Detailed Description

A gaussian distribution for 3D points.

Also a method for bayesian fusion is provided.

See also: CPointPDF

Definition at line 22 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 }

using	type_value = CPoint3D
	The type of the state the PDF represents. More...

using	self_t = CProbabilityDensityFunction< CPoint3D, STATE_LEN >

using	cov_mat_t = mrpt::math::CMatrixFixed< double, STATE_LEN, STATE_LEN >
	Covariance matrix type. More...

using	inf_mat_t = cov_mat_t
	Information matrix type. More...

Public Member Functions
	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 override

std::tuple< cov_mat_t, type_value >	getCovarianceAndMean () const override
	Returns an estimate of the pose covariance matrix (STATE_LENxSTATE_LEN cov matrix) and the mean, both at once. More...

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

bool	saveToTextFile (const std::string &file) const 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) 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 override
	Draw a sample from the pdf. More...

void	bayesianFusion (const CPointPDF &p1, const CPointPDF &p2, const double minMahalanobisDistToDrop=0) 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...

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

virtual void	getCovarianceAndMean (cov_mat_t &c, CPoint3D &mean) const final

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

type_value	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 (cov_mat_t &cov) const
	Returns the estimate of the covariance matrix (STATE_LEN x STATE_LEN covariance matrix) More...

cov_mat_t	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 (inf_mat_t &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...

RTTI classes and functions for polymorphic hierarchies
mrpt::rtti::CObject::Ptr	duplicateGetSmartPtr () const
	Makes a deep copy of the object and returns a smart pointer to it. More...

Static Public Member Functions
static constexpr bool	is_3D ()

static constexpr bool	is_PDF ()

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

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

Static Public Attributes
static constexpr 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...

Protected Member Functions
CSerializable virtual methods
uint8_t	serializeGetVersion () const override
	Must return the current versioning number of the object. More...

void	serializeTo (mrpt::serialization::CArchive &out) const override
	Pure virtual method for writing (serializing) to an abstract archive. More...

void	serializeFrom (mrpt::serialization::CArchive &in, uint8_t serial_version) override
	Pure virtual method for reading (deserializing) from an abstract archive. More...

CSerializable virtual methods
virtual void	serializeTo (CSchemeArchiveBase &out) const
	Virtual method for writing (serializing) to an abstract schema based archive. More...

virtual void	serializeFrom (CSchemeArchiveBase &in)
	Virtual method for reading (deserializing) from an abstract schema based archive. More...

RTTI stuff
using	Ptr = std::shared_ptr< mrpt::poses ::CPointPDFGaussian >

using	ConstPtr = std::shared_ptr< const mrpt::poses ::CPointPDFGaussian >

using	UniquePtr = std::unique_ptr< mrpt::poses ::CPointPDFGaussian >

using	ConstUniquePtr = std::unique_ptr< const mrpt::poses ::CPointPDFGaussian >

static const mrpt::rtti::TRuntimeClassId	runtimeClassId

static constexpr const char *	className = "mrpt::poses" "::" "CPointPDFGaussian"

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

static constexpr auto	getClassName ()

static const mrpt::rtti::TRuntimeClassId &	GetRuntimeClassIdStatic ()

static std::shared_ptr< CObject >	CreateObject ()

template<typename... Args>
static Ptr	Create (Args &&... args)

template<typename Alloc , typename... Args>
static Ptr	CreateAlloc (const Alloc &alloc, Args &&... args)

template<typename... Args>
static UniquePtr	CreateUnique (Args &&... args)

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

virtual mrpt::rtti::CObject *	clone () const override
	Returns a deep copy (clone) of the object, indepently of its class. More...

Member Typedef Documentation

◆ ConstPtr

using mrpt::poses::CPointPDFGaussian::ConstPtr = std::shared_ptr<const mrpt::poses :: CPointPDFGaussian >

Definition at line 24 of file CPointPDFGaussian.h.

◆ ConstUniquePtr

using mrpt::poses::CPointPDFGaussian::ConstUniquePtr = std::unique_ptr<const mrpt::poses :: CPointPDFGaussian >

Definition at line 24 of file CPointPDFGaussian.h.

