Detailed Description

A Probability Density function (PDF) of a 2D pose $p(\mathbf{x}) = [x ~ y ~ \phi ]^t$ as a Gaussian with a mean and the inverse of the covariance.

This class implements a PDF as a mono-modal Gaussian distribution in its information form, that is, keeping the inverse of the covariance matrix instead of the covariance matrix itself.

This class is the dual of CPosePDFGaussian.

See also:: CPose2D, CPosePDF, CPosePDFParticles

#include <mrpt/poses/CPosePDFGaussianInf.h>

Inheritance diagram for mrpt::poses::CPosePDFGaussianInf:

[legend]

List of all members.

Public Types
enum	{ is_3D_val = 0 }
enum	{ is_PDF_val = 1 }
typedef TDATA	type_value
	The type of the state the PDF represents.
Public Member Functions
const CPose2D &	getPoseMean () const
CPose2D &	getPoseMean ()
	CPosePDFGaussianInf ()
	Default constructor (mean=all zeros, inverse covariance=all zeros -> so be careful!)
	CPosePDFGaussianInf (const CPose2D &init_Mean)
	Constructor with a mean value (inverse covariance=all zeros -> so be careful!)
	CPosePDFGaussianInf (const CPose2D &init_Mean, const CMatrixDouble33 &init_CovInv)
	Constructor.
	CPosePDFGaussianInf (const CPosePDF &o)
	Copy constructor, including transformations between other PDFs.
	CPosePDFGaussianInf (const CPose3DPDF &o)
	Copy constructor, including transformations between other PDFs.
void	getMean (CPose2D &mean_pose) const
	Returns an estimate of the pose, (the mean, or mathematical expectation of the PDF).
void	getCovarianceAndMean (CMatrixDouble33 &cov, CPose2D &mean_point) const
	Returns an estimate of the pose covariance matrix (3x3 cov matrix) and the mean, both at once.
void	copyFrom (const CPosePDF &o)
	Copy operator, translating if necesary (for example, between particles and gaussian representations)
void	copyFrom (const CPose3DPDF &o)
	Copy operator, translating if necesary (for example, between particles and gaussian representations)
void	saveToTextFile (const std::string &file) const
	Save PDF's particles to a text file, containing the 2D pose in the first line, then the covariance matrix in next 3 lines.
void	changeCoordinatesReference (const CPose3D &newReferenceBase)
	This can be used to convert a PDF from local coordinates to global, providing the point (newReferenceBase) from which "to project" the current pdf.
void	changeCoordinatesReference (const CPose2D &newReferenceBase)
	This can be used to convert a PDF from local coordinates to global, providing the point (newReferenceBase) from which "to project" the current pdf.
void	rotateCov (const double ang)
	Rotate the covariance matrix by replacing it by $\mathbf{R}~\mathbf{COV}~\mathbf{R}^t$ , where $\mathbf{R} = \left[ \begin{array}{ccc} \cos\alpha & -\sin\alpha & 0 \\ \sin\alpha & \cos\alpha & 0 \\ 0 & 0 & 1 \end{array}\right]$ .
void	inverseComposition (const CPosePDFGaussianInf &x, const CPosePDFGaussianInf &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!).
void	inverseComposition (const CPosePDFGaussianInf &x1, const CPosePDFGaussianInf &x0, const 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).
void	drawSingleSample (CPose2D &outPart) const
	Draws a single sample from the distribution.
void	drawManySamples (size_t N, std::vector< vector_double > &outSamples) const
	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.
void	bayesianFusion (const CPosePDF &p1, const CPosePDF &p2, const double &minMahalanobisDistToDrop=0)
	Bayesian fusion of two points gauss.
void	inverse (CPosePDF &o) const
	Returns a new PDF such as: NEW_PDF = (0,0,0) - THIS_PDF.
void	operator+= (const CPose2D &Ap)
	Makes: thisPDF = thisPDF + Ap, where "+" is pose composition (both the mean, and the covariance matrix are updated).
double	evaluatePDF (const CPose2D &x) const
	Evaluates the PDF at a given point.
double	evaluateNormalizedPDF (const CPose2D &x) const
