Detailed Description

A gaussian distribution for 2D points.

Also a method for bayesian fusion is provided.

See also: CPoint2DPDF

Definition at line 20 of file CPoint2DPDFGaussian.h.

#include <mrpt/poses/CPoint2DPDFGaussian.h>

Inheritance diagram for mrpt::poses::CPoint2DPDFGaussian:

Public Types
enum	{ is_3D_val = 0 }

enum	{ is_PDF_val = 1 }

using	type_value = CPoint2D
	The type of the state the PDF represents. More...

using	self_t = CProbabilityDensityFunction< CPoint2D, 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
	CPoint2DPDFGaussian ()
	Default constructor. More...

	CPoint2DPDFGaussian (const CPoint2D &init_Mean)
	Constructor. More...

	CPoint2DPDFGaussian (const CPoint2D &init_Mean, const mrpt::math::CMatrixDouble22 &init_Cov)
	Constructor. More...

void	getMean (CPoint2D &p) const override
	Returns an estimate of the point, (the mean, or mathematical expectation of the PDF) More...

std::tuple< cov_mat_t, type_value >	getCovarianceAndMean () const override
	Returns an estimate of the point covariance matrix (2x2 cov matrix) and the mean, both at once. More...

void	copyFrom (const CPoint2DPDF &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 CPoint2DPDFGaussian &p1, const CPoint2DPDFGaussian &p2)
	Bayesian fusion of two points gauss. More...

double	productIntegralWith (const CPoint2DPDFGaussian &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 CPoint2DPDFGaussian &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 (CPoint2D &outSample) const override
	Draw a sample from the pdf. More...

void	bayesianFusion (const CPoint2DPDF &p1, const CPoint2DPDF &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 CPoint2DPDFGaussian &other) const
	Returns the Mahalanobis distance from this PDF to another PDF, that is, it's evaluation at (0,0,0) More...

double	mahalanobisDistanceToPoint (const double x, const double y) const
	Returns the Mahalanobis distance from this PDF to some point. 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, CPoint2D &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 (CPoint2D &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
CPoint2D	mean
	The mean value. More...

mrpt::math::CMatrixDouble22	cov
	The 2x2 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 ::CPoint2DPDFGaussian >

using	ConstPtr = std::shared_ptr< const mrpt::poses ::CPoint2DPDFGaussian >

using	UniquePtr = std::unique_ptr< mrpt::poses ::CPoint2DPDFGaussian >

using	ConstUniquePtr = std::unique_ptr< const mrpt::poses ::CPoint2DPDFGaussian >

static const mrpt::rtti::TRuntimeClassId	runtimeClassId

static constexpr const char *	className = "mrpt::poses" "::" "CPoint2DPDFGaussian"

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::CPoint2DPDFGaussian::ConstPtr = std::shared_ptr<const mrpt::poses :: CPoint2DPDFGaussian >

Definition at line 22 of file CPoint2DPDFGaussian.h.

◆ ConstUniquePtr

using mrpt::poses::CPoint2DPDFGaussian::ConstUniquePtr = std::unique_ptr<const mrpt::poses :: CPoint2DPDFGaussian >

Definition at line 22 of file CPoint2DPDFGaussian.h.

◆ cov_mat_t

using mrpt::math::CProbabilityDensityFunction< CPoint2D , 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< CPoint2D , STATE_LEN >::inf_mat_t = cov_mat_t

inherited

Information matrix type.

Definition at line 39 of file CProbabilityDensityFunction.h.

◆ Ptr

using mrpt::poses::CPoint2DPDFGaussian::Ptr = std::shared_ptr< mrpt::poses :: CPoint2DPDFGaussian >

A type for the associated smart pointer

Definition at line 22 of file CPoint2DPDFGaussian.h.

◆ self_t

using mrpt::math::CProbabilityDensityFunction< CPoint2D , STATE_LEN >::self_t = CProbabilityDensityFunction<CPoint2D , STATE_LEN>

inherited

Definition at line 35 of file CProbabilityDensityFunction.h.