◆ cov_mat_t

using mrpt::math::CProbabilityDensityFunction< CPoint3D , STATE_LEN >::cov_mat_t = mrpt::math::CMatrixFixed<double, STATE_LEN, STATE_LEN>

inherited

Covariance matrix type.

Definition at line 37 of file CProbabilityDensityFunction.h.

◆ inf_mat_t

using mrpt::math::CProbabilityDensityFunction< CPoint3D , STATE_LEN >::inf_mat_t = cov_mat_t

inherited

Information matrix type.

Definition at line 39 of file CProbabilityDensityFunction.h.

◆ Ptr

using mrpt::poses::CPointPDFGaussian::Ptr = std::shared_ptr< mrpt::poses :: CPointPDFGaussian >

A type for the associated smart pointer

Definition at line 24 of file CPointPDFGaussian.h.

◆ self_t

using mrpt::math::CProbabilityDensityFunction< CPoint3D , STATE_LEN >::self_t = CProbabilityDensityFunction<CPoint3D , STATE_LEN>

inherited

Definition at line 35 of file CProbabilityDensityFunction.h.

◆ type_value

using mrpt::math::CProbabilityDensityFunction< CPoint3D , STATE_LEN >::type_value = CPoint3D

inherited

The type of the state the PDF represents.

Definition at line 34 of file CProbabilityDensityFunction.h.

◆ UniquePtr

using mrpt::poses::CPointPDFGaussian::UniquePtr = std::unique_ptr< mrpt::poses :: CPointPDFGaussian >

Definition at line 24 of file CPointPDFGaussian.h.

Member Enumeration Documentation

◆ anonymous enum

anonymous enum

inherited

Enumerator
is_3D_val

Definition at line 64 of file CPointPDF.h.

◆ anonymous enum

anonymous enum

inherited

Enumerator
is_PDF_val

Definition at line 69 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 45 of file CPointPDFGaussian.cpp.

References cov, and mrpt::math::MatrixVectorBase< Scalar, Derived >::setZero().

Here is the call graph for this function:

◆ CPointPDFGaussian() [3/3]

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

Constructor.

Definition at line 36 of file CPointPDFGaussian.cpp.

Member Function Documentation

◆ _GetBaseClass()

static const mrpt::rtti::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 156 of file CPointPDFGaussian.cpp.

References mrpt::math::CMatrixFixed< T, ROWS, COLS >::asEigen(), cov, mrpt::math::MatrixBase< Scalar, Derived >::inverse_LLt(), mean, MRPT_END, MRPT_START, mrpt::poses::CPoseOrPoint< DERIVEDCLASS, DIM >::x(), and mrpt::poses::CPoseOrPoint< DERIVEDCLASS, DIM >::y().

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

Here is the call graph for this function:

Here is the caller graph for this function:

◆ bayesianFusion() [2/2]

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

overridevirtual

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.

◆ changeCoordinatesReference()

void CPointPDFGaussian::changeCoordinatesReference ( const CPose3D & newReferenceBase )

overridevirtual

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::poses::CPointPDF.

Definition at line 141 of file CPointPDFGaussian.cpp.

References mrpt::math::CMatrixFixed< T, ROWS, COLS >::asEigen(), cov, mrpt::poses::CPose3D::getRotationMatrix(), mean, and mrpt::math::MatrixVectorBase< Scalar, Derived >::transpose().

Here is the call graph for this function:

◆ clone()

virtual mrpt::rtti::CObject* mrpt::poses::CPointPDFGaussian::clone ( ) const

overridevirtual

Returns a deep copy (clone) of the object, indepently of its class.

Implements mrpt::rtti::CObject.

◆ copyFrom()

void CPointPDFGaussian::copyFrom ( const CPointPDF & o )

overridevirtual

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::math::CProbabilityDensityFunction< TDATA, STATE_LEN >::getCovarianceAndMean(), and mean.

