Detailed Description

Declares a class that represents a Probability Density function (PDF) of a 2D pose $p(\mathbf{x}) = [x ~ y ~ \phi ]^t$ .

This class implements that PDF using a mono-modal Gaussian distribution. See mrpt::poses::CPosePDF for more details.

See also: CPose2D, CPosePDF, CPosePDFParticles

Examples:: serialization_json_example/test.cpp.

Definition at line 28 of file CPosePDFGaussian.h.

#include <mrpt/poses/CPosePDFGaussian.h>

Inheritance diagram for mrpt::poses::CPosePDFGaussian:

Public Types
enum	{ is_3D_val = 0 }

enum	{ is_PDF_val = 1 }

using	type_value = CPose2D
	The type of the state the PDF represents. More...

using	self_t = CProbabilityDensityFunction< CPose2D, 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
const CPose2D &	getPoseMean () const

CPose2D &	getPoseMean ()

	CPosePDFGaussian ()
	Default constructor. More...

	CPosePDFGaussian (const CPose2D &init_Mean)
	Constructor. More...

	CPosePDFGaussian (const CPose2D &init_Mean, const mrpt::math::CMatrixDouble33 &init_Cov)
	Constructor. More...

	CPosePDFGaussian (const CPosePDF &o)
	Copy constructor, including transformations between other PDFs. More...

	CPosePDFGaussian (const CPose3DPDF &o)
	Copy constructor, including transformations between other PDFs. More...

void	getMean (CPose2D &mean_pose) 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 CPosePDF &o) override
	Copy operator, translating if necesary (for example, between particles and gaussian representations) More...

void	copyFrom (const CPose3DPDF &o)
	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	changeCoordinatesReference (const CPose2D &newReferenceBase)
	this = p (+) this. More...

void	rotateCov (const double ang)
	Rotate the covariance matrix by replacing it by $\mathbf{R}~\mathbf{COV}~\mathbf{R}^t$ , where $\mathbf{R} = \left[ \begin{array}{ccc} \cos\alpha & -\sin\alpha & 0 \\ \sin\alpha & \cos\alpha & 0 \\ 0 & 0 & 1 \end{array}\right]$ . More...

void	inverseComposition (const CPosePDFGaussian &x, const CPosePDFGaussian &ref)
	Set $this = x1 \ominus x0$ , computing the mean using the "-" operator and the covariances through the corresponding Jacobians (For 'x0' and 'x1' being independent variables!). More...

void	inverseComposition (const CPosePDFGaussian &x1, const CPosePDFGaussian &x0, const mrpt::math::CMatrixDouble33 &COV_01)
	Set $this = x1 \ominus x0$ , computing the mean using the "-" operator and the covariances through the corresponding Jacobians (Given the 3x3 cross-covariance matrix of variables x0 and x1). More...

void	drawSingleSample (CPose2D &outPart) const override
	Draws a single sample from the distribution. More...

void	drawManySamples (size_t N, std::vector< mrpt::math::CVectorDouble > &outSamples) const override
	Draws a number of samples from the distribution, and saves as a list of 1x3 vectors, where each row contains a (x,y,phi) datum. More...

void	bayesianFusion (const CPosePDF &p1, const CPosePDF &p2, const double minMahalanobisDistToDrop=0) override
	Bayesian fusion of two points gauss. More...

void	inverse (CPosePDF &o) const override
	Returns a new PDF such as: NEW_PDF = (0,0,0) - THIS_PDF. More...

void	operator+= (const CPose2D &Ap)
	Makes: thisPDF = thisPDF + Ap, where "+" is pose composition (both the mean, and the covariance matrix are updated). More...

double	evaluatePDF (const CPose2D &x) const
	Evaluates the PDF at a given point. More...

double	evaluateNormalizedPDF (const CPose2D &x) const
	Evaluates the ratio PDF(x) / PDF(MEAN), that is, the normalized PDF in the range [0,1]. More...

double	mahalanobisDistanceTo (const CPosePDFGaussian &theOther)
	Computes the Mahalanobis distance between the centers of two Gaussians. More...

void	assureMinCovariance (double minStdXY, double minStdPhi)
	Substitutes the diagonal elements if (square) they are below some given minimum values (Use this before bayesianFusion, for example, to avoid inversion of singular matrixes, etc...) More...

