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mrpt::poses::CPointPDFGaussian Class Referenceabstract

Detailed Description

A gaussian distribution for 3D points.

Also a method for bayesian fusion is provided.

See Also
CPointPDF

Definition at line 26 of file CPointPDFGaussian.h.

#include <mrpt/poses/CPointPDFGaussian.h>

Inheritance diagram for mrpt::poses::CPointPDFGaussian:
Inheritance graph

Public Types

enum  { is_3D_val = 1 }
 
enum  { is_PDF_val = 1 }
 
typedef CPoint3D type_value
 The type of the state the PDF represents. More...
 
typedef
CProbabilityDensityFunction
< CPoint3D, STATE_LEN > 
self_t
 

Public Member Functions

voidoperator new (size_t size)
 
voidoperator new[] (size_t size)
 
void operator delete (void *ptr) throw ()
 
void operator delete[] (void *ptr) throw ()
 
void operator delete (void *memory, void *ptr) throw ()
 
voidoperator new (size_t size, const std::nothrow_t &) throw ()
 
void operator delete (void *ptr, const std::nothrow_t &) throw ()
 
 CPointPDFGaussian ()
 Default constructor. More...
 
 CPointPDFGaussian (const CPoint3D &init_Mean)
 Constructor. More...
 
 CPointPDFGaussian (const CPoint3D &init_Mean, const mrpt::math::CMatrixDouble33 &init_Cov)
 Constructor. More...
 
void getMean (CPoint3D &p) const MRPT_OVERRIDE
 Returns an estimate of the point, (the mean, or mathematical expectation of the PDF) More...
 
void getCovarianceAndMean (mrpt::math::CMatrixDouble33 &cov, CPoint3D &mean_point) const MRPT_OVERRIDE
 Returns an estimate of the point covariance matrix (3x3 cov matrix) and the mean, both at once. More...
 
void copyFrom (const CPointPDF &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 CPointPDFGaussian &p1, const CPointPDFGaussian &p2)
 Bayesian fusion of two points gauss. More...
 
double productIntegralWith (const CPointPDFGaussian &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 productIntegralWith2D (const CPointPDFGaussian &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 CPointPDFGaussian &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 productIntegralNormalizedWith2D (const CPointPDFGaussian &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 (CPoint3D &outSample) const MRPT_OVERRIDE
 Draw a sample from the pdf. More...
 
void bayesianFusion (const CPointPDF &p1, const CPointPDF &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 CPointPDFGaussian &other, bool only_2D=false) const
 Returns the Mahalanobis distance from this PDF to another PDF, that is, it's evaluation at (0,0,0) 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 , class OPENGL_SETOFOBJECTS >
OPENGL_SETOFOBJECTSPTR getAs3DObject () const
 Returns a 3D representation of this PDF. More...
 
virtual mxArraywriteToMatlab () 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...
 
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...
 
CObjectclone () const
 Cloning interface for smart pointers. More...
 
virtual void getMean (CPoint3D &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, CPoint3D &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, CPoint3D &mean_point) const
 Returns an estimate of the pose covariance matrix (STATE_LENxSTATE_LEN cov matrix) and the mean, both at once. More...
 
CPoint3D 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 (CPoint3D &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...
 

Static Public Member Functions

static voidoperator new (size_t size, void *ptr)
 
static bool is_3D ()
 
static bool is_PDF ()
 

Public Attributes

CPoint3D mean
 The mean value. More...
 
mrpt::math::CMatrixDouble33 cov
 The 3x3 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 
classCPointPDF
 
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 CPointPDFGaussianPtr Ptr
 
typedef CPointPDFGaussianPtr ConstPtr
 
static mrpt::utils::CLASSINIT _init_CPointPDFGaussian
 
static mrpt::utils::TