bayesian fusion of two point distributions (product of two distributions->new distribution), then save the result in this object (WARNING: See implementing classes to see classes that can and cannot be mixtured!) More...

double	mahalanobisDistanceTo (const CPointPDFGaussian &other, bool only_2D=false) const
	Returns the Mahalanobis distance from this PDF to another PDF, that is, it's evaluation at (0,0,0) More...

template<class OPENGL_SETOFOBJECTSPTR >
void	getAs3DObject (OPENGL_SETOFOBJECTSPTR &out_obj) const
	Returns a 3D representation of this PDF (it doesn't clear the current contents of out_obj, but append new OpenGL objects to that list) More...

template<class OPENGL_SETOFOBJECTSPTR , class OPENGL_SETOFOBJECTS >
OPENGL_SETOFOBJECTSPTR	getAs3DObject () const
	Returns a 3D representation of this PDF. More...

virtual mxArray *	writeToMatlab () const
	Introduces a pure virtual method responsible for writing to a `mxArray` Matlab object, typically a MATLAB `struct` whose contents are documented in each derived class. More...

mrpt::utils::CObjectPtr	duplicateGetSmartPtr () const
	Returns a copy of the object, indepently of its class, as a smart pointer (the newly created object will exist as long as any copy of this smart pointer). More...

CObject *	clone () const
	Cloning interface for smart pointers. More...

virtual void	getMean (CPoint3D &mean_point) const=0
	Returns the mean, or mathematical expectation of the probability density distribution (PDF). More...

virtual void	getCovarianceAndMean (mrpt::math::CMatrixFixedNumeric< double, STATE_LEN, STATE_LEN > &cov, CPoint3D &mean_point) const=0
	Returns an estimate of the pose covariance matrix (STATE_LENxSTATE_LEN cov matrix) and the mean, both at once. More...

void	getCovarianceDynAndMean (mrpt::math::CMatrixDouble &cov, CPoint3D &mean_point) const
	Returns an estimate of the pose covariance matrix (STATE_LENxSTATE_LEN cov matrix) and the mean, both at once. More...

CPoint3D	getMeanVal () const
	Returns the mean, or mathematical expectation of the probability density distribution (PDF). More...

void	getCovariance (mrpt::math::CMatrixDouble &cov) const
	Returns the estimate of the covariance matrix (STATE_LEN x STATE_LEN covariance matrix) More...

void	getCovariance (mrpt::math::CMatrixFixedNumeric< double, STATE_LEN, STATE_LEN > &cov) const
	Returns the estimate of the covariance matrix (STATE_LEN x STATE_LEN covariance matrix) More...

mrpt::math::CMatrixFixedNumeric< double, STATE_LEN, STATE_LEN >	getCovariance () const
	Returns the estimate of the covariance matrix (STATE_LEN x STATE_LEN covariance matrix) More...

virtual bool	isInfType () const
	Returns whether the class instance holds the uncertainty in covariance or information form. More...

virtual void	getInformationMatrix (mrpt::math::CMatrixFixedNumeric< double, STATE_LEN, STATE_LEN > &inf) const
	Returns the information (inverse covariance) matrix (a STATE_LEN x STATE_LEN matrix) Unless reimplemented in derived classes, this method first reads the covariance, then invert it. More...

virtual void	drawSingleSample (CPoint3D &outPart) const=0
	Draws a single sample from the distribution. More...

virtual void	drawManySamples (size_t N, std::vector< mrpt::math::CVectorDouble > &outSamples) const
	Draws a number of samples from the distribution, and saves as a list of 1xSTATE_LEN vectors, where each row contains a (x,y,z,yaw,pitch,roll) datum. More...

double	getCovarianceEntropy () const
	Compute the entropy of the estimated covariance matrix. More...

Static Public Member Functions
static void *	operator new (size_t size, void *ptr)

static bool	is_3D ()

static bool	is_PDF ()

Public Attributes
CPoint3D	mean
	The mean value. More...

mrpt::math::CMatrixDouble33	cov
	The 3x3 covariance matrix. More...

Static Public Attributes
static const mrpt::utils::TRuntimeClassId	classCObject

static const size_t	state_length
	The length of the variable, for example, 3 for a 3D point, 6 for a 3D pose (x y z yaw pitch roll). More...