void	operator+= (const CPosePDFGaussian &Ap)
	Makes: thisPDF = thisPDF + Ap, where "+" is pose composition (both the mean, and the covariance matrix are updated) (see formulas in jacobiansPoseComposition ). More...

void	operator-= (const CPosePDFGaussian &ref)
	Makes: thisPDF = thisPDF - Ap, where "-" is pose inverse composition (both the mean, and the covariance matrix are updated) More...

void	composePoint (const mrpt::math::TPoint2D &l, CPoint2DPDFGaussian &g) const
	Returns the PDF of the 2D point $g = q \oplus l$ with "q"=this pose and "l" a point without uncertainty. 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 >
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, CPose2D &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 (CPose2D &outPart) const=0
	Draws a single sample from the distribution. 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 void	jacobiansPoseComposition (const CPose2D &x, const CPose2D &u, mrpt::math::CMatrixDouble33 &df_dx, mrpt::math::CMatrixDouble33 &df_du, const bool compute_df_dx=true, const bool compute_df_du=true)
	This static method computes the pose composition Jacobians, with these formulas: More...

static void	jacobiansPoseComposition (const CPosePDFGaussian &x, const CPosePDFGaussian &u, mrpt::math::CMatrixDouble33 &df_dx, mrpt::math::CMatrixDouble33 &df_du)

static constexpr bool	is_3D ()

static constexpr bool	is_PDF ()

Public Attributes
Data fields
CPose2D	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
void	enforceCovSymmetry ()
	Assures the symmetry of the covariance matrix (eventually certain operations in the math-coprocessor lead to non-symmetric matrixes!) More...

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 ::CPosePDFGaussian >

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

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

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

static const mrpt::rtti::TRuntimeClassId	runtimeClassId

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

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

Definition at line 30 of file CPosePDFGaussian.h.

◆ ConstUniquePtr

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

Definition at line 30 of file CPosePDFGaussian.h.

◆ cov_mat_t

using mrpt::math::CProbabilityDensityFunction< CPose2D , 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< CPose2D , STATE_LEN >::inf_mat_t = cov_mat_t

inherited

Information matrix type.

Definition at line 39 of file CProbabilityDensityFunction.h.

◆ Ptr

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

A type for the associated smart pointer

Definition at line 30 of file CPosePDFGaussian.h.

◆ self_t

using mrpt::math::CProbabilityDensityFunction< CPose2D , STATE_LEN >::self_t = CProbabilityDensityFunction<CPose2D , STATE_LEN>

inherited

Definition at line 35 of file CProbabilityDensityFunction.h.

◆ type_value

using mrpt::math::CProbabilityDensityFunction< CPose2D , STATE_LEN >::type_value = CPose2D

inherited

The type of the state the PDF represents.

Definition at line 34 of file CProbabilityDensityFunction.h.

◆ UniquePtr

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

Definition at line 30 of file CPosePDFGaussian.h.

Member Enumeration Documentation

◆ anonymous enum

anonymous enum

inherited

Enumerator
is_3D_val

Definition at line 94 of file CPosePDF.h.

◆ anonymous enum

anonymous enum

inherited

Enumerator
is_PDF_val

Definition at line 99 of file CPosePDF.h.

Constructor & Destructor Documentation

◆ CPosePDFGaussian() [1/5]

CPosePDFGaussian::CPosePDFGaussian ( )

Default constructor.

Definition at line 38 of file CPosePDFGaussian.cpp.

◆ CPosePDFGaussian() [2/5]

CPosePDFGaussian::CPosePDFGaussian ( const CPose2D & init_Mean )

explicit

Constructor.

Definition at line 51 of file CPosePDFGaussian.cpp.

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

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◆ CPosePDFGaussian() [3/5]

CPosePDFGaussian::CPosePDFGaussian	(	const CPose2D &	init_Mean,
		const mrpt::math::CMatrixDouble33 &	init_Cov
	)

Constructor.

Definition at line 42 of file CPosePDFGaussian.cpp.

◆ CPosePDFGaussian() [4/5]

mrpt::poses::CPosePDFGaussian::CPosePDFGaussian ( const CPosePDF & o )

inlineexplicit

Copy constructor, including transformations between other PDFs.

Definition at line 66 of file CPosePDFGaussian.h.

References copyFrom().

