Detailed Description

A gaussian distribution for 2D points.

Also a method for bayesian fusion is provided.

See also: CPoint2DPDF

Definition at line 24 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 }

typedef CPoint2D	type_value
	The type of the state the PDF represents. More...

typedef CProbabilityDensityFunction< CPoint2D, STATE_LEN >	self_t

Public Member Functions
void *	operator new (size_t size)

void *	operator new[] (size_t size)

void	operator delete (void *ptr) throw ()

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

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

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

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

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

void	getCovarianceAndMean (mrpt::math::CMatrixDouble22 &out_cov, CPoint2D &mean_point) const MRPT_OVERRIDE
	Returns an estimate of the point covariance matrix (2x2 cov matrix) and the mean, both at once. More...

void	copyFrom (const CPoint2DPDF &o) MRPT_OVERRIDE
	Copy operator, translating if necesary (for example, between particles and gaussian representations) More...

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

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

void	bayesianFusion (const 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 MRPT_OVERRIDE
	Draw a sample from the pdf. More...

void	bayesianFusion (const CPoint2DPDF &p1, const CPoint2DPDF &p2, const double &minMahalanobisDistToDrop=0) MRPT_OVERRIDE
	Bayesian fusion of two point distributions (product of two distributions->new distribution), then save the result in this object (WARNING: See implementing classes to see classes that can and cannot be mixtured!) More...

double	mahalanobisDistanceTo (const 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...

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

virtual void	getMean (CPoint2D &mean_point) const=0
	Returns the mean, or mathematical expectation of the probability density distribution (PDF). More...

virtual void	getCovarianceAndMean (mrpt::math::CMatrixFixedNumeric< double, STATE_LEN, STATE_LEN > &cov, CPoint2D &mean_point) const=0
	Returns an estimate of the pose covariance matrix (STATE_LENxSTATE_LEN cov matrix) and the mean, both at once. More...

void	getCovarianceDynAndMean (mrpt::math::CMatrixDouble &cov, CPoint2D &mean_point) const
	Returns an estimate of the pose covariance matrix (STATE_LENxSTATE_LEN cov matrix) and the mean, both at once. More...

CPoint2D	getMeanVal () const
	Returns the mean, or mathematical expectation of the probability density distribution (PDF). More...

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

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

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

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

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

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

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

static bool	is_3D ()

static bool	is_PDF ()

Public Attributes
CPoint2D	mean
	The mean value. More...

mrpt::math::CMatrixDouble22	cov
	The 2x2 covariance matrix. More...

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

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

RTTI stuff
static const mrpt::utils::TRuntimeClassId	classCPoint2DPDF

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

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

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

RTTI stuff
typedef CPoint2DPDFGaussianPtr	Ptr

typedef CPoint2DPDFGaussianPtr	ConstPtr

static mrpt::utils::CLASSINIT	_init_CPoint2DPDFGaussian

static mrpt::utils::TRuntimeClassId	classCPoint2DPDFGaussian

static const mrpt::utils::TRuntimeClassId *	classinfo

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

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

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

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

static CPoint2DPDFGaussianPtr	Create ()

Member Typedef Documentation

◆ ConstPtr

typedef CPoint2DPDFGaussianPtr mrpt::poses::CPoint2DPDFGaussian::ConstPtr

Definition at line 27 of file CPoint2DPDFGaussian.h.

◆ Ptr

typedef CPoint2DPDFGaussianPtr mrpt::poses::CPoint2DPDFGaussian::Ptr

A typedef for the associated smart pointer

Definition at line 27 of file CPoint2DPDFGaussian.h.

◆ self_t

typedef CProbabilityDensityFunction<CPoint2D , STATE_LEN> mrpt::utils::CProbabilityDensityFunction< CPoint2D , STATE_LEN >::self_t

inherited

Definition at line 33 of file CProbabilityDensityFunction.h.

◆ type_value

typedef CPoint2D mrpt::utils::CProbabilityDensityFunction< CPoint2D , STATE_LEN >::type_value

inherited

The type of the state the PDF represents.

Definition at line 32 of file CProbabilityDensityFunction.h.

Member Enumeration Documentation

◆ anonymous enum

anonymous enum

inherited

Enumerator
is_3D_val

Definition at line 51 of file CPoint2DPDF.h.

◆ anonymous enum

anonymous enum

inherited

Enumerator
is_PDF_val

Definition at line 53 of file CPoint2DPDF.h.

Constructor & Destructor Documentation

◆ CPoint2DPDFGaussian() [1/3]

CPoint2DPDFGaussian::CPoint2DPDFGaussian ( )

Default constructor.

Definition at line 34 of file CPoint2DPDFGaussian.cpp.

◆ CPoint2DPDFGaussian() [2/3]

CPoint2DPDFGaussian::CPoint2DPDFGaussian ( const CPoint2D & init_Mean )

Constructor.