	Evaluates the ratio PDF(x) / PDF(MEAN), that is, the normalized PDF in the range [0,1].
double	mahalanobisDistanceTo (const CPosePDFGaussianInf &theOther)
	Computes the Mahalanobis distance between the centers of two Gaussians.
void	operator+= (const CPosePDFGaussianInf &Ap)
	Makes: thisPDF = thisPDF + Ap, where "+" is pose composition (both the mean, and the covariance matrix are updated) (see formulas in jacobiansPoseComposition ).
void	operator-= (const CPosePDFGaussianInf &ref)
	Makes: thisPDF = thisPDF - Ap, where "-" is pose inverse composition (both the mean, and the covariance matrix are updated)
template<class OPENGL_SETOFOBJECTSPTR >
void	getAs3DObject (OPENGL_SETOFOBJECTSPTR &out_obj) const
	Returns a 3D representation of this PDF.
template<class OPENGL_SETOFOBJECTSPTR >
OPENGL_SETOFOBJECTSPTR	getAs3DObject () const
	Returns a 3D representation of this PDF.
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).
CObject *	clone () const
	Cloning interface for smart pointers.
virtual void	getMean (TDATA &mean_point) const =0
	Returns the mean, or mathematical expectation of the probability density distribution (PDF).
virtual void	getCovarianceAndMean (CMatrixFixedNumeric< double, STATE_LEN, STATE_LEN > &cov, TDATA &mean_point) const =0
	Returns an estimate of the pose covariance matrix (STATE_LENxSTATE_LEN cov matrix) and the mean, both at once.
void	getCovarianceDynAndMean (CMatrixDouble &cov, TDATA &mean_point) const
	Returns an estimate of the pose covariance matrix (STATE_LENxSTATE_LEN cov matrix) and the mean, both at once.
TDATA	getMeanVal () const
	Returns the mean, or mathematical expectation of the probability density distribution (PDF).
void	getCovariance (CMatrixDouble &cov) const
	Returns the estimate of the covariance matrix (STATE_LEN x STATE_LEN covariance matrix)
void	getCovariance (CMatrixFixedNumeric< double, STATE_LEN, STATE_LEN > &cov) const
	Returns the estimate of the covariance matrix (STATE_LEN x STATE_LEN covariance matrix)
CMatrixFixedNumeric< double, STATE_LEN, STATE_LEN >	getCovariance () const
	Returns the estimate of the covariance matrix (STATE_LEN x STATE_LEN covariance matrix)
virtual void	drawSingleSample (TDATA &outPart) const =0
	Draws a single sample from the distribution.
double	getCovarianceEntropy () const
	Compute the entropy of the estimated covariance matrix.
Static Public Member Functions
static void	jacobiansPoseComposition (const CPosePDFGaussianInf &x, const CPosePDFGaussianInf &u, CMatrixDouble33 &df_dx, CMatrixDouble33 &df_du)
	This static method computes the pose composition Jacobians, with these formulas:
static bool	is_3D ()
static bool	is_PDF ()
Public Attributes
Data fields
CPose2D	mean
	The mean value.
CMatrixDouble33	cov_inv
	The inverse of the 3x3 covariance matrix (the "information" matrix)
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).
RTTI stuff
static const mrpt::utils::TRuntimeClassId	classCSerializable
Protected Member Functions
void	assureSymmetry ()
	Assures the symmetry of the covariance matrix (eventually certain operations in the math-coprocessor lead to non-symmetric matrixes!)
virtual void	writeToStream (mrpt::utils::CStream &out, int *getVersion) const =0
	Introduces a pure virtual method responsible for writing to a CStream.
virtual void	readFromStream (mrpt::utils::CStream &in, int version)=0
	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.
RTTI stuff
static const mrpt::utils::TRuntimeClassId	classCPosePDF
class	mrpt::utils::CStream
RTTI stuff
typedef CPosePDFGaussianInfPtr	SmartPtr
static mrpt::utils::CLASSINIT	_init_CPosePDFGaussianInf
static mrpt::utils::TRuntimeClassId	classCPosePDFGaussianInf
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.
virtual mrpt::utils::CObject *	duplicate () const
	Returns a copy of the object, indepently of its class.
static mrpt::utils::CObject *	CreateObject ()
static CPosePDFGaussianInfPtr	Create ()