Here is the call graph for this function:

◆ Create()

template<typename... Args>

static Ptr mrpt::poses::CPointPDFGaussian::Create ( Args &&... args )

inlinestatic

Definition at line 24 of file CPointPDFGaussian.h.

◆ CreateAlloc()

template<typename Alloc , typename... Args>

static Ptr mrpt::poses::CPointPDFGaussian::CreateAlloc	(	const Alloc &	alloc,
		Args &&...	args
	)

inlinestatic

Definition at line 24 of file CPointPDFGaussian.h.

◆ CreateObject()

static std::shared_ptr<CObject> mrpt::poses::CPointPDFGaussian::CreateObject ( )

static

◆ CreateUnique()

template<typename... Args>

static UniquePtr mrpt::poses::CPointPDFGaussian::CreateUnique ( Args &&... args )

inlinestatic

Definition at line 24 of file CPointPDFGaussian.h.

◆ drawManySamples()

virtual void mrpt::math::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 151 of file CProbabilityDensityFunction.h.

◆ drawSingleSample() [1/2]

void CPointPDFGaussian::drawSingleSample ( CPoint3D & outSample ) const

override

Draw a sample from the pdf.

Definition at line 260 of file CPointPDFGaussian.cpp.

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

Here is the call graph for this function:

◆ drawSingleSample() [2/2]

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

pure virtualinherited

Draws a single sample from the distribution.

◆ duplicateGetSmartPtr()

mrpt::rtti::CObject::Ptr CObject::duplicateGetSmartPtr ( ) const

inlineinherited

Makes a deep copy of the object and returns a smart pointer to it.

Definition at line 204 of file CObject.h.

References mrpt::rtti::CObject::clone().

Referenced by mrpt::obs::CRawlog::insert().

Here is the call graph for this function:

Here is the caller graph for this function:

◆ 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::CSetOfObjects::Ptr 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 83 of file CPointPDF.h.

References mrpt::opengl::posePDF2opengl().

Here is the call graph for this function:

◆ 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::CSetOfObjects::Ptr as template argument.

Definition at line 94 of file CPointPDF.h.

References mrpt::opengl::posePDF2opengl().

Here is the call graph for this function:

◆ getClassName()

static constexpr auto mrpt::poses::CPointPDFGaussian::getClassName ( )

inlinestatic

Definition at line 24 of file CPointPDFGaussian.h.

◆ getCovariance() [1/3]

void mrpt::math::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 88 of file CProbabilityDensityFunction.h.

◆ getCovariance() [2/3]

void mrpt::math::CProbabilityDensityFunction< CPoint3D , STATE_LEN >::getCovariance ( cov_mat_t & 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 98 of file CProbabilityDensityFunction.h.

◆ getCovariance() [3/3]

cov_mat_t mrpt::math::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 108 of file CProbabilityDensityFunction.h.

◆ getCovarianceAndMean() [1/2]

std::tuple<cov_mat_t, type_value> mrpt::poses::CPointPDFGaussian::getCovarianceAndMean ( ) const

inlineoverridevirtual

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

See also: getMean, getInformationMatrix

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

Definition at line 47 of file CPointPDFGaussian.h.

References cov, and mean.

◆ getCovarianceAndMean() [2/2]

virtual void mrpt::math::CProbabilityDensityFunction< CPoint3D , STATE_LEN >::getCovarianceAndMean	(	cov_mat_t &	c,
		CPoint3D &	mean
	)		const

inlinefinalvirtualinherited

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

Definition at line 54 of file CProbabilityDensityFunction.h.

◆ getCovarianceDynAndMean()

void mrpt::math::CProbabilityDensityFunction< CPoint3D , STATE_LEN >::getCovarianceDynAndMean	(	mrpt::math::CMatrixDouble &	cov,
		type_value &	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 65 of file CProbabilityDensityFunction.h.

◆ getCovarianceEntropy()

double mrpt::math::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 167 of file CProbabilityDensityFunction.h.

◆ getInformationMatrix()

virtual void mrpt::math::CProbabilityDensityFunction< CPoint3D , STATE_LEN >::getInformationMatrix ( inf_mat_t & 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 130 of file CProbabilityDensityFunction.h.

