mrpt::utils::CProbabilityDensityFunction< TDATA, STATE_LEN > Class Template Reference

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 50 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.

Public Member Functions
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	getInformationMatrix (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.
virtual void	saveToTextFile (const std::string &file) const =0
	Save PDF's particles to a text file.
virtual void	drawSingleSample (TDATA &outPart) const =0
	Draws a single sample from the distribution.
virtual 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 1xSTATE_LEN vectors, where each row contains a (x,y,z,yaw,pitch,roll) datum.
virtual void	changeCoordinatesReference (const mrpt::poses::CPose3D &newReferenceBase)=0
	this = p (+) this.
double	getCovarianceEntropy () const
	Compute the entropy of the estimated covariance matrix.

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).

Member Typedef Documentation

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 54 of file CProbabilityDensityFunction.h.

Member Function Documentation

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::CPose3DPDFSOG, mrpt::poses::CPosePDFParticles, mrpt::poses::CPose3DPDFGaussian, mrpt::poses::CPose3DPDFGaussianInf, mrpt::slam::CBeacon, mrpt::poses::CPose3DQuatPDFGaussian, mrpt::poses::CPose3DPDFParticles, mrpt::poses::CPosePDFGaussianInf, mrpt::poses::CPointPDFParticles, mrpt::poses::CPosePDFGaussian, mrpt::poses::CPose3DQuatPDFGaussianInf, mrpt::poses::CPosePDFGrid, mrpt::poses::CPoint2DPDFGaussian, and mrpt::poses::CPointPDFGaussian.

template<class TDATA, size_t STATE_LEN>

virtual void mrpt::utils::CProbabilityDensityFunction< TDATA, STATE_LEN >::drawManySamples ( size_t  N, std::vector< vector_double > &  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.

Definition at line 139 of file CProbabilityDensityFunction.h.

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.

template<class TDATA, size_t STATE_LEN>

void mrpt::utils::CProbabilityDensityFunction< TDATA, STATE_LEN >::getCovariance ( 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 89 of file CProbabilityDensityFunction.h.

template<class TDATA, size_t STATE_LEN>

void mrpt::utils::CProbabilityDensityFunction< TDATA, STATE_LEN >::getCovariance ( 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 98 of file CProbabilityDensityFunction.h.

template<class TDATA, size_t STATE_LEN>

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 107 of file CProbabilityDensityFunction.h.

template<class TDATA, size_t STATE_LEN>

virtual void mrpt::utils::CProbabilityDensityFunction< TDATA, STATE_LEN >::getCovarianceAndMean ( 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

template<class TDATA, size_t STATE_LEN>

void mrpt::utils::CProbabilityDensityFunction< TDATA, STATE_LEN >::getCovarianceDynAndMean ( 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 69 of file CProbabilityDensityFunction.h.

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 158 of file CProbabilityDensityFunction.h.

template<class TDATA, size_t STATE_LEN>

virtual void mrpt::utils::CProbabilityDensityFunction< TDATA, STATE_LEN >::getInformationMatrix ( 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 120 of file CProbabilityDensityFunction.h.

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::slam::PF_implementation< PARTICLE_TYPE, MYSELF >::PF_SLAM_implementation_gatherActionsCheckBothActObs().

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 79 of file CProbabilityDensityFunction.h.

Referenced by mrpt::slam::PF_implementation< PARTICLE_TYPE, MYSELF >::PF_SLAM_implementation_gatherActionsCheckBothActObs(), and mrpt::slam::PF_implementation< PARTICLE_TYPE, MYSELF >::PF_SLAM_implementation_pfStandardProposal().

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.

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

Member Data Documentation

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 53 of file CProbabilityDensityFunction.h.