Member Typedef Documentation

typedef CPosePDFGaussianInfPtr mrpt::poses::CPosePDFGaussianInf::SmartPtr

A typedef for the associated smart pointer

Definition at line 58 of file CPosePDFGaussianInf.h.

typedef TDATA mrpt::utils::CProbabilityDensityFunction::type_value [inherited]

The type of the state the PDF represents.

Definition at line 54 of file CProbabilityDensityFunction.h.

Member Enumeration Documentation

anonymous enum [inherited]

Enumerator:

is_3D_val

Definition at line 79 of file CPosePDF.h.

anonymous enum [inherited]

Enumerator:

is_PDF_val

Definition at line 81 of file CPosePDF.h.

Constructor & Destructor Documentation

mrpt::poses::CPosePDFGaussianInf::CPosePDFGaussianInf ( )

Default constructor (mean=all zeros, inverse covariance=all zeros -> so be careful!)

mrpt::poses::CPosePDFGaussianInf::CPosePDFGaussianInf ( const CPose2D & init_Mean ) [explicit]

Constructor with a mean value (inverse covariance=all zeros -> so be careful!)

mrpt::poses::CPosePDFGaussianInf::CPosePDFGaussianInf	(	const CPose2D &	init_Mean,
		const CMatrixDouble33 &	init_CovInv
	)

Constructor.

mrpt::poses::CPosePDFGaussianInf::CPosePDFGaussianInf ( const CPosePDF & o ) [inline, explicit]

Copy constructor, including transformations between other PDFs.

Definition at line 87 of file CPosePDFGaussianInf.h.

mrpt::poses::CPosePDFGaussianInf::CPosePDFGaussianInf ( const CPose3DPDF & o ) [inline, explicit]

Copy constructor, including transformations between other PDFs.

Definition at line 90 of file CPosePDFGaussianInf.h.

Member Function Documentation

static const mrpt::utils::TRuntimeClassId* mrpt::poses::CPosePDFGaussianInf::_GetBaseClass ( ) [static, protected]

Reimplemented from mrpt::poses::CPosePDF.

void mrpt::poses::CPosePDFGaussianInf::assureSymmetry ( ) [protected]

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

void mrpt::poses::CPosePDFGaussianInf::bayesianFusion	(	const CPosePDF &	p1,
		const CPosePDF &	p2,
		const double &	minMahalanobisDistToDrop = `0`
	)		`[virtual]`

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.

void mrpt::poses::CPosePDFGaussianInf::changeCoordinatesReference ( const CPose3D & newReferenceBase ) [virtual]

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::utils::CProbabilityDensityFunction< CPose2D, 3 >.

void mrpt::poses::CPosePDFGaussianInf::changeCoordinatesReference ( const CPose2D & newReferenceBase )

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.

CObject* mrpt::utils::CObject::clone ( ) const [inline, inherited]

Cloning interface for smart pointers.

Reimplemented in mrpt::opengl::CRenderizable, and mrpt::opengl::CRenderizableDisplayList.

Definition at line 154 of file CObject.h.

void mrpt::poses::CPosePDFGaussianInf::copyFrom ( const CPosePDF & o ) [virtual]

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

Implements mrpt::poses::CPosePDF.