RTTI stuff
static const mrpt::utils::TRuntimeClassId	classCPointPDF

RTTI stuff
static const mrpt::utils::TRuntimeClassId	classCSerializable

Protected Member Functions
CSerializable virtual methods
void	writeToStream (mrpt::utils::CStream &out, int *getVersion) const
	Introduces a pure virtual method responsible for writing to a CStream. More...

void	readFromStream (mrpt::utils::CStream &in, int version)
	Introduces a pure virtual method responsible for loading from a CStream This can not be used directly be users, instead use "stream >> object;" for reading it from a stream or "stream >> object_ptr;" if the class is unknown apriori. More...

RTTI stuff
typedef CPointPDFGaussianPtr	Ptr

typedef CPointPDFGaussianPtr	ConstPtr

static mrpt::utils::CLASSINIT	_init_CPointPDFGaussian

static mrpt::utils::TRuntimeClassId	classCPointPDFGaussian

static const mrpt::utils::TRuntimeClassId *	classinfo

static const mrpt::utils::TRuntimeClassId *	_GetBaseClass ()

virtual const mrpt::utils::TRuntimeClassId *	GetRuntimeClass () const
	Returns information about the class of an object in runtime. More...

virtual mrpt::utils::CObject *	duplicate () const
	Returns a copy of the object, indepently of its class. More...

static mrpt::utils::CObject *	CreateObject ()

static CPointPDFGaussianPtr	Create ()

Member Typedef Documentation

◆ ConstPtr

typedef CPointPDFGaussianPtr mrpt::poses::CPointPDFGaussian::ConstPtr

Definition at line 29 of file CPointPDFGaussian.h.

◆ Ptr

typedef CPointPDFGaussianPtr mrpt::poses::CPointPDFGaussian::Ptr

A typedef for the associated smart pointer

Definition at line 29 of file CPointPDFGaussian.h.

◆ self_t

typedef CProbabilityDensityFunction<CPoint3D , STATE_LEN> mrpt::utils::CProbabilityDensityFunction< CPoint3D , STATE_LEN >::self_t

inherited

Definition at line 33 of file CProbabilityDensityFunction.h.

◆ type_value

typedef CPoint3D mrpt::utils::CProbabilityDensityFunction< CPoint3D , STATE_LEN >::type_value

inherited

The type of the state the PDF represents.

Definition at line 32 of file CProbabilityDensityFunction.h.

Member Enumeration Documentation

◆ anonymous enum

anonymous enum

inherited

Enumerator
is_3D_val

Definition at line 55 of file CPointPDF.h.

◆ anonymous enum

anonymous enum

inherited

Enumerator
is_PDF_val

Definition at line 57 of file CPointPDF.h.

Constructor & Destructor Documentation

◆ CPointPDFGaussian() [1/3]

CPointPDFGaussian::CPointPDFGaussian ( )

Default constructor.

Definition at line 32 of file CPointPDFGaussian.cpp.

◆ CPointPDFGaussian() [2/3]

CPointPDFGaussian::CPointPDFGaussian ( const CPoint3D & init_Mean )

Constructor.

Definition at line 50 of file CPointPDFGaussian.cpp.

References cov.

◆ CPointPDFGaussian() [3/3]

CPointPDFGaussian::CPointPDFGaussian	(	const CPoint3D &	init_Mean,
		const mrpt::math::CMatrixDouble33 &	init_Cov
	)

Constructor.

Definition at line 40 of file CPointPDFGaussian.cpp.

Member Function Documentation

◆ _GetBaseClass()

static const mrpt::utils::TRuntimeClassId* mrpt::poses::CPointPDFGaussian::_GetBaseClass ( )

staticprotected

◆ bayesianFusion() [1/2]

void CPointPDFGaussian::bayesianFusion	(	const CPointPDFGaussian &	p1,
		const CPointPDFGaussian &	p2
	)

Bayesian fusion of two points gauss.

distributions, then save the result in this object. The process is as follows:

(x1,S1): Mean and variance of the p1 distribution.
(x2,S2): Mean and variance of the p2 distribution.
(x,S): Mean and variance of the resulting distribution.

S = (S1^-1 + S2^-1)^-1; x = S * ( S1^-1*x1 + S2^-1*x2 );

Definition at line 160 of file CPointPDFGaussian.cpp.

References cov, inv(), mean, MRPT_END, MRPT_START, mrpt::poses::CPoseOrPoint< DERIVEDCLASS >::x(), and mrpt::poses::CPoseOrPoint< DERIVEDCLASS >::y().

Referenced by mrpt::poses::CPointPDFSOG::bayesianFusion(), and mrpt::maps::CLandmarksMap::fuseWith().