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◆ CPosePDFGaussian() [5/5]

mrpt::poses::CPosePDFGaussian::CPosePDFGaussian ( const CPose3DPDF & o )

inlineexplicit

Copy constructor, including transformations between other PDFs.

Definition at line 68 of file CPosePDFGaussian.h.

References copyFrom().

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Member Function Documentation

◆ _GetBaseClass()

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

staticprotected

◆ assureMinCovariance()

void CPosePDFGaussian::assureMinCovariance	(	double	minStdXY,
		double	minStdPhi
	)

Substitutes the diagonal elements if (square) they are below some given minimum values (Use this before bayesianFusion, for example, to avoid inversion of singular matrixes, etc...)

Definition at line 417 of file CPosePDFGaussian.cpp.

References cov, and mrpt::square().

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◆ bayesianFusion()

void CPosePDFGaussian::bayesianFusion	(	const CPosePDF &	p1,
		const CPosePDF &	p2,
		const double	minMahalanobisDistToDrop = `0`
	)

overridevirtual

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 );

Implements mrpt::poses::CPosePDF.

Definition at line 259 of file CPosePDFGaussian.cpp.

References mrpt::math::CMatrixFixed< T, ROWS, COLS >::asEigen(), ASSERT_, CLASS_ID, cov, enforceCovSymmetry(), mrpt::poses::CPosePDF::GetRuntimeClass(), mrpt::math::MatrixBase< Scalar, Derived >::inverse_LLt(), mean, MRPT_END, MRPT_START, mrpt::poses::CPose2D::normalizePhi(), mrpt::poses::CPose2D::phi(), mrpt::poses::CPoseOrPoint< DERIVEDCLASS, DIM >::x(), and mrpt::poses::CPoseOrPoint< DERIVEDCLASS, DIM >::y().

Referenced by mrpt::poses::CPosePDFSOG::bayesianFusion().

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◆ changeCoordinatesReference() [1/2]

void CPosePDFGaussian::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.

Implements mrpt::poses::CPosePDF.

Definition at line 171 of file CPosePDFGaussian.cpp.

References mrpt::poses::CPose2D::composeFrom(), mean, mrpt::poses::CPose2D::phi(), and rotateCov().

Referenced by operator+().

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◆ changeCoordinatesReference() [2/2]

void CPosePDFGaussian::changeCoordinatesReference ( const CPose2D & newReferenceBase )

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.

Definition at line 186 of file CPosePDFGaussian.cpp.

References mrpt::poses::CPose2D::composeFrom(), mean, mrpt::poses::CPose2D::phi(), and rotateCov().

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◆ clone()

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

overridevirtual

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

Implements mrpt::rtti::CObject.

◆ composePoint()

void CPosePDFGaussian::composePoint	(	const mrpt::math::TPoint2D &	l,
		CPoint2DPDFGaussian &	g
	)		const

Returns the PDF of the 2D point $g = q \oplus l$ with "q"=this pose and "l" a point without uncertainty.

Definition at line 542 of file CPosePDFGaussian.cpp.

References mrpt::poses::CPose2D::composePoint(), mrpt::poses::CPoint2DPDFGaussian::cov, cov, mrpt::poses::CPosePDF::jacobiansPoseComposition(), mrpt::poses::CPoint2DPDFGaussian::mean, mean, mrpt::math::MatrixVectorBase< Scalar, Derived >::transpose(), mrpt::math::UNINITIALIZED_MATRIX, mrpt::math::TPoint2D_data< T >::x, mrpt::poses::CPoseOrPoint< DERIVEDCLASS, DIM >::x(), mrpt::math::TPoint2D_data< T >::y, and mrpt::poses::CPoseOrPoint< DERIVEDCLASS, DIM >::y().

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

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◆ copyFrom() [1/2]

void CPosePDFGaussian::copyFrom ( const CPosePDF & o )

overridevirtual

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

Implements mrpt::poses::CPosePDF.

Definition at line 124 of file CPosePDFGaussian.cpp.

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

Referenced by CPosePDFGaussian(), mrpt::poses::CPoseRandomSampler::getOriginalPDFCov2D(), mrpt::slam::CRangeBearingKFSLAM::OnTransitionNoise(), mrpt::maps::CMultiMetricMapPDF::prediction_and_update_pfOptimalProposal(), mrpt::hmtslam::CLSLAM_RBPF_2DLASER::prediction_and_update_pfOptimalProposal(), mrpt::slam::CMetricMapBuilderICP::processObservation(), and mrpt::ros1bridge::toROS().