◆ type_value

using mrpt::math::CProbabilityDensityFunction< CPoint2D , STATE_LEN >::type_value = CPoint2D

inherited

The type of the state the PDF represents.

Definition at line 34 of file CProbabilityDensityFunction.h.

◆ UniquePtr

using mrpt::poses::CPoint2DPDFGaussian::UniquePtr = std::unique_ptr< mrpt::poses :: CPoint2DPDFGaussian >

Definition at line 22 of file CPoint2DPDFGaussian.h.

Member Enumeration Documentation

◆ anonymous enum

anonymous enum

inherited

Enumerator
is_3D_val

Definition at line 61 of file CPoint2DPDF.h.

◆ anonymous enum

anonymous enum

inherited

Enumerator
is_PDF_val

Definition at line 66 of file CPoint2DPDF.h.

Constructor & Destructor Documentation

◆ CPoint2DPDFGaussian() [1/3]

CPoint2DPDFGaussian::CPoint2DPDFGaussian ( )

Default constructor.

Definition at line 33 of file CPoint2DPDFGaussian.cpp.

◆ CPoint2DPDFGaussian() [2/3]

CPoint2DPDFGaussian::CPoint2DPDFGaussian ( const CPoint2D & init_Mean )

Constructor.

Definition at line 46 of file CPoint2DPDFGaussian.cpp.

◆ CPoint2DPDFGaussian() [3/3]

CPoint2DPDFGaussian::CPoint2DPDFGaussian	(	const CPoint2D &	init_Mean,
		const mrpt::math::CMatrixDouble22 &	init_Cov
	)

Constructor.

Definition at line 37 of file CPoint2DPDFGaussian.cpp.

Member Function Documentation

◆ _GetBaseClass()

static const mrpt::rtti::TRuntimeClassId* mrpt::poses::CPoint2DPDFGaussian::_GetBaseClass ( )

staticprotected

◆ bayesianFusion() [1/2]

void CPoint2DPDFGaussian::bayesianFusion	(	const CPoint2DPDFGaussian &	p1,
		const CPoint2DPDFGaussian &	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 144 of file CPoint2DPDFGaussian.cpp.

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

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◆ bayesianFusion() [2/2]

void mrpt::poses::CPoint2DPDFGaussian::bayesianFusion	(	const CPoint2DPDF &	p1,
		const CPoint2DPDF &	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::CPoint2DPDF.

◆ changeCoordinatesReference()

void CPoint2DPDFGaussian::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::CPoint2DPDF.

Definition at line 128 of file CPoint2DPDFGaussian.cpp.

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

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◆ clone()

virtual mrpt::rtti::CObject* mrpt::poses::CPoint2DPDFGaussian::clone ( ) const

overridevirtual

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

Implements mrpt::rtti::CObject.

◆ copyFrom()

void CPoint2DPDFGaussian::copyFrom ( const CPoint2DPDF & o )

overridevirtual

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

Implements mrpt::poses::CPoint2DPDF.

Definition at line 97 of file CPoint2DPDFGaussian.cpp.

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

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◆ Create()

template<typename... Args>

static Ptr mrpt::poses::CPoint2DPDFGaussian::Create ( Args &&... args )

inlinestatic

Definition at line 22 of file CPoint2DPDFGaussian.h.

◆ CreateAlloc()

template<typename Alloc , typename... Args>

static Ptr mrpt::poses::CPoint2DPDFGaussian::CreateAlloc	(	const Alloc &	alloc,
		Args &&...	args
	)

inlinestatic

Definition at line 22 of file CPoint2DPDFGaussian.h.

◆ CreateObject()

static std::shared_ptr<CObject> mrpt::poses::CPoint2DPDFGaussian::CreateObject ( )

static

◆ CreateUnique()

template<typename... Args>

static UniquePtr mrpt::poses::CPoint2DPDFGaussian::CreateUnique ( Args &&... args )

inlinestatic

Definition at line 22 of file CPoint2DPDFGaussian.h.