◆ bayesianFusion() [2/2]

void CPointPDFGaussian::bayesianFusion	(	const CPointPDF &	p1,
		const CPointPDF &	p2,
		const double &	minMahalanobisDistToDrop = `0`
	)

virtual

Bayesian fusion of two point distributions (product of two distributions->new distribution), then save the result in this object (WARNING: See implementing classes to see classes that can and cannot be mixtured!)

Parameters

p1	The first distribution to fuse
p2	The second distribution to fuse
minMahalanobisDistToDrop	If set to different of 0, the result of very separate Gaussian modes (that will result in negligible components) in SOGs will be dropped to reduce the number of modes in the output.

Implements mrpt::poses::CPointPDF.

Definition at line 287 of file CPointPDFGaussian.cpp.

References ASSERT_, CLASS_ID, mrpt::poses::CPointPDF::GetRuntimeClass(), MRPT_END, MRPT_START, MRPT_UNUSED_PARAM, and THROW_EXCEPTION.

◆ changeCoordinatesReference()

void CPointPDFGaussian::changeCoordinatesReference ( const CPose3D & newReferenceBase )

virtual

this = p (+) this.

This can be used to convert a PDF from local coordinates to global, providing the point (newReferenceBase) from which "to project" the current pdf. Result PDF substituted the currently stored one in the object. Both the mean value and the covariance matrix are updated correctly.

Implements mrpt::utils::CProbabilityDensityFunction< CPoint3D, 3 >.

Definition at line 146 of file CPointPDFGaussian.cpp.

References cov, mrpt::poses::CPose3D::getRotationMatrix(), and mean.

◆ clone()

CObject* mrpt::utils::CObject::clone ( ) const

inlineinherited

Cloning interface for smart pointers.

Definition at line 143 of file CObject.h.

◆ copyFrom()

void CPointPDFGaussian::copyFrom ( const CPointPDF & o )

virtual

Copy operator, translating if necesary (for example, between particles and gaussian representations)

Implements mrpt::poses::CPointPDF.

Definition at line 113 of file CPointPDFGaussian.cpp.

References cov, mrpt::utils::CProbabilityDensityFunction< TDATA, STATE_LEN >::getCovarianceAndMean(), and mean.

◆ Create()

static CPointPDFGaussianPtr mrpt::poses::CPointPDFGaussian::Create ( )

static

◆ CreateObject()

static mrpt::utils::CObject* mrpt::poses::CPointPDFGaussian::CreateObject ( )

static

◆ drawManySamples()

virtual void mrpt::utils::CProbabilityDensityFunction< CPoint3D , STATE_LEN >::drawManySamples	(	size_t	N,
		std::vector< mrpt::math::CVectorDouble > &	outSamples
	)		const

inlinevirtualinherited

Draws a number of samples from the distribution, and saves as a list of 1xSTATE_LEN vectors, where each row contains a (x,y,z,yaw,pitch,roll) datum.

This base method just call N times to drawSingleSample, but derived classes should implemented optimized method for each particular PDF.

Definition at line 125 of file CProbabilityDensityFunction.h.

◆ drawSingleSample() [1/2]

void CPointPDFGaussian::drawSingleSample ( CPoint3D & outSample ) const

Draw a sample from the pdf.

Definition at line 269 of file CPointPDFGaussian.cpp.

References ASSERT_, cov, mrpt::random::CRandomGenerator::drawGaussianMultivariate(), mean, MRPT_END, MRPT_START, mrpt::random::randomGenerator, mrpt::poses::CPoseOrPoint< DERIVEDCLASS >::x(), and mrpt::poses::CPoseOrPoint< DERIVEDCLASS >::y().

◆ drawSingleSample() [2/2]

virtual void mrpt::utils::CProbabilityDensityFunction< CPoint3D , STATE_LEN >::drawSingleSample ( CPoint3D & outPart ) const

pure virtualinherited

Draws a single sample from the distribution.

◆ duplicate()

virtual mrpt::utils::CObject* mrpt::poses::CPointPDFGaussian::duplicate ( ) const

virtual

Returns a copy of the object, indepently of its class.

Implements mrpt::utils::CObject.

◆ duplicateGetSmartPtr()

mrpt::utils::CObjectPtr mrpt::utils::CObject::duplicateGetSmartPtr ( ) const

inlineinherited

Returns a copy of the object, indepently of its class, as a smart pointer (the newly created object will exist as long as any copy of this smart pointer).

Definition at line 140 of file CObject.h.

Referenced by mrpt::obs::CRawlog::addActions(), mrpt::slam::CIncrementalMapPartitioner::addMapFrame(), and mrpt::obs::CRawlog::addObservations().