Definition at line 50 of file CPoint2DPDFGaussian.cpp.

◆ CPoint2DPDFGaussian() [3/3]

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

Constructor.

Definition at line 41 of file CPoint2DPDFGaussian.cpp.

Member Function Documentation

◆ _GetBaseClass()

static const mrpt::utils::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 133 of file CPoint2DPDFGaussian.cpp.

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

◆ bayesianFusion() [2/2]

void CPoint2DPDFGaussian::bayesianFusion	(	const CPoint2DPDF &	p1,
		const CPoint2DPDF &	p2,
		const double &	minMahalanobisDistToDrop = `0`
	)

virtual

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

Parameters

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

Implements mrpt::poses::CPoint2DPDF.

Definition at line 220 of file CPoint2DPDFGaussian.cpp.

References ASSERT_, CLASS_ID, mrpt::poses::CPoint2DPDF::GetRuntimeClass(), MRPT_END, MRPT_START, MRPT_UNUSED_PARAM, and THROW_EXCEPTION.

◆ changeCoordinatesReference()

void CPoint2DPDFGaussian::changeCoordinatesReference ( const CPose3D & newReferenceBase )

virtual

this = p (+) this.

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

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

Definition at line 118 of file CPoint2DPDFGaussian.cpp.

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

◆ clone()

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

inlineinherited

Cloning interface for smart pointers.

Definition at line 133 of file CObject.h.

◆ copyFrom()

void CPoint2DPDFGaussian::copyFrom ( const CPoint2DPDF & o )

virtual

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

Implements mrpt::poses::CPoint2DPDF.

Definition at line 87 of file CPoint2DPDFGaussian.cpp.

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

◆ Create()

static CPoint2DPDFGaussianPtr mrpt::poses::CPoint2DPDFGaussian::Create ( )

static

◆ CreateObject()

static mrpt::utils::CObject* mrpt::poses::CPoint2DPDFGaussian::CreateObject ( )

static

◆ drawManySamples()

virtual void mrpt::utils::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 125 of file CProbabilityDensityFunction.h.

◆ drawSingleSample() [1/2]

void CPoint2DPDFGaussian::drawSingleSample ( CPoint2D & outSample ) const

Draw a sample from the pdf.

Definition at line 202 of file CPoint2DPDFGaussian.cpp.

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

◆ drawSingleSample() [2/2]

virtual void mrpt::utils::CProbabilityDensityFunction< CPoint2D , STATE_LEN >::drawSingleSample ( CPoint2D & outPart ) const

pure virtualinherited

Draws a single sample from the distribution.

◆ duplicate()

virtual mrpt::utils::CObject* mrpt::poses::CPoint2DPDFGaussian::duplicate ( ) const

virtual

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

Implements mrpt::utils::CObject.

◆ duplicateGetSmartPtr()

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

inlineinherited

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

Definition at line 162 of file CObject.h.

References mrpt::utils::CObjectPtr.

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

◆ getCovariance() [1/3]

void mrpt::utils::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 68 of file CProbabilityDensityFunction.h.

◆ getCovariance() [2/3]

void mrpt::utils::CProbabilityDensityFunction< CPoint2D , STATE_LEN >::getCovariance ( mrpt::math::CMatrixFixedNumeric< double, STATE_LEN, STATE_LEN > & cov ) const

inlineinherited

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

See also: getMean, getCovarianceAndMean, getInformationMatrix

Definition at line 77 of file CProbabilityDensityFunction.h.

◆ getCovariance() [3/3]

mrpt::math::CMatrixFixedNumeric<double,STATE_LEN,STATE_LEN> mrpt::utils::CProbabilityDensityFunction< 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 86 of file CProbabilityDensityFunction.h.

◆ getCovarianceAndMean() [1/2]

virtual void mrpt::utils::CProbabilityDensityFunction< CPoint2D , STATE_LEN >::getCovarianceAndMean	(	mrpt::math::CMatrixFixedNumeric< double, STATE_LEN, STATE_LEN > &	cov,
		CPoint2D &	mean_point
	)		const

pure virtualinherited

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

See also: getMean, getInformationMatrix

◆ getCovarianceAndMean() [2/2]

void mrpt::poses::CPoint2DPDFGaussian::getCovarianceAndMean	(	mrpt::math::CMatrixDouble22 &	out_cov,
		CPoint2D &	mean_point
	)		const

inline

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

See also: getMean

Definition at line 43 of file CPoint2DPDFGaussian.h.

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

◆ getCovarianceDynAndMean()

void mrpt::utils::CProbabilityDensityFunction< CPoint2D , STATE_LEN >::getCovarianceDynAndMean	(	mrpt::math::CMatrixDouble &	cov,
		CPoint2D &	mean_point
	)		const

inlineinherited

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

See also: getMean, getInformationMatrix

Definition at line 48 of file CProbabilityDensityFunction.h.