◆ drawManySamples()

virtual void mrpt::math::CProbabilityDensityFunction< CPoint2D , 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 CPoint2DPDFGaussian::drawSingleSample ( CPoint2D & outSample ) const

override

Draw a sample from the pdf.

Definition at line 204 of file CPoint2DPDFGaussian.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().

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◆ drawSingleSample() [2/2]

virtual void mrpt::math::CProbabilityDensityFunction< CPoint2D , STATE_LEN >::drawSingleSample ( CPoint2D & 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().

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◆ getClassName()

static constexpr auto mrpt::poses::CPoint2DPDFGaussian::getClassName ( )

inlinestatic

Definition at line 22 of file CPoint2DPDFGaussian.h.

◆ getCovariance() [1/3]

void mrpt::math::CProbabilityDensityFunction< CPoint2D , 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< CPoint2D , 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< CPoint2D , 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::CPoint2DPDFGaussian::getCovarianceAndMean ( ) const

inlineoverridevirtual

Returns an estimate of the point covariance matrix (2x2 cov matrix) and the mean, both at once.

See also: getMean

Implements mrpt::math::CProbabilityDensityFunction< CPoint2D, 2 >.

Definition at line 44 of file CPoint2DPDFGaussian.h.

References cov, and mean.

◆ getCovarianceAndMean() [2/2]

virtual void mrpt::math::CProbabilityDensityFunction< CPoint2D , STATE_LEN >::getCovarianceAndMean	(	cov_mat_t &	c,
		CPoint2D &	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< CPoint2D , 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< CPoint2D , 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< CPoint2D , 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]

void mrpt::poses::CPoint2DPDFGaussian::getMean ( CPoint2D & p ) const

inlineoverride

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

Definition at line 41 of file CPoint2DPDFGaussian.h.

References mean.

◆ getMean() [2/2]

virtual void mrpt::math::CProbabilityDensityFunction< CPoint2D , 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

◆ getMeanVal()

type_value mrpt::math::CProbabilityDensityFunction< CPoint2D , 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::CPoint2DPDFGaussian::GetRuntimeClass ( ) const

overridevirtual

Returns information about the class of an object in runtime.

Reimplemented from mrpt::poses::CPoint2DPDF.

◆ GetRuntimeClassIdStatic()

static const mrpt::rtti::TRuntimeClassId& mrpt::poses::CPoint2DPDFGaussian::GetRuntimeClassIdStatic ( )

static

◆ is_3D()

static constexpr bool mrpt::poses::CPoint2DPDF::is_3D ( )

inlinestaticinherited

Definition at line 65 of file CPoint2DPDF.h.

References mrpt::poses::CPoint2DPDF::is_3D_val.

◆ is_PDF()

static constexpr bool mrpt::poses::CPoint2DPDF::is_PDF ( )

inlinestaticinherited

Definition at line 70 of file CPoint2DPDF.h.

References mrpt::poses::CPoint2DPDF::is_PDF_val.

◆ isInfType()

virtual bool mrpt::math::CProbabilityDensityFunction< CPoint2D , 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 CPoint2DPDFGaussian::mahalanobisDistanceTo ( const CPoint2DPDFGaussian & other ) const

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

Definition at line 241 of file CPoint2DPDFGaussian.cpp.

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

Referenced by mrpt::slam::CGridMapAligner::AlignPDF_robustMatch(), and productIntegralNormalizedWith().

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◆ mahalanobisDistanceToPoint()

double CPoint2DPDFGaussian::mahalanobisDistanceToPoint	(	const double	x,
		const double	y
	)		const

Returns the Mahalanobis distance from this PDF to some point.

Definition at line 255 of file CPoint2DPDFGaussian.cpp.

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

Referenced by mrpt::tfest::se2_l2_robust().

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◆ productIntegralNormalizedWith()

double CPoint2DPDFGaussian::productIntegralNormalizedWith ( const CPoint2DPDFGaussian & 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 195 of file CPoint2DPDFGaussian.cpp.