◆ getAs3DObject() [1/2]

template<class OPENGL_SETOFOBJECTSPTR >

void mrpt::poses::CPointPDF::getAs3DObject ( OPENGL_SETOFOBJECTSPTR & out_obj ) const

inlineinherited

Returns a 3D representation of this PDF (it doesn't clear the current contents of out_obj, but append new OpenGL objects to that list)

Note: Needs the mrpt-opengl library, and using mrpt::opengl::CSetOfObjectsPtr as template argument.; By default, ellipsoids for the confidence intervals of "q=3" are drawn; for more mathematical details, see CGeneralizedEllipsoidTemplate::setQuantiles()

Definition at line 65 of file CPointPDF.h.

References mrpt::opengl::posePDF2opengl().

◆ getAs3DObject() [2/2]

template<class OPENGL_SETOFOBJECTSPTR , class OPENGL_SETOFOBJECTS >

OPENGL_SETOFOBJECTSPTR mrpt::poses::CPointPDF::getAs3DObject ( ) const

inlineinherited

Returns a 3D representation of this PDF.

Note: Needs the mrpt-opengl library, and using mrpt::opengl::CSetOfObjectsPtr as template argument.

Definition at line 74 of file CPointPDF.h.

References mrpt::opengl::posePDF2opengl().

◆ getCovariance() [1/3]

void mrpt::utils::CProbabilityDensityFunction< CPoint3D , STATE_LEN >::getCovariance ( mrpt::math::CMatrixDouble & cov ) const

inlineinherited

Returns the estimate of the covariance matrix (STATE_LEN x STATE_LEN covariance matrix)

See also: getMean, getCovarianceAndMean, getInformationMatrix

Definition at line 68 of file CProbabilityDensityFunction.h.

◆ getCovariance() [2/3]

void mrpt::utils::CProbabilityDensityFunction< CPoint3D , STATE_LEN >::getCovariance ( mrpt::math::CMatrixFixedNumeric< double, STATE_LEN, STATE_LEN > & cov ) const

inlineinherited

Returns the estimate of the covariance matrix (STATE_LEN x STATE_LEN covariance matrix)

See also: getMean, getCovarianceAndMean, getInformationMatrix

Definition at line 77 of file CProbabilityDensityFunction.h.

◆ getCovariance() [3/3]

mrpt::math::CMatrixFixedNumeric<double,STATE_LEN,STATE_LEN> mrpt::utils::CProbabilityDensityFunction< CPoint3D , STATE_LEN >::getCovariance ( ) const

inlineinherited

Returns the estimate of the covariance matrix (STATE_LEN x STATE_LEN covariance matrix)

See also: getMean, getInformationMatrix

Definition at line 86 of file CProbabilityDensityFunction.h.

◆ getCovarianceAndMean() [1/2]

virtual void mrpt::utils::CProbabilityDensityFunction< CPoint3D , STATE_LEN >::getCovarianceAndMean	(	mrpt::math::CMatrixFixedNumeric< double, STATE_LEN, STATE_LEN > &	cov,
		CPoint3D &	mean_point
	)		const

pure virtualinherited

Returns an estimate of the pose covariance matrix (STATE_LENxSTATE_LEN cov matrix) and the mean, both at once.

See also: getMean, getInformationMatrix

◆ getCovarianceAndMean() [2/2]

void CPointPDFGaussian::getCovarianceAndMean	(	mrpt::math::CMatrixDouble33 &	cov,
		CPoint3D &	mean_point
	)		const

Returns an estimate of the point covariance matrix (3x3 cov matrix) and the mean, both at once.

See also: getMean

Definition at line 69 of file CPointPDFGaussian.cpp.

References cov, and mean.

◆ getCovarianceDynAndMean()

void mrpt::utils::CProbabilityDensityFunction< CPoint3D , STATE_LEN >::getCovarianceDynAndMean	(	mrpt::math::CMatrixDouble &	cov,
		CPoint3D &	mean_point
	)		const

inlineinherited

Returns an estimate of the pose covariance matrix (STATE_LENxSTATE_LEN cov matrix) and the mean, both at once.

See also: getMean, getInformationMatrix

Definition at line 48 of file CProbabilityDensityFunction.h.

◆ getCovarianceEntropy()

double mrpt::utils::CProbabilityDensityFunction< CPoint3D , STATE_LEN >::getCovarianceEntropy ( ) const

inlineinherited

Compute the entropy of the estimated covariance matrix.