◆ getCovarianceEntropy()

double mrpt::utils::CProbabilityDensityFunction< 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 144 of file CProbabilityDensityFunction.h.

◆ getInformationMatrix()

virtual void mrpt::utils::CProbabilityDensityFunction< CPoint2D , STATE_LEN >::getInformationMatrix ( mrpt::math::CMatrixFixedNumeric< double, STATE_LEN, STATE_LEN > & inf ) const

inlinevirtualinherited

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

See also: getMean, getCovarianceAndMean

Definition at line 106 of file CProbabilityDensityFunction.h.

◆ getMean() [1/2]

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

inline

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

Definition at line 38 of file CPoint2DPDFGaussian.h.

References mean().

◆ getMean() [2/2]

virtual void mrpt::utils::CProbabilityDensityFunction< CPoint2D , STATE_LEN >::getMean ( CPoint2D & mean_point ) const

pure virtualinherited

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

See also: getCovarianceAndMean, getInformationMatrix

◆ getMeanVal()

CPoint2D mrpt::utils::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 58 of file CProbabilityDensityFunction.h.

◆ GetRuntimeClass()

virtual const mrpt::utils::TRuntimeClassId* mrpt::poses::CPoint2DPDFGaussian::GetRuntimeClass ( ) const

virtual

Returns information about the class of an object in runtime.

Reimplemented from mrpt::poses::CPoint2DPDF.

◆ is_3D()

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

inlinestaticinherited

Definition at line 52 of file CPoint2DPDF.h.

◆ is_PDF()

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

inlinestaticinherited

Definition at line 54 of file CPoint2DPDF.h.

◆ isInfType()

virtual bool mrpt::utils::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 100 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 237 of file CPoint2DPDFGaussian.cpp.

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

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

◆ mahalanobisDistanceToPoint()

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

Returns the Mahalanobis distance from this PDF to some point.

Definition at line 249 of file CPoint2DPDFGaussian.cpp.

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

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

◆ operator delete() [1/3]

void mrpt::poses::CPoint2DPDFGaussian::operator delete	(	void *	ptr	)
throw	(
	)

inline

Definition at line 27 of file CPoint2DPDFGaussian.h.

◆ operator delete() [2/3]

void mrpt::poses::CPoint2DPDFGaussian::operator delete	(	void *	memory,
		void *	ptr
	)
throw	(
	)

inline

Definition at line 27 of file CPoint2DPDFGaussian.h.

◆ operator delete() [3/3]

void mrpt::poses::CPoint2DPDFGaussian::operator delete	(	void *	ptr,
		const std::nothrow_t &
	)
throw	(
	)

inline

Definition at line 27 of file CPoint2DPDFGaussian.h.

◆ operator delete[]()

void mrpt::poses::CPoint2DPDFGaussian::operator delete[]	(	void *	ptr	)
throw	(
	)

inline

Definition at line 27 of file CPoint2DPDFGaussian.h.

◆ operator new() [1/3]

void* mrpt::poses::CPoint2DPDFGaussian::operator new ( size_t size )

inline

Definition at line 27 of file CPoint2DPDFGaussian.h.

◆ operator new() [2/3]

static void* mrpt::poses::CPoint2DPDFGaussian::operator new	(	size_t	size,
		void *	ptr
	)

inlinestatic

Definition at line 27 of file CPoint2DPDFGaussian.h.

◆ operator new() [3/3]

void* mrpt::poses::CPoint2DPDFGaussian::operator new	(	size_t	size,
		const std::nothrow_t &
	)
throw	(
	)

inline

Definition at line 27 of file CPoint2DPDFGaussian.h.

◆ operator new[]()

void* mrpt::poses::CPoint2DPDFGaussian::operator new[] ( size_t size )

inline

Definition at line 27 of file CPoint2DPDFGaussian.h.

◆ 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 194 of file CPoint2DPDFGaussian.cpp.

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

◆ 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 165 of file CPoint2DPDFGaussian.cpp.

References cov, M_2PI, mean, MRPT_END, MRPT_START, mrpt::utils::CProbabilityDensityFunction< CPoint2D, 2 >::state_length, mrpt::math::UNINITIALIZED_MATRIX, mrpt::poses::CPoseOrPoint< DERIVEDCLASS >::x(), and mrpt::poses::CPoseOrPoint< DERIVEDCLASS >::y().

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

◆ readFromStream()

void CPoint2DPDFGaussian::readFromStream	(	mrpt::utils::CStream &	in,
		int	version
	)

protectedvirtual

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

Parameters

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

Exceptions

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

See also: CStream

Implements mrpt::utils::CSerializable.

Definition at line 72 of file CPoint2DPDFGaussian.cpp.