Referenced by mrpt::graphs::detail::graph_ops::write_EDGE_line().

void mrpt::poses::CPosePDFGaussianInf::copyFrom ( const CPose3DPDF & o )

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

static CPosePDFGaussianInfPtr mrpt::poses::CPosePDFGaussianInf::Create ( ) [static]

static mrpt::utils::CObject* mrpt::poses::CPosePDFGaussianInf::CreateObject ( ) [static]

void mrpt::poses::CPosePDFGaussianInf::drawManySamples	(	size_t	N,
		std::vector< vector_double > &	outSamples
	)		const `[virtual]`

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::utils::CProbabilityDensityFunction< CPose2D, 3 >.

virtual void mrpt::utils::CProbabilityDensityFunction::drawSingleSample ( TDATA & outPart ) const [pure virtual, inherited]

Draws a single sample from the distribution.

void mrpt::poses::CPosePDFGaussianInf::drawSingleSample ( CPose2D & outPart ) const

Draws a single sample from the distribution.

virtual mrpt::utils::CObject* mrpt::poses::CPosePDFGaussianInf::duplicate ( ) const [virtual]

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

Implements mrpt::utils::CObject.

mrpt::utils::CObjectPtr mrpt::utils::CObject::duplicateGetSmartPtr ( ) const [inline, inherited]

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 151 of file CObject.h.

double mrpt::poses::CPosePDFGaussianInf::evaluateNormalizedPDF ( const CPose2D & x ) const

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

double mrpt::poses::CPosePDFGaussianInf::evaluatePDF ( const CPose2D & x ) const

Evaluates the PDF at a given point.

template<class OPENGL_SETOFOBJECTSPTR >

void mrpt::poses::CPosePDF::getAs3DObject ( OPENGL_SETOFOBJECTSPTR & out_obj ) const [inline, inherited]

Returns a 3D representation of this PDF.

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

Definition at line 88 of file CPosePDF.h.

References mrpt::opengl::posePDF2opengl().

template<class OPENGL_SETOFOBJECTSPTR >

OPENGL_SETOFOBJECTSPTR mrpt::poses::CPosePDF::getAs3DObject ( ) const [inline, inherited]

Returns a 3D representation of this PDF.

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

Definition at line 97 of file CPosePDF.h.

References mrpt::opengl::posePDF2opengl().

void mrpt::utils::CProbabilityDensityFunction::getCovariance ( CMatrixDouble & cov ) const [inline, inherited]

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

See also:: getMean, getCovarianceAndMean

Definition at line 89 of file CProbabilityDensityFunction.h.

References mrpt::utils::CProbabilityDensityFunction::getCovarianceDynAndMean().

void mrpt::utils::CProbabilityDensityFunction::getCovariance ( CMatrixFixedNumeric< double, STATE_LEN, STATE_LEN > & cov ) const [inline, inherited]

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

See also:: getMean, getCovarianceAndMean

Definition at line 98 of file CProbabilityDensityFunction.h.

References mrpt::utils::CProbabilityDensityFunction::getCovarianceAndMean().

CMatrixFixedNumeric<double,STATE_LEN,STATE_LEN> mrpt::utils::CProbabilityDensityFunction::getCovariance ( ) const [inline, inherited]

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

See also:: getMean

Definition at line 107 of file CProbabilityDensityFunction.h.

References mrpt::math::cov(), and mrpt::utils::CProbabilityDensityFunction::getCovarianceAndMean().

virtual void mrpt::utils::CProbabilityDensityFunction::getCovarianceAndMean	(	CMatrixFixedNumeric< double, STATE_LEN, STATE_LEN > &	cov,
		TDATA &	mean_point
	)		const `[pure virtual, inherited]`

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

See also:: getMean

void mrpt::poses::CPosePDFGaussianInf::getCovarianceAndMean	(	CMatrixDouble33 &	cov,
		CPose2D &	mean_point
	)		const

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

See also:: getMean

void mrpt::utils::CProbabilityDensityFunction::getCovarianceDynAndMean	(	CMatrixDouble &	cov,
		TDATA &	mean_point
	)		const `[inline, inherited]`

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

See also:: getMean

Definition at line 69 of file CProbabilityDensityFunction.h.