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◆ copyFrom() [2/2]

void CPosePDFGaussian::copyFrom ( const CPose3DPDF & o )

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

Definition at line 136 of file CPosePDFGaussian.cpp.

References mrpt::math::MatrixVectorBase< Scalar, Derived >::block(), cov, mrpt::math::CProbabilityDensityFunction< TDATA, STATE_LEN >::getCovariance(), mrpt::math::CProbabilityDensityFunction< TDATA, STATE_LEN >::getMeanVal(), and mean.

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◆ Create()

template<typename... Args>

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

inlinestatic

Definition at line 30 of file CPosePDFGaussian.h.

◆ CreateAlloc()

template<typename Alloc , typename... Args>

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

inlinestatic

Definition at line 30 of file CPosePDFGaussian.h.

◆ CreateObject()

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

static

◆ CreateUnique()

template<typename... Args>

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

inlinestatic

Definition at line 30 of file CPosePDFGaussian.h.

◆ drawManySamples()

void CPosePDFGaussian::drawManySamples	(	size_t	N,
		std::vector< mrpt::math::CVectorDouble > &	outSamples
	)		const

overridevirtual

Draws a number of samples from the distribution, and saves as a list of 1x3 vectors, where each row contains a (x,y,phi) datum.

Reimplemented from mrpt::math::CProbabilityDensityFunction< CPose2D, 3 >.

Definition at line 234 of file CPosePDFGaussian.cpp.

References cov, mrpt::random::CRandomGenerator::drawGaussianMultivariateMany(), mrpt::random::getRandomGenerator(), mean, MRPT_END, MRPT_START, mrpt::poses::CPose2D::phi(), mrpt::math::wrapToPiInPlace(), mrpt::poses::CPoseOrPoint< DERIVEDCLASS, DIM >::x(), and mrpt::poses::CPoseOrPoint< DERIVEDCLASS, DIM >::y().

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◆ drawSingleSample() [1/2]

void CPosePDFGaussian::drawSingleSample ( CPose2D & outPart ) const

override

Draws a single sample from the distribution.

Definition at line 213 of file CPosePDFGaussian.cpp.

References cov, mrpt::random::CRandomGenerator::drawGaussianMultivariate(), mrpt::random::getRandomGenerator(), mean, MRPT_END_WITH_CLEAN_UP, MRPT_START, mrpt::poses::CPose2D::normalizePhi(), mrpt::poses::CPose2D::phi(), mrpt::math::MatrixVectorBase< Scalar, Derived >::saveToTextFile(), 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< CPose2D , STATE_LEN >::drawSingleSample ( CPose2D & 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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◆ enforceCovSymmetry()

void CPosePDFGaussian::enforceCovSymmetry ( )

protected

Assures the symmetry of the covariance matrix (eventually certain operations in the math-coprocessor lead to non-symmetric matrixes!)

Definition at line 355 of file CPosePDFGaussian.cpp.

References cov.

Referenced by bayesianFusion().

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◆ evaluateNormalizedPDF()

double CPosePDFGaussian::evaluateNormalizedPDF ( const CPose2D & x ) const

Evaluates the ratio PDF(x) / PDF(MEAN), that is, the normalized PDF in the range [0,1].

Definition at line 343 of file CPosePDFGaussian.cpp.

References cov, mean, and mrpt::math::normalPDF().

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◆ evaluatePDF()

double CPosePDFGaussian::evaluatePDF ( const CPose2D & x ) const

Evaluates the PDF at a given point.

Definition at line 332 of file CPosePDFGaussian.cpp.

References cov, mean, and mrpt::math::normalPDF().

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◆ getAs3DObject() [1/2]

template<class OPENGL_SETOFOBJECTSPTR >

void mrpt::poses::CPosePDF::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 113 of file CPosePDF.h.

References mrpt::opengl::posePDF2opengl().

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◆ getAs3DObject() [2/2]

template<class OPENGL_SETOFOBJECTSPTR >

OPENGL_SETOFOBJECTSPTR mrpt::poses::CPosePDF::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 124 of file CPosePDF.h.

References mrpt::opengl::posePDF2opengl().

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◆ getClassName()

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

inlinestatic

Definition at line 30 of file CPosePDFGaussian.h.