See also: http://en.wikipedia.org/wiki/Multivariate_normal_distribution#Entropy

Definition at line 144 of file CProbabilityDensityFunction.h.

◆ getInformationMatrix()

virtual void mrpt::utils::CProbabilityDensityFunction< CPoint3D , STATE_LEN >::getInformationMatrix ( mrpt::math::CMatrixFixedNumeric< double, STATE_LEN, STATE_LEN > & inf ) const

inlinevirtualinherited

Returns the information (inverse covariance) matrix (a STATE_LEN x STATE_LEN matrix) Unless reimplemented in derived classes, this method first reads the covariance, then invert it.

See also: getMean, getCovarianceAndMean

Definition at line 106 of file CProbabilityDensityFunction.h.

◆ getMean() [1/2]

virtual void mrpt::utils::CProbabilityDensityFunction< CPoint3D , STATE_LEN >::getMean ( CPoint3D & mean_point ) const

pure virtualinherited

Returns the mean, or mathematical expectation of the probability density distribution (PDF).

See also: getCovarianceAndMean, getInformationMatrix

◆ getMean() [2/2]

void CPointPDFGaussian::getMean ( CPoint3D & p ) const

Returns an estimate of the point, (the mean, or mathematical expectation of the PDF)

Definition at line 61 of file CPointPDFGaussian.cpp.

References mean.

◆ getMeanVal()

CPoint3D mrpt::utils::CProbabilityDensityFunction< CPoint3D , STATE_LEN >::getMeanVal ( ) const

inlineinherited

Returns the mean, or mathematical expectation of the probability density distribution (PDF).

See also: getCovariance, getInformationMatrix

Definition at line 58 of file CProbabilityDensityFunction.h.

◆ GetRuntimeClass()

virtual const mrpt::utils::TRuntimeClassId* mrpt::poses::CPointPDFGaussian::GetRuntimeClass ( ) const

virtual

Returns information about the class of an object in runtime.

Reimplemented from mrpt::poses::CPointPDF.

◆ is_3D()

static bool mrpt::poses::CPointPDF::is_3D ( )

inlinestaticinherited

Definition at line 56 of file CPointPDF.h.

◆ is_PDF()

static bool mrpt::poses::CPointPDF::is_PDF ( )

inlinestaticinherited

Definition at line 58 of file CPointPDF.h.

◆ isInfType()

virtual bool mrpt::utils::CProbabilityDensityFunction< CPoint3D , STATE_LEN >::isInfType ( ) const

inlinevirtualinherited

Returns whether the class instance holds the uncertainty in covariance or information form.

Note: By default this is going to be covariance form. *Inf classes (e.g. CPosePDFGaussianInf) store it in information form.

See also: mrpt::traits::is_inf_type

Definition at line 100 of file CProbabilityDensityFunction.h.

◆ mahalanobisDistanceTo()

double CPointPDFGaussian::mahalanobisDistanceTo	(	const CPointPDFGaussian &	other,
		bool	only_2D = `false`
	)		const

Returns the Mahalanobis distance from this PDF to another PDF, that is, it's evaluation at (0,0,0)

Definition at line 304 of file CPointPDFGaussian.cpp.

References cov, mean, mrpt::poses::CPoseOrPoint< DERIVEDCLASS >::x(), and mrpt::poses::CPoseOrPoint< DERIVEDCLASS >::y().

Referenced by productIntegralNormalizedWith(), and productIntegralNormalizedWith2D().

◆ operator delete() [1/3]

void mrpt::poses::CPointPDFGaussian::operator delete	(	void *	ptr	)
throw	(
	)

inline

Definition at line 29 of file CPointPDFGaussian.h.

◆ operator delete() [2/3]

void mrpt::poses::CPointPDFGaussian::operator delete	(	void *	memory,
		void *	ptr
	)
throw	(
	)

inline

Definition at line 29 of file CPointPDFGaussian.h.

◆ operator delete() [3/3]

void mrpt::poses::CPointPDFGaussian::operator delete	(	void *	ptr,
		const std::nothrow_t &
	)
throw	(
	)

inline

Definition at line 29 of file CPointPDFGaussian.h.

◆ operator delete[]()

void mrpt::poses::CPointPDFGaussian::operator delete[]	(	void *	ptr	)
throw	(
	)

inline

Definition at line 29 of file CPointPDFGaussian.h.

◆ operator new() [1/3]

void* mrpt::poses::CPointPDFGaussian::operator new ( size_t size )

inline

Definition at line 29 of file CPointPDFGaussian.h.