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

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◆ productIntegralWith()

double CPoint2DPDFGaussian::productIntegralWith ( const CPoint2DPDFGaussian & 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 169 of file CPoint2DPDFGaussian.cpp.

References mrpt::math::CMatrixFixed< T, ROWS, COLS >::asEigen(), cov, M_2PI, mean, MRPT_END, MRPT_START, mrpt::math::CProbabilityDensityFunction< CPoint2D, 2 >::state_length, mrpt::poses::CPoseOrPoint< DERIVEDCLASS, DIM >::x(), and mrpt::poses::CPoseOrPoint< DERIVEDCLASS, DIM >::y().

Referenced by mrpt::slam::CGridMapAligner::AlignPDF_robustMatch().

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◆ saveToTextFile()

bool CPoint2DPDFGaussian::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< CPoint2D, 2 >.

Definition at line 108 of file CPoint2DPDFGaussian.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().

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◆ serializeFrom() [1/2]

void CPoint2DPDFGaussian::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 56 of file CPoint2DPDFGaussian.cpp.

References cov, mean, and MRPT_THROW_UNKNOWN_SERIALIZATION_VERSION.

◆ 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.

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◆ serializeGetVersion()

uint8_t CPoint2DPDFGaussian::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 51 of file CPoint2DPDFGaussian.cpp.

◆ serializeTo() [1/2]

void CPoint2DPDFGaussian::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 52 of file CPoint2DPDFGaussian.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.

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◆ 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::CPoint2DPDFGaussian::className = "mrpt::poses" "::" "CPoint2DPDFGaussian"

static

Definition at line 22 of file CPoint2DPDFGaussian.h.

◆ cov

mrpt::math::CMatrixDouble22 mrpt::poses::CPoint2DPDFGaussian::cov

The 2x2 covariance matrix.

Definition at line 37 of file CPoint2DPDFGaussian.h.

Referenced by mrpt::slam::CGridMapAligner::AlignPDF_robustMatch(), bayesianFusion(), changeCoordinatesReference(), mrpt::poses::CPosePDFGaussian::composePoint(), copyFrom(), drawSingleSample(), mrpt::slam::CRangeBearingKFSLAM2D::getAs3DObject(), getCovarianceAndMean(), mahalanobisDistanceTo(), mahalanobisDistanceToPoint(), productIntegralWith(), saveToTextFile(), serializeFrom(), and serializeTo().

◆ mean

CPoint2D mrpt::poses::CPoint2DPDFGaussian::mean

The mean value.

Definition at line 35 of file CPoint2DPDFGaussian.h.

Referenced by mrpt::slam::CGridMapAligner::AlignPDF_robustMatch(), bayesianFusion(), changeCoordinatesReference(), mrpt::poses::CPosePDFGaussian::composePoint(), copyFrom(), drawSingleSample(), mrpt::slam::CRangeBearingKFSLAM2D::getAs3DObject(), getCovarianceAndMean(), getMean(), mahalanobisDistanceTo(), mahalanobisDistanceToPoint(), productIntegralWith(), saveToTextFile(), serializeFrom(), and serializeTo().

◆ runtimeClassId

const mrpt::rtti::TRuntimeClassId mrpt::poses::CPoint2DPDFGaussian::runtimeClassId

staticprotected

Definition at line 22 of file CPoint2DPDFGaussian.h.

◆ state_length

constexpr size_t mrpt::math::CProbabilityDensityFunction< CPoint2D , 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().

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

◆ CPoint2DPDFGaussian() [1/3]

◆ CPoint2DPDFGaussian() [2/3]

◆ CPoint2DPDFGaussian() [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()

◆ 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()

◆ mahalanobisDistanceToPoint()

◆ productIntegralNormalizedWith()

◆ productIntegralWith()

◆ saveToTextFile()

◆ serializeFrom() [1/2]

◆ serializeFrom() [2/2]

◆ serializeGetVersion()

◆ serializeTo() [1/2]

◆ serializeTo() [2/2]

◆ writeToMatlab()

Member Data Documentation

◆ className

◆ cov

◆ mean

◆ runtimeClassId

◆ state_length