◆ getCovariance() [1/3]

void mrpt::math::CProbabilityDensityFunction< CPose2D , 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.

References mrpt::math::CProbabilityDensityFunction< TDATA, STATE_LEN >::getCovarianceDynAndMean().

◆ getCovariance() [2/3]

void mrpt::math::CProbabilityDensityFunction< CPose2D , 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.

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

◆ getCovariance() [3/3]

cov_mat_t mrpt::math::CProbabilityDensityFunction< CPose2D , 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.

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

◆ getCovarianceAndMean() [1/2]

virtual void mrpt::math::CProbabilityDensityFunction< CPose2D , STATE_LEN >::getCovarianceAndMean	(	cov_mat_t &	c,
		CPose2D &	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.

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

◆ getCovarianceAndMean() [2/2]

std::tuple<cov_mat_t, type_value> mrpt::poses::CPosePDFGaussian::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< CPose2D, 3 >.

Definition at line 72 of file CPosePDFGaussian.h.

References cov, and mean.

◆ getCovarianceDynAndMean()

void mrpt::math::CProbabilityDensityFunction< CPose2D , 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.

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

◆ getCovarianceEntropy()

double mrpt::math::CProbabilityDensityFunction< CPose2D , 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.

References mrpt::math::CProbabilityDensityFunction< TDATA, STATE_LEN >::getCovariance().

◆ getInformationMatrix()

virtual void mrpt::math::CProbabilityDensityFunction< CPose2D , 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.

References mrpt::math::CProbabilityDensityFunction< TDATA, STATE_LEN >::getCovariance(), and mrpt::math::MatrixBase< Scalar, Derived >::inverse_LLt().

◆ getMean() [1/2]

virtual void mrpt::math::CProbabilityDensityFunction< CPose2D , 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 mrpt::poses::CPosePDFGaussian::getMean ( CPose2D & mean_pose ) const

inlineoverride

Definition at line 70 of file CPosePDFGaussian.h.

References mean.

◆ getMeanVal()

type_value mrpt::math::CProbabilityDensityFunction< CPose2D , 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.

References mrpt::math::CProbabilityDensityFunction< TDATA, STATE_LEN >::getMean().

◆ getPoseMean() [1/2]

const CPose2D& mrpt::poses::CPosePDFGaussian::getPoseMean ( ) const

inline

Definition at line 50 of file CPosePDFGaussian.h.

References mean.

◆ getPoseMean() [2/2]

CPose2D& mrpt::poses::CPosePDFGaussian::getPoseMean ( )

inline

Definition at line 51 of file CPosePDFGaussian.h.

References mean.

◆ GetRuntimeClass()

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

overridevirtual

Returns information about the class of an object in runtime.

Reimplemented from mrpt::poses::CPosePDF.

◆ GetRuntimeClassIdStatic()

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

static

◆ inverse()

void CPosePDFGaussian::inverse ( CPosePDF & o ) const

overridevirtual

Returns a new PDF such as: NEW_PDF = (0,0,0) - THIS_PDF.

Implements mrpt::poses::CPosePDF.

Definition at line 297 of file CPosePDFGaussian.cpp.

References mrpt::math::CMatrixFixed< T, ROWS, COLS >::asEigen(), ASSERT_, CLASS_ID, cov, mrpt::poses::CPosePDF::GetRuntimeClass(), mean, out, mrpt::poses::CPose2D::phi(), mrpt::math::MatrixVectorBase< Scalar, Derived >::transpose(), mrpt::poses::CPoseOrPoint< DERIVEDCLASS, DIM >::x(), and mrpt::poses::CPoseOrPoint< DERIVEDCLASS, DIM >::y().

Referenced by PosePDFGaussTests::testPoseInverse().

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◆ inverseComposition() [1/2]

void CPosePDFGaussian::inverseComposition	(	const CPosePDFGaussian &	x,
		const CPosePDFGaussian &	ref
	)

Set $this = x1 \ominus x0$ , computing the mean using the "-" operator and the covariances through the corresponding Jacobians (For 'x0' and 'x1' being independent variables!).

Definition at line 429 of file CPosePDFGaussian.cpp.

References cov, mean, mrpt::math::multiply_HCHt(), mrpt::poses::CPose2D::phi(), mrpt::poses::CPoseOrPoint< DERIVEDCLASS, DIM >::x(), and mrpt::poses::CPoseOrPoint< DERIVEDCLASS, DIM >::y().