References mrpt::utils::CProbabilityDensityFunction::getCovarianceAndMean().

double mrpt::utils::CProbabilityDensityFunction::getCovarianceEntropy ( ) const [inline, inherited]

Compute the entropy of the estimated covariance matrix.

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

Definition at line 145 of file CProbabilityDensityFunction.h.

References mrpt::utils::CProbabilityDensityFunction::getCovariance(), and det().

virtual void mrpt::utils::CProbabilityDensityFunction::getMean ( TDATA & mean_point ) const [pure virtual, inherited]

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

See also:: getCovarianceAndMean

void mrpt::poses::CPosePDFGaussianInf::getMean ( CPose2D & mean_pose ) const

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

See also:: getCovariance

TDATA mrpt::utils::CProbabilityDensityFunction::getMeanVal ( ) const [inline, inherited]

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

See also:: getCovariance

Definition at line 79 of file CProbabilityDensityFunction.h.

References mrpt::utils::CProbabilityDensityFunction::getMean().

const CPose2D& mrpt::poses::CPosePDFGaussianInf::getPoseMean ( ) const [inline]

Definition at line 74 of file CPosePDFGaussianInf.h.

References mean().

CPose2D& mrpt::poses::CPosePDFGaussianInf::getPoseMean ( ) [inline]

Definition at line 75 of file CPosePDFGaussianInf.h.

References mean().

virtual const mrpt::utils::TRuntimeClassId* mrpt::poses::CPosePDFGaussianInf::GetRuntimeClass ( ) const [virtual]

Returns information about the class of an object in runtime.

Reimplemented from mrpt::poses::CPosePDF.

void mrpt::poses::CPosePDFGaussianInf::inverse ( CPosePDF & o ) const [virtual]

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

Implements mrpt::poses::CPosePDF.

void mrpt::poses::CPosePDFGaussianInf::inverseComposition	(	const CPosePDFGaussianInf &	x,
		const CPosePDFGaussianInf &	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!).

Referenced by mrpt::poses::operator-().

void mrpt::poses::CPosePDFGaussianInf::inverseComposition	(	const CPosePDFGaussianInf &	x1,
		const CPosePDFGaussianInf &	x0,
		const 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).

static bool mrpt::poses::CPosePDF::is_3D ( ) [inline, static, inherited]

Definition at line 80 of file CPosePDF.h.

static bool mrpt::poses::CPosePDF::is_PDF ( ) [inline, static, inherited]

Definition at line 82 of file CPosePDF.h.

static void mrpt::poses::CPosePDFGaussianInf::jacobiansPoseComposition	(	const CPosePDFGaussianInf &	x,
		const CPosePDFGaussianInf &	u,
		CMatrixDouble33 &	df_dx,
		CMatrixDouble33 &	df_du
	)		`[static]`

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  ]

double mrpt::poses::CPosePDFGaussianInf::mahalanobisDistanceTo ( const CPosePDFGaussianInf & theOther )

Computes the Mahalanobis distance between the centers of two Gaussians.

void mrpt::poses::CPosePDFGaussianInf::operator+= ( const CPose2D & Ap )

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

void mrpt::poses::CPosePDFGaussianInf::operator+= ( const CPosePDFGaussianInf & Ap )

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

void mrpt::poses::CPosePDFGaussianInf::operator-= ( const CPosePDFGaussianInf & ref ) [inline]

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

Definition at line 185 of file CPosePDFGaussianInf.h.

virtual void mrpt::utils::CSerializable::readFromStream	(	mrpt::utils::CStream &	in,
		int	version
	)		`[protected, pure virtual, inherited]`

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

Implemented in mrpt::math::CMatrixD, and mrpt::math::CMatrix.

void mrpt::poses::CPosePDFGaussianInf::rotateCov ( const double ang )

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

void mrpt::poses::CPosePDFGaussianInf::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< CPose2D, 3 >.

virtual void mrpt::utils::CSerializable::writeToStream	(	mrpt::utils::CStream &	out,
		int *	getVersion
	)		const `[protected, pure virtual, inherited]`

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