◆ operator new() [2/3]

static void* mrpt::poses::CPointPDFGaussian::operator new	(	size_t	size,
		void *	ptr
	)

inlinestatic

Definition at line 29 of file CPointPDFGaussian.h.

◆ operator new() [3/3]

void* mrpt::poses::CPointPDFGaussian::operator new	(	size_t	size,
		const std::nothrow_t &
	)
throw	(
	)

inline

Definition at line 29 of file CPointPDFGaussian.h.

◆ operator new[]()

void* mrpt::poses::CPointPDFGaussian::operator new[] ( size_t size )

inline

Definition at line 29 of file CPointPDFGaussian.h.

◆ productIntegralNormalizedWith()

double CPointPDFGaussian::productIntegralNormalizedWith ( const CPointPDFGaussian & p ) const

Computes the "correspondence likelihood" of this PDF with another one: This is implemented as the integral from -inf to +inf of the product of both PDF.

The resulting number is in the range [0,1] Note that the resulting value is in fact

$exp( -\frac{1}{2} D^2 )$

, with $ D^2 $ being the square Mahalanobis distance between the two pdfs.

See also: productIntegralWith

Exceptions

std::exception On errors like covariance matrix with null determinant, etc...

Definition at line 253 of file CPointPDFGaussian.cpp.

References mahalanobisDistanceTo(), and mrpt::math::square().

◆ productIntegralNormalizedWith2D()

double CPointPDFGaussian::productIntegralNormalizedWith2D ( const CPointPDFGaussian & p ) const

Computes the "correspondence likelihood" of this PDF with another one: This is implemented as the integral from -inf to +inf of the product of both PDF.

The resulting number is in the range [0,1]. This versions ignores the "z" coordinate.

Note that the resulting value is in fact

$exp( -\frac{1}{2} D^2 )$

, with $ D^2 $ being the square Mahalanobis distance between the two pdfs.

See also: productIntegralWith

Exceptions

std::exception On errors like covariance matrix with null determinant, etc...

Definition at line 261 of file CPointPDFGaussian.cpp.

References mahalanobisDistanceTo(), and mrpt::math::square().

Referenced by mrpt::maps::CLandmarksMap::computeLikelihood_RSLC_2007().

◆ productIntegralWith()

double CPointPDFGaussian::productIntegralWith ( const CPointPDFGaussian & p ) const

Computes the "correspondence likelihood" of this PDF with another one: This is implemented as the integral from -inf to +inf of the product of both PDF.

The resulting number is >=0.

See also: productIntegralNormalizedWith

Exceptions

std::exception On errors like covariance matrix with null determinant, etc...

Definition at line 194 of file CPointPDFGaussian.cpp.

References cov, M_2PI, mean, MRPT_END, MRPT_START, mrpt::utils::CProbabilityDensityFunction< CPoint3D, 3 >::state_length, mrpt::math::UNINITIALIZED_MATRIX, mrpt::poses::CPoseOrPoint< DERIVEDCLASS >::x(), and mrpt::poses::CPoseOrPoint< DERIVEDCLASS >::y().

◆ productIntegralWith2D()

double CPointPDFGaussian::productIntegralWith2D ( const CPointPDFGaussian & p ) const

Computes the "correspondence likelihood" of this PDF with another one: This is implemented as the integral from -inf to +inf of the product of both PDF.

The resulting number is >=0. NOTE: This version ignores the "z" coordinates!!

See also: productIntegralNormalizedWith

Exceptions

std::exception On errors like covariance matrix with null determinant, etc...

Definition at line 223 of file CPointPDFGaussian.cpp.

References cov, M_2PI, mean, MRPT_END, MRPT_START, mrpt::utils::CProbabilityDensityFunction< CPoint3D, 3 >::state_length, mrpt::math::UNINITIALIZED_MATRIX, mrpt::poses::CPoseOrPoint< DERIVEDCLASS >::x(), and mrpt::poses::CPoseOrPoint< DERIVEDCLASS >::y().

◆ readFromStream()

void CPointPDFGaussian::readFromStream	(	mrpt::utils::CStream &	in,
		int	version
	)

protectedvirtual

Introduces a pure virtual method responsible for loading from a CStream This can not be used directly be users, instead use "stream >> object;" for reading it from a stream or "stream >> object_ptr;" if the class is unknown apriori.

Parameters

in	The input binary stream where the object data must read from.
version	The version of the object stored in the stream: use this version number in your code to know how to read the incoming data.