Referenced by mrpt::poses::CPosePDFGaussianInf::inverseComposition(), mrpt::poses::operator-(), and operator-=().

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◆ inverseComposition() [2/2]

void CPosePDFGaussian::inverseComposition	(	const CPosePDFGaussian &	x1,
		const CPosePDFGaussian &	x0,
		const mrpt::math::CMatrixDouble33 &	COV_01
	)

Set $this = x1 \ominus x0$ , computing the mean using the "-" operator and the covariances through the corresponding Jacobians (Given the 3x3 cross-covariance matrix of variables x0 and x1).

Definition at line 474 of file CPosePDFGaussian.cpp.

References mrpt::math::CMatrixFixed< T, ROWS, COLS >::asEigen(), cov, mean, mrpt::math::multiply_HCHt(), mrpt::poses::CPose2D::phi(), mrpt::poses::CPoseOrPoint< DERIVEDCLASS, DIM >::x(), and mrpt::poses::CPoseOrPoint< DERIVEDCLASS, DIM >::y().

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◆ is_3D()

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

inlinestaticinherited

Definition at line 98 of file CPosePDF.h.

References mrpt::poses::CPosePDF::is_3D_val.

◆ is_PDF()

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

inlinestaticinherited

Definition at line 103 of file CPosePDF.h.

References mrpt::poses::CPosePDF::is_PDF_val.

◆ isInfType()

virtual bool mrpt::math::CProbabilityDensityFunction< CPose2D , 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

Reimplemented in mrpt::poses::CPosePDFGaussianInf.

Definition at line 123 of file CProbabilityDensityFunction.h.

◆ jacobiansPoseComposition() [1/2]

void CPosePDF::jacobiansPoseComposition	(	const CPose2D &	x,
		const CPose2D &	u,
		mrpt::math::CMatrixDouble33 &	df_dx,
		mrpt::math::CMatrixDouble33 &	df_du,
		const bool	compute_df_dx = `true`,
		const bool	compute_df_du = `true`
	)

staticinherited

This static method computes the pose composition Jacobians, with these formulas:

df_dx =
[ 1, 0, -sin(phi_x)*x_u-cos(phi_x)*y_u ]
[ 0, 1,  cos(phi_x)*x_u-sin(phi_x)*y_u ]
[ 0, 0,                              1 ]
df_du =
[ cos(phi_x) , -sin(phi_x) ,  0  ]
[ sin(phi_x) ,  cos(phi_x) ,  0  ]
[         0  ,          0  ,  1  ]

Definition at line 32 of file CPosePDF.cpp.

References mrpt::poses::CPose2D::phi(), mrpt::math::MatrixBase< Scalar, Derived >::setIdentity(), mrpt::poses::CPoseOrPoint< DERIVEDCLASS, DIM >::x(), and mrpt::poses::CPoseOrPoint< DERIVEDCLASS, DIM >::y().

Referenced by composePoint(), mrpt::poses::CPosePDF::jacobiansPoseComposition(), operator+=(), and mrpt::poses::CPosePDFGaussianInf::operator+=().

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◆ jacobiansPoseComposition() [2/2]

void CPosePDF::jacobiansPoseComposition	(	const CPosePDFGaussian &	x,
		const CPosePDFGaussian &	u,
		mrpt::math::CMatrixDouble33 &	df_dx,
		mrpt::math::CMatrixDouble33 &	df_du
	)

staticinherited

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 22 of file CPosePDF.cpp.

References mrpt::poses::CPosePDF::jacobiansPoseComposition().

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◆ mahalanobisDistanceTo()

double CPosePDFGaussian::mahalanobisDistanceTo ( const CPosePDFGaussian & theOther )

Computes the Mahalanobis distance between the centers of two Gaussians.

Definition at line 367 of file CPosePDFGaussian.cpp.

References mrpt::math::CMatrixFixed< T, ROWS, COLS >::asEigen(), cov, mrpt::math::MatrixBase< Scalar, Derived >::inverse_LLt(), mean, MRPT_END, MRPT_START, mrpt::math::multiply_HtCH_scalar(), and mrpt::math::wrapToPiInPlace().

