Detailed Description

template<class TDATA, size_t STATE_LEN>
class mrpt::utils::CProbabilityDensityFunction< TDATA, STATE_LEN >

A generic template for probability density distributions (PDFs).

This template is used as base for many classes in mrpt::poses Any derived class must implement getMean() and a getCovarianceAndMean(). Other methods such as getMean() or getCovariance() are implemented here for convenience.

See also: mprt::poses::CPosePDF, mprt::poses::CPose3DPDF, mprt::poses::CPointPDF

Definition at line 29 of file CProbabilityDensityFunction.h.

#include <mrpt/utils/CProbabilityDensityFunction.h>

Inheritance diagram for mrpt::utils::CProbabilityDensityFunction< TDATA, STATE_LEN >:

Public Types
typedef TDATA	type_value
	The type of the state the PDF represents. More...

typedef CProbabilityDensityFunction< TDATA, STATE_LEN >	self_t

Public Member Functions
virtual void	getMean (TDATA &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, TDATA &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, TDATA &mean_point) const
	Returns an estimate of the pose covariance matrix (STATE_LENxSTATE_LEN cov matrix) and the mean, both at once. More...

TDATA	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	saveToTextFile (const std::string &file) const =0
	Save PDF's particles to a text file. More...

virtual void	drawSingleSample (TDATA &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...

virtual void	changeCoordinatesReference (const mrpt::poses::CPose3D &newReferenceBase)=0
	this = p (+) this. More...

double	getCovarianceEntropy () const
	Compute the entropy of the estimated covariance matrix. More...

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

Member Typedef Documentation

◆ self_t

template<class TDATA, size_t STATE_LEN>

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

Definition at line 37 of file CProbabilityDensityFunction.h.

◆ type_value

template<class TDATA, size_t STATE_LEN>

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

The type of the state the PDF represents.

Definition at line 36 of file CProbabilityDensityFunction.h.

Member Function Documentation

◆ changeCoordinatesReference()

template<class TDATA, size_t STATE_LEN>

virtual void mrpt::utils::CProbabilityDensityFunction< TDATA, STATE_LEN >::changeCoordinatesReference ( const mrpt::poses::CPose3D & newReferenceBase )

pure 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.

Implemented in mrpt::poses::CPosePDFSOG, mrpt::poses::CPointPDFSOG, mrpt::poses::CPose3DPDFGaussian, mrpt::maps::CBeacon, mrpt::poses::CPose3DPDFGaussianInf, mrpt::poses::CPose3DPDFSOG, mrpt::poses::CPosePDFParticles, mrpt::poses::CPose3DQuatPDFGaussian, mrpt::poses::CPosePDFGaussianInf, mrpt::poses::CPose3DQuatPDFGaussianInf, mrpt::poses::CPosePDFGaussian, mrpt::poses::CPointPDFParticles, mrpt::poses::CPose3DPDFParticles, mrpt::poses::CPointPDFGaussian, mrpt::poses::CPosePDFGrid, and mrpt::poses::CPoint2DPDFGaussian.

◆ drawManySamples()

template<class TDATA, size_t STATE_LEN>

virtual void mrpt::utils::CProbabilityDensityFunction< TDATA, STATE_LEN >::drawManySamples	(	size_t	N,
		std::vector< mrpt::math::CVectorDouble > &	outSamples
	)		const

inlinevirtual

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.

Reimplemented in mrpt::poses::CPosePDFSOG, mrpt::poses::CPosePDFGaussianInf, mrpt::poses::CPose3DPDFGaussian, mrpt::poses::CPosePDFGaussian, mrpt::poses::CPose3DPDFSOG, mrpt::poses::CPose3DPDFGaussianInf, mrpt::poses::CPose3DQuatPDFGaussian, mrpt::poses::CPose3DQuatPDFGaussianInf, mrpt::poses::CPose3DPDFParticles, and mrpt::poses::CPosePDFGrid.

Definition at line 154 of file CProbabilityDensityFunction.h.

◆ drawSingleSample()

template<class TDATA, size_t STATE_LEN>

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

pure virtual

Draws a single sample from the distribution.

Referenced by mrpt::utils::CProbabilityDensityFunction< CPose2D, 3 >::drawManySamples().

Here is the caller graph for this function:

◆ getCovariance() [1/3]

template<class TDATA, size_t STATE_LEN>

void mrpt::utils::CProbabilityDensityFunction< TDATA, STATE_LEN >::getCovariance ( mrpt::math::CMatrixDouble & cov ) const

inline

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

See also: getMean, getCovarianceAndMean, getInformationMatrix

Definition at line 81 of file CProbabilityDensityFunction.h.

Referenced by mrpt::maps::CMultiMetricMapPDF::prediction_and_update< mrpt::slam::OptimalProposal >(), mrpt::poses::CPosePDFGaussian::copyFrom(), mrpt::poses::CPosePDFGaussianInf::copyFrom(), and mrpt::poses::CPosePDFSOG::copyFrom().

Here is the caller graph for this function:

◆ getCovariance() [2/3]

template<class TDATA, size_t STATE_LEN>

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

inline

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

See also: getMean, getCovarianceAndMean, getInformationMatrix

Definition at line 91 of file CProbabilityDensityFunction.h.

◆ getCovariance() [3/3]

template<class TDATA, size_t STATE_LEN>

mrpt::math::CMatrixFixedNumeric<double, STATE_LEN, STATE_LEN> mrpt::utils::CProbabilityDensityFunction< TDATA, STATE_LEN >::getCovariance ( ) const

inline

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

See also: getMean, getInformationMatrix

Definition at line 104 of file CProbabilityDensityFunction.h.