Exceptions

std::exception On any error, see CStream::ReadBuffer

See also: CStream

Implements mrpt::utils::CSerializable.

Definition at line 91 of file CPointPDFGaussian.cpp.

References cov, mean, MRPT_THROW_UNKNOWN_SERIALIZATION_VERSION, and version.

◆ saveToTextFile()

void CPointPDFGaussian::saveToTextFile ( const std::string & file ) const

virtual

Save PDF's particles to a text file, containing the 2D pose in the first line, then the covariance matrix in next 3 lines.

Implements mrpt::utils::CProbabilityDensityFunction< CPoint3D, 3 >.

Definition at line 124 of file CPointPDFGaussian.cpp.

References cov, mrpt::system::os::fclose(), mrpt::system::os::fopen(), mrpt::system::os::fprintf(), mean, MRPT_END, MRPT_START, mrpt::poses::CPoseOrPoint< DERIVEDCLASS >::x(), and mrpt::poses::CPoseOrPoint< DERIVEDCLASS >::y().

◆ writeToMatlab()

virtual mxArray* mrpt::utils::CSerializable::writeToMatlab ( ) const

inlinevirtualinherited

Introduces a pure virtual method responsible for writing to a mxArray Matlab object, typically a MATLAB struct whose contents are documented in each derived class.

Returns: A new mxArray (caller is responsible of memory freeing) or NULL is class does not support conversion to MATLAB.

Definition at line 79 of file CSerializable.h.

◆ writeToStream()

void CPointPDFGaussian::writeToStream	(	mrpt::utils::CStream &	out,
		int *	getVersion
	)		const

protectedvirtual

Introduces a pure virtual method responsible for writing to a CStream.

This can not be used directly be users, instead use "stream << object;" for writing it to a stream.

Parameters

out	The output binary stream where object must be dumped.
getVersion	If NULL, the object must be dumped. If not, only the version of the object dump must be returned in this pointer. This enables the versioning of objects dumping and backward compatibility with previously stored data.

Exceptions

std::exception On any error, see CStream::WriteBuffer

See also: CStream

Implements mrpt::utils::CSerializable.

Definition at line 78 of file CPointPDFGaussian.cpp.

References cov, mean, and version.

Member Data Documentation

◆ _init_CPointPDFGaussian

mrpt::utils::CLASSINIT mrpt::poses::CPointPDFGaussian::_init_CPointPDFGaussian

staticprotected

Definition at line 29 of file CPointPDFGaussian.h.

◆ classCObject

const mrpt::utils::TRuntimeClassId mrpt::utils::CObject::classCObject

staticinherited

Definition at line 128 of file CObject.h.

◆ classCPointPDF

const mrpt::utils::TRuntimeClassId mrpt::poses::CPointPDF::classCPointPDF

staticinherited

Definition at line 40 of file CPointPDF.h.

◆ classCPointPDFGaussian

mrpt::utils::TRuntimeClassId mrpt::poses::CPointPDFGaussian::classCPointPDFGaussian

static

Definition at line 29 of file CPointPDFGaussian.h.

◆ classCSerializable

const mrpt::utils::TRuntimeClassId mrpt::utils::CSerializable::classCSerializable

staticinherited

Definition at line 42 of file CSerializable.h.

◆ classinfo

const mrpt::utils::TRuntimeClassId* mrpt::poses::CPointPDFGaussian::classinfo

static

Definition at line 29 of file CPointPDFGaussian.h.

◆ cov

mrpt::math::CMatrixDouble33 mrpt::poses::CPointPDFGaussian::cov

The 3x3 covariance matrix.

Definition at line 45 of file CPointPDFGaussian.h.

Referenced by bayesianFusion(), mrpt::poses::CPointPDFSOG::bayesianFusion(), changeCoordinatesReference(), mrpt::maps::CLandmarksMap::computeLikelihood_SIFT_LandmarkMap(), mrpt::maps::CLandmarksMap::computeMatchingWith3DLandmarks(), copyFrom(), CPointPDFGaussian(), drawSingleSample(), mrpt::maps::CBeacon::generateRingSOG(), mrpt::slam::CRangeBearingKFSLAM::getAs3DObject(), mrpt::maps::CLandmarksMap::getAs3DObject(), getCovarianceAndMean(), mrpt::maps::CLandmark::getPose(), mrpt::maps::CBeaconMap::internal_computeObservationLikelihood(), mrpt::maps::CBeaconMap::internal_insertObservation(), mrpt::maps::CLandmarksMap::loadSiftFeaturesFromImageObservation(), mahalanobisDistanceTo(), mrpt::maps::CMultiMetricMapPDF::prediction_and_update_pfOptimalProposal(), productIntegralWith(), productIntegralWith2D(), readFromStream(), saveToTextFile(), mrpt::maps::CLandmark::setPose(), and writeToStream().