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

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◆ operator+=() [1/2]

void CPosePDFGaussian::operator+= ( const CPose2D & Ap )

Makes: thisPDF = thisPDF + Ap, where "+" is pose composition (both the mean, and the covariance matrix are updated).

Definition at line 323 of file CPosePDFGaussian.cpp.

References mean, and rotateCov().

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◆ operator+=() [2/2]

void CPosePDFGaussian::operator+= ( const CPosePDFGaussian & Ap )

Makes: thisPDF = thisPDF + Ap, where "+" is pose composition (both the mean, and the covariance matrix are updated) (see formulas in jacobiansPoseComposition ).

Definition at line 522 of file CPosePDFGaussian.cpp.

References cov, mrpt::poses::CPosePDF::jacobiansPoseComposition(), mean, mrpt::math::multiply_HCHt(), and mrpt::math::UNINITIALIZED_MATRIX.

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◆ operator-=()

void mrpt::poses::CPosePDFGaussian::operator-= ( const CPosePDFGaussian & ref )

inline

Makes: thisPDF = thisPDF - Ap, where "-" is pose inverse composition (both the mean, and the covariance matrix are updated)

Definition at line 179 of file CPosePDFGaussian.h.

References inverseComposition().

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◆ rotateCov()

void CPosePDFGaussian::rotateCov ( const double ang )

Rotate the covariance matrix by replacing it by $\mathbf{R}~\mathbf{COV}~\mathbf{R}^t$ , where $\mathbf{R} = \left[ \begin{array}{ccc} \cos\alpha & -\sin\alpha & 0 \\ \sin\alpha & \cos\alpha & 0 \\ 0 & 0 & 1 \end{array}\right]$ .

Definition at line 198 of file CPosePDFGaussian.cpp.

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

Referenced by changeCoordinatesReference(), mrpt::slam::CRangeBearingKFSLAM2D::OnTransitionNoise(), and operator+=().

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◆ saveToTextFile()

bool CPosePDFGaussian::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< CPose2D, 3 >.

Definition at line 153 of file CPosePDFGaussian.cpp.

References cov, mrpt::system::os::fclose(), mrpt::system::os::fopen(), mrpt::system::os::fprintf(), mean, mrpt::poses::CPose2D::phi(), mrpt::poses::CPoseOrPoint< DERIVEDCLASS, DIM >::x(), and mrpt::poses::CPoseOrPoint< DERIVEDCLASS, DIM >::y().

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◆ serializeFrom() [1/2]

void CPosePDFGaussian::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 CPosePDFGaussian.cpp.

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

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◆ 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 CPosePDFGaussian::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 57 of file CPosePDFGaussian.cpp.

◆ serializeTo() [1/2]

void CPosePDFGaussian::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 58 of file CPosePDFGaussian.cpp.

References cov, mean, out, and mrpt::math::serializeSymmetricMatrixTo().

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◆ 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::CPosePDFGaussian::className = "mrpt::poses" "::" "CPosePDFGaussian"

static

Definition at line 30 of file CPosePDFGaussian.h.

◆ cov

mrpt::math::CMatrixDouble33 mrpt::poses::CPosePDFGaussian::cov

The 3x3 covariance matrix.

Definition at line 46 of file CPosePDFGaussian.h.

Referenced by mrpt::slam::CGridMapAligner::AlignPDF_robustMatch(), assureMinCovariance(), mrpt::graphs::detail::graph_ops< graph_t >::auxMaha2Dist(), bayesianFusion(), mrpt::poses::CPosePDFSOG::bayesianFusion(), composePoint(), copyFrom(), mrpt::poses::CPose3DPDFGaussian::CPose3DPDFGaussian(), CPosePDFGaussian(), drawManySamples(), drawSingleSample(), enforceCovSymmetry(), evaluateNormalizedPDF(), evaluatePDF(), getCovarianceAndMean(), mrpt::slam::CMetricMapBuilderICP::getCurrentPoseEstimation(), mrpt::slam::CRangeBearingKFSLAM2D::getCurrentRobotPose(), mrpt::slam::CRangeBearingKFSLAM2D::getCurrentState(), mrpt::poses::CPoseRandomSampler::getOriginalPDFCov2D(), inverse(), inverseComposition(), mrpt::poses::CPosePDFGaussianInf::inverseComposition(), mrpt::maps::COccupancyGridMap2D::laserScanSimulatorWithUncertainty(), mahalanobisDistanceTo(), mrpt::slam::CRangeBearingKFSLAM2D::OnTransitionNoise(), operator+=(), mrpt::poses::operator<<(), mrpt::poses::operator==(), mrpt::slam::CMetricMapBuilderICP::processObservation(), ransac_data_assoc_run(), rotateCov(), mrpt::apps::RBPF_SLAM_App_Base::run(), saveToTextFile(), mrpt::tfest::se2_l2(), mrpt::tfest::se2_l2_robust(), serializeFrom(), serializeTo(), PosePDFGaussTests::testPoseInverse(), and mrpt::ros1bridge::toROS().