◆ getMean() [1/2]

virtual void mrpt::math::CProbabilityDensityFunction< CPoint3D , STATE_LEN >::getMean ( type_value & 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

override

Definition at line 56 of file CPointPDFGaussian.cpp.

References mean.

◆ getMeanVal()

type_value mrpt::math::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 77 of file CProbabilityDensityFunction.h.

◆ GetRuntimeClass()

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

overridevirtual

Returns information about the class of an object in runtime.

Reimplemented from mrpt::poses::CPointPDF.

◆ GetRuntimeClassIdStatic()

static const mrpt::rtti::TRuntimeClassId& mrpt::poses::CPointPDFGaussian::GetRuntimeClassIdStatic ( )

static

◆ is_3D()

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

inlinestaticinherited

Definition at line 68 of file CPointPDF.h.

References mrpt::poses::CPointPDF::is_3D_val.

◆ is_PDF()

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

inlinestaticinherited

Definition at line 73 of file CPointPDF.h.

References mrpt::poses::CPointPDF::is_PDF_val.

◆ isInfType()

virtual bool mrpt::math::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 123 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 296 of file CPointPDFGaussian.cpp.

References mrpt::math::MatrixVectorBase< Scalar, Derived >::block(), cov, mrpt::math::MatrixBase< Scalar, Derived >::inverse_LLt(), mean, mrpt::math::multiply_HCHt_scalar(), mrpt::poses::CPoseOrPoint< DERIVEDCLASS, DIM >::x(), and mrpt::poses::CPoseOrPoint< DERIVEDCLASS, DIM >::y().

Referenced by productIntegralNormalizedWith(), and productIntegralNormalizedWith2D().

Here is the call graph for this function:

Here is the caller graph for this function:

◆ 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 242 of file CPointPDFGaussian.cpp.

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

Here is the call graph for this function:

◆ 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 251 of file CPointPDFGaussian.cpp.

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

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

Here is the call graph for this function:

Here is the caller graph for this function:

◆ 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 189 of file CPointPDFGaussian.cpp.

References mrpt::math::CMatrixFixed< T, ROWS, COLS >::asEigen(), cov, mrpt::math::MatrixBase< Scalar, Derived >::inverse_LLt(), M_2PI, mean, MRPT_END, MRPT_START, mrpt::math::CProbabilityDensityFunction< CPoint3D, 3 >::state_length, mrpt::poses::CPoseOrPoint< DERIVEDCLASS, DIM >::x(), and mrpt::poses::CPoseOrPoint< DERIVEDCLASS, DIM >::y().

Here is the call graph for this function:

◆ 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 215 of file CPointPDFGaussian.cpp.

References mrpt::math::CMatrixFixed< T, ROWS, COLS >::asEigen(), mrpt::math::MatrixBase< Scalar, Derived >::blockCopy(), cov, mrpt::math::MatrixBase< Scalar, Derived >::inverse_LLt(), M_2PI, mean, MRPT_END, MRPT_START, mrpt::math::CProbabilityDensityFunction< CPoint3D, 3 >::state_length, mrpt::poses::CPoseOrPoint< DERIVEDCLASS, DIM >::x(), and mrpt::poses::CPoseOrPoint< DERIVEDCLASS, DIM >::y().

Here is the call graph for this function:

◆ saveToTextFile()

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

overridevirtual

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::math::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, DIM >::x(), and mrpt::poses::CPoseOrPoint< DERIVEDCLASS, DIM >::y().

Here is the call graph for this function:

◆ serializeFrom() [1/2]

void CPointPDFGaussian::serializeFrom	(	mrpt::serialization::CArchive &	in,
		uint8_t	serial_version
	)

overrideprotectedvirtual

Pure virtual method for reading (deserializing) from an abstract archive.

Users don't call this method directly. Instead, use stream >> object;.

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 I/O error

Implements mrpt::serialization::CSerializable.

Definition at line 63 of file CPointPDFGaussian.cpp.

References mrpt::math::CMatrixFixed< T, ROWS, COLS >::cast_double(), cov, mean, and MRPT_THROW_UNKNOWN_SERIALIZATION_VERSION.