◆ mean

CPoint3D mrpt::poses::CPointPDFGaussian::mean

The mean value.

Definition at line 44 of file CPointPDFGaussian.h.

Referenced by bayesianFusion(), mrpt::poses::CPointPDFSOG::bayesianFusion(), changeCoordinatesReference(), mrpt::maps::CLandmarksMap::computeMatchingWith3DLandmarks(), copyFrom(), drawSingleSample(), mrpt::maps::CBeacon::generateRingSOG(), mrpt::slam::CRangeBearingKFSLAM::getAs3DObject(), mrpt::maps::CLandmarksMap::getAs3DObject(), getCovarianceAndMean(), getMean(), mrpt::maps::CLandmark::getPose(), mrpt::maps::CBeaconMap::internal_computeObservationLikelihood(), mrpt::maps::CLandmarksMap::internal_computeObservationLikelihood(), mrpt::maps::CBeaconMap::internal_insertObservation(), mrpt::maps::CLandmarksMap::loadSiftFeaturesFromImageObservation(), mahalanobisDistanceTo(), mrpt::maps::CMultiMetricMapPDF::prediction_and_update_pfOptimalProposal(), productIntegralWith(), productIntegralWith2D(), readFromStream(), saveToTextFile(), mrpt::maps::CLandmark::setPose(), mrpt::maps::CLandmarksMap::simulateBeaconReadings(), mrpt::maps::CLandmarksMap::simulateRangeBearingReadings(), and writeToStream().

◆ state_length

const size_t mrpt::utils::CProbabilityDensityFunction< CPoint3D , STATE_LEN >::state_length

staticinherited

The length of the variable, for example, 3 for a 3D point, 6 for a 3D pose (x y z yaw pitch roll).

Definition at line 31 of file CProbabilityDensityFunction.h.

Referenced by productIntegralWith(), and productIntegralWith2D().

Detailed Description

Public Types

Public Member Functions

Static Public Member Functions

Public Attributes

Static Public Attributes

Protected Member Functions

RTTI stuff

Member Typedef Documentation

◆ ConstPtr

◆ Ptr

◆ self_t

◆ type_value

Member Enumeration Documentation

◆ anonymous enum

◆ anonymous enum

Constructor & Destructor Documentation

◆ CPointPDFGaussian() [1/3]

◆ CPointPDFGaussian() [2/3]

◆ CPointPDFGaussian() [3/3]

Member Function Documentation

◆ _GetBaseClass()

◆ bayesianFusion() [1/2]

◆ bayesianFusion() [2/2]

◆ changeCoordinatesReference()

◆ clone()

◆ copyFrom()

◆ Create()

◆ CreateObject()

◆ drawManySamples()

◆ drawSingleSample() [1/2]

◆ drawSingleSample() [2/2]

◆ duplicate()

◆ duplicateGetSmartPtr()

◆ getAs3DObject() [1/2]

◆ getAs3DObject() [2/2]

◆ getCovariance() [1/3]

◆ getCovariance() [2/3]

◆ getCovariance() [3/3]

◆ getCovarianceAndMean() [1/2]

◆ getCovarianceAndMean() [2/2]

◆ getCovarianceDynAndMean()

◆ getCovarianceEntropy()

◆ getInformationMatrix()

◆ getMean() [1/2]

◆ getMean() [2/2]

◆ getMeanVal()

◆ GetRuntimeClass()

◆ is_3D()

◆ is_PDF()

◆ isInfType()

◆ mahalanobisDistanceTo()

◆ operator delete() [1/3]

◆ operator delete() [2/3]

◆ operator delete() [3/3]

◆ operator delete[]()

◆ operator new() [1/3]

◆ operator new() [2/3]

◆ operator new() [3/3]

◆ operator new[]()

◆ productIntegralNormalizedWith()

◆ productIntegralNormalizedWith2D()

◆ productIntegralWith()

◆ productIntegralWith2D()

◆ readFromStream()

◆ saveToTextFile()

◆ writeToMatlab()

◆ writeToStream()

Member Data Documentation

◆ _init_CPointPDFGaussian

◆ classCObject

◆ classCPointPDF

◆ classCPointPDFGaussian

◆ classCSerializable

◆ classinfo

◆ cov

◆ mean

◆ state_length