◆ mean

CPose2D mrpt::poses::CPosePDFGaussian::mean

The mean value.

Definition at line 44 of file CPosePDFGaussian.h.

Referenced by mrpt::slam::CGridMapAligner::AlignPDF_robustMatch(), bayesianFusion(), mrpt::poses::CPosePDFSOG::bayesianFusion(), changeCoordinatesReference(), composePoint(), copyFrom(), drawManySamples(), drawSingleSample(), evaluateNormalizedPDF(), evaluatePDF(), getCovarianceAndMean(), mrpt::slam::CMetricMapBuilderICP::getCurrentPoseEstimation(), mrpt::slam::CRangeBearingKFSLAM2D::getCurrentRobotPose(), mrpt::slam::CRangeBearingKFSLAM2D::getCurrentState(), getMean(), getPoseMean(), mrpt::slam::CICP::ICP_Method_Classic(), mrpt::slam::CICP::ICP_Method_LM(), inverse(), inverseComposition(), mrpt::poses::CPosePDFGaussianInf::inverseComposition(), mrpt::maps::COccupancyGridMap2D::laserScanSimulatorWithUncertainty(), mahalanobisDistanceTo(), operator+=(), mrpt::poses::operator<<(), mrpt::poses::operator==(), mrpt::maps::CMultiMetricMapPDF::prediction_and_update_pfOptimalProposal(), mrpt::slam::CMetricMapBuilderICP::processObservation(), ransac_data_assoc_run(), mrpt::apps::RBPF_SLAM_App_Base::run(), saveToTextFile(), mrpt::tfest::se2_l2(), mrpt::tfest::se2_l2_robust(), serializeFrom(), serializeTo(), PosePDFGaussTests::testPoseInverse(), and mrpt::ros1bridge::toROS().

◆ runtimeClassId

const mrpt::rtti::TRuntimeClassId mrpt::poses::CPosePDFGaussian::runtimeClassId

staticprotected

Definition at line 30 of file CPosePDFGaussian.h.

◆ state_length

constexpr size_t mrpt::math::CProbabilityDensityFunction< CPose2D , 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.

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

◆ CPosePDFGaussian() [1/5]

◆ CPosePDFGaussian() [2/5]

◆ CPosePDFGaussian() [3/5]

◆ CPosePDFGaussian() [4/5]

◆ CPosePDFGaussian() [5/5]

Member Function Documentation

◆ _GetBaseClass()

◆ assureMinCovariance()

◆ bayesianFusion()

◆ changeCoordinatesReference() [1/2]

◆ changeCoordinatesReference() [2/2]

◆ clone()

◆ composePoint()

◆ copyFrom() [1/2]

◆ copyFrom() [2/2]

◆ Create()

◆ CreateAlloc()

◆ CreateObject()

◆ CreateUnique()

◆ drawManySamples()

◆ drawSingleSample() [1/2]

◆ drawSingleSample() [2/2]

◆ duplicateGetSmartPtr()

◆ enforceCovSymmetry()

◆ evaluateNormalizedPDF()

◆ evaluatePDF()

◆ 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()

◆ getPoseMean() [1/2]

◆ getPoseMean() [2/2]

◆ GetRuntimeClass()

◆ GetRuntimeClassIdStatic()

◆ inverse()

◆ inverseComposition() [1/2]

◆ inverseComposition() [2/2]

◆ is_3D()

◆ is_PDF()

◆ isInfType()

◆ jacobiansPoseComposition() [1/2]

◆ jacobiansPoseComposition() [2/2]

◆ mahalanobisDistanceTo()

◆ operator+=() [1/2]

◆ operator+=() [2/2]

◆ operator-=()

◆ rotateCov()

◆ saveToTextFile()

◆ serializeFrom() [1/2]