Here is the call graph for this function:

◆ serializeFrom() [2/2]

virtual void mrpt::serialization::CSerializable::serializeFrom ( CSchemeArchiveBase & in )

inlineprotectedvirtualinherited

Virtual method for reading (deserializing) from an abstract schema based archive.

Definition at line 74 of file CSerializable.h.

References mrpt::serialization::CSerializable::GetRuntimeClass(), and THROW_EXCEPTION.

Here is the call graph for this function:

◆ serializeGetVersion()

uint8_t CPointPDFGaussian::serializeGetVersion ( ) const

overrideprotectedvirtual

Must return the current versioning number of the object.

Start in zero for new classes, and increments each time there is a change in the stored format.

Implements mrpt::serialization::CSerializable.

Definition at line 58 of file CPointPDFGaussian.cpp.

◆ serializeTo() [1/2]

void CPointPDFGaussian::serializeTo ( mrpt::serialization::CArchive & out ) const

overrideprotectedvirtual

Pure virtual method for writing (serializing) to an abstract archive.

Users don't call this method directly. Instead, use stream << object;.

Exceptions

std::exception On any I/O error

Implements mrpt::serialization::CSerializable.

Definition at line 59 of file CPointPDFGaussian.cpp.

References cov, mean, and out.

◆ serializeTo() [2/2]

virtual void mrpt::serialization::CSerializable::serializeTo ( CSchemeArchiveBase & out ) const

inlineprotectedvirtualinherited

Virtual method for writing (serializing) to an abstract schema based archive.

Definition at line 64 of file CSerializable.h.

References mrpt::serialization::CSerializable::GetRuntimeClass(), and THROW_EXCEPTION.

Here is the call graph for this function:

◆ writeToMatlab()

virtual mxArray* mrpt::serialization::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 nullptr is class does not support conversion to MATLAB.

Definition at line 90 of file CSerializable.h.

Member Data Documentation

◆ className

constexpr const char* mrpt::poses::CPointPDFGaussian::className = "mrpt::poses" "::" "CPointPDFGaussian"

static

Definition at line 24 of file CPointPDFGaussian.h.

◆ cov

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

The 3x3 covariance matrix.

Definition at line 44 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(), saveToTextFile(), serializeFrom(), serializeTo(), and mrpt::maps::CLandmark::setPose().

◆ mean

CPoint3D mrpt::poses::CPointPDFGaussian::mean

The mean value.

Definition at line 42 of file CPointPDFGaussian.h.

◆ runtimeClassId

const mrpt::rtti::TRuntimeClassId mrpt::poses::CPointPDFGaussian::runtimeClassId

staticprotected

Definition at line 24 of file CPointPDFGaussian.h.

◆ state_length

constexpr size_t mrpt::math::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 32 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

◆ ConstUniquePtr

◆ cov_mat_t

◆ inf_mat_t

◆ Ptr

◆ self_t

◆ type_value

◆ UniquePtr

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()

◆ CreateAlloc()

◆ CreateObject()

◆ CreateUnique()

◆ drawManySamples()

◆ drawSingleSample() [1/2]

◆ drawSingleSample() [2/2]

◆ duplicateGetSmartPtr()

◆ getAs3DObject() [1/2]

◆ getAs3DObject() [2/2]

◆ getClassName()

◆ 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()

◆ GetRuntimeClassIdStatic()

◆ is_3D()

◆ is_PDF()

◆ isInfType()

◆ mahalanobisDistanceTo()

◆ productIntegralNormalizedWith()

◆ productIntegralNormalizedWith2D()

◆ productIntegralWith()

◆ productIntegralWith2D()

◆ saveToTextFile()

◆ serializeFrom() [1/2]

◆ serializeFrom() [2/2]

◆ serializeGetVersion()

◆ serializeTo() [1/2]

◆ serializeTo() [2/2]

◆ writeToMatlab()

Member Data Documentation

◆ className

◆ cov

◆ mean

◆ runtimeClassId

◆ state_length