Referenced by mrpt::utils::CProbabilityDensityFunction< CPose2D, 3 >::getCovarianceEntropy().

Here is the caller graph for this function:

◆ getCovarianceAndMean()

template<class TDATA, size_t STATE_LEN>

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

pure virtual

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

See also: getMean, getInformationMatrix

Referenced by mrpt::poses::CPoint2DPDFGaussian::copyFrom(), mrpt::poses::CPointPDFGaussian::copyFrom(), mrpt::poses::CPose3DQuatPDFGaussian::copyFrom(), mrpt::poses::CPose3DQuatPDFGaussianInf::copyFrom(), mrpt::poses::CPose3DPDFSOG::copyFrom(), mrpt::poses::CPose3DPDFGaussianInf::copyFrom(), mrpt::poses::CPose3DPDFGaussian::copyFrom(), mrpt::poses::CPointPDFSOG::copyFrom(), mrpt::utils::CProbabilityDensityFunction< CPose2D, 3 >::getCovariance(), mrpt::utils::CProbabilityDensityFunction< CPose2D, 3 >::getCovarianceDynAndMean(), and mrpt::utils::CProbabilityDensityFunction< CPose2D, 3 >::getInformationMatrix().

Here is the caller graph for this function:

◆ getCovarianceDynAndMean()

template<class TDATA, size_t STATE_LEN>

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

inline

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 57 of file CProbabilityDensityFunction.h.

Referenced by mrpt::utils::CProbabilityDensityFunction< CPose2D, 3 >::getCovariance().

Here is the caller graph for this function:

◆ getCovarianceEntropy()

template<class TDATA, size_t STATE_LEN>

double mrpt::utils::CProbabilityDensityFunction< TDATA, STATE_LEN >::getCovarianceEntropy ( ) const

inline

Compute the entropy of the estimated covariance matrix.

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

Definition at line 178 of file CProbabilityDensityFunction.h.

Referenced by mrpt::maps::CMultiMetricMapPDF::getCurrentEntropyOfPaths().

Here is the caller graph for this function:

◆ getInformationMatrix()

template<class TDATA, size_t STATE_LEN>

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

inlinevirtual

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 127 of file CProbabilityDensityFunction.h.

◆ getMean()

template<class TDATA, size_t STATE_LEN>

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

pure virtual

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

See also: getCovarianceAndMean, getInformationMatrix

Referenced by mrpt::poses::CPosePDFGaussian::copyFrom(), mrpt::poses::CPosePDFGaussianInf::copyFrom(), mrpt::poses::CPosePDFSOG::copyFrom(), and mrpt::utils::CProbabilityDensityFunction< CPose2D, 3 >::getMeanVal().

Here is the caller graph for this function:

◆ getMeanVal()

template<class TDATA, size_t STATE_LEN>

TDATA mrpt::utils::CProbabilityDensityFunction< TDATA, STATE_LEN >::getMeanVal ( ) const

inline

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

See also: getCovariance, getInformationMatrix

Definition at line 70 of file CProbabilityDensityFunction.h.

Referenced by mrpt::poses::CPosePDFGaussian::copyFrom(), mrpt::poses::CPosePDFGaussianInf::copyFrom(), mrpt::slam::CMetricMapBuilderICP::initialize(), mrpt::slam::CMetricMapBuilderRBPF::initialize(), and mrpt::slam::CMetricMapBuilderICP::processObservation().

Here is the caller graph for this function:

◆ isInfType()

template<class TDATA, size_t STATE_LEN>

virtual bool mrpt::utils::CProbabilityDensityFunction< TDATA, STATE_LEN >::isInfType ( ) const

inlinevirtual

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::CPose3DPDFGaussianInf, mrpt::poses::CPosePDFGaussianInf, and mrpt::poses::CPose3DQuatPDFGaussianInf.

Definition at line 120 of file CProbabilityDensityFunction.h.

◆ saveToTextFile()

template<class TDATA, size_t STATE_LEN>

virtual void mrpt::utils::CProbabilityDensityFunction< TDATA, STATE_LEN >::saveToTextFile ( const std::string & file ) const

pure virtual

Save PDF's particles to a text file.

See derived classes for more information about the format of generated files.

Member Data Documentation

◆ state_length

template<class TDATA, size_t STATE_LEN>

const size_t mrpt::utils::CProbabilityDensityFunction< TDATA, STATE_LEN >::state_length = STATE_LEN

static

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 34 of file CProbabilityDensityFunction.h.

Detailed Description

template<class TDATA, size_t STATE_LEN> class mrpt::utils::CProbabilityDensityFunction< TDATA, STATE_LEN >

Public Types

Public Member Functions

Static Public Attributes

Member Typedef Documentation

◆ self_t

◆ type_value

Member Function Documentation

◆ changeCoordinatesReference()

◆ drawManySamples()

◆ drawSingleSample()

◆ getCovariance() [1/3]

◆ getCovariance() [2/3]

◆ getCovariance() [3/3]

◆ getCovarianceAndMean()

◆ getCovarianceDynAndMean()

◆ getCovarianceEntropy()

◆ getInformationMatrix()

◆ getMean()

◆ getMeanVal()

◆ isInfType()

◆ saveToTextFile()

Member Data Documentation

◆ state_length

template<class TDATA, size_t STATE_LEN>
class mrpt::utils::CProbabilityDensityFunction< TDATA, STATE_LEN >