References cov, mean, MRPT_THROW_UNKNOWN_SERIALIZATION_VERSION, and version.

◆ saveToTextFile()

void CPoint2DPDFGaussian::saveToTextFile ( const std::string & file ) const

virtual

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

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

Definition at line 98 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 >::x(), and mrpt::poses::CPoseOrPoint< DERIVEDCLASS >::y().

◆ writeToMatlab()

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

inlinevirtualinherited

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

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

Definition at line 79 of file CSerializable.h.

◆ writeToStream()

void CPoint2DPDFGaussian::writeToStream	(	mrpt::utils::CStream &	out,
		int *	getVersion
	)		const

protectedvirtual

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

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

Parameters

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

Exceptions

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

See also: CStream

Implements mrpt::utils::CSerializable.

Definition at line 59 of file CPoint2DPDFGaussian.cpp.

References cov, mean, and version.

Member Data Documentation

◆ _init_CPoint2DPDFGaussian

mrpt::utils::CLASSINIT mrpt::poses::CPoint2DPDFGaussian::_init_CPoint2DPDFGaussian

staticprotected

Definition at line 27 of file CPoint2DPDFGaussian.h.

◆ classCObject

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

staticinherited

Definition at line 118 of file CObject.h.

◆ classCPoint2DPDF

const mrpt::utils::TRuntimeClassId mrpt::poses::CPoint2DPDF::classCPoint2DPDF

staticinherited

Definition at line 37 of file CPoint2DPDF.h.

◆ classCPoint2DPDFGaussian

mrpt::utils::TRuntimeClassId mrpt::poses::CPoint2DPDFGaussian::classCPoint2DPDFGaussian

static

Definition at line 27 of file CPoint2DPDFGaussian.h.

◆ classCSerializable

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

staticinherited

Definition at line 42 of file CSerializable.h.

◆ classinfo

const mrpt::utils::TRuntimeClassId* mrpt::poses::CPoint2DPDFGaussian::classinfo

static

Definition at line 27 of file CPoint2DPDFGaussian.h.

◆ cov

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

The 2x2 covariance matrix.

Definition at line 35 of file CPoint2DPDFGaussian.h.

Referenced by mrpt::slam::CGridMapAligner::AlignPDF_robustMatch(), bayesianFusion(), changeCoordinatesReference(), copyFrom(), drawSingleSample(), mrpt::slam::CRangeBearingKFSLAM2D::getAs3DObject(), mahalanobisDistanceTo(), productIntegralWith(), readFromStream(), saveToTextFile(), and writeToStream().

◆ mean

CPoint2D mrpt::poses::CPoint2DPDFGaussian::mean

The mean value.

Definition at line 34 of file CPoint2DPDFGaussian.h.

Referenced by mrpt::slam::CGridMapAligner::AlignPDF_robustMatch(), bayesianFusion(), changeCoordinatesReference(), copyFrom(), drawSingleSample(), mrpt::slam::CRangeBearingKFSLAM2D::getAs3DObject(), mahalanobisDistanceTo(), mahalanobisDistanceToPoint(), productIntegralWith(), readFromStream(), saveToTextFile(), and writeToStream().

◆ state_length

const size_t mrpt::utils::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 31 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

◆ Ptr

◆ self_t

◆ type_value

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()

◆ CreateObject()

◆ drawManySamples()

◆ drawSingleSample() [1/2]

◆ drawSingleSample() [2/2]

◆ duplicate()

◆ duplicateGetSmartPtr()

◆ getCovariance() [1/3]

◆ getCovariance() [2/3]

◆ getCovariance() [3/3]

◆ getCovarianceAndMean() [1/2]

◆ getCovarianceAndMean() [2/2]

◆ getCovarianceDynAndMean()

◆ getCovarianceEntropy()

◆ getInformationMatrix()

◆ getMean() [1/2]

◆ getMean() [2/2]

◆ getMeanVal()

◆ GetRuntimeClass()

◆ is_3D()

◆ is_PDF()

◆ isInfType()

◆ mahalanobisDistanceTo()

◆ mahalanobisDistanceToPoint()

◆ operator delete() [1/3]

◆ operator delete() [2/3]

◆ operator delete() [3/3]

◆ operator delete[]()

◆ operator new() [1/3]

◆ operator new() [2/3]

◆ operator new() [3/3]

◆ operator new[]()

◆ productIntegralNormalizedWith()

◆ productIntegralWith()

◆ readFromStream()

◆ saveToTextFile()

◆ writeToMatlab()

◆ writeToStream()

Member Data Documentation

◆ _init_CPoint2DPDFGaussian

◆ classCObject

◆ classCPoint2DPDF

◆ classCPoint2DPDFGaussian

◆ classCSerializable

◆ classinfo

◆ cov

◆ mean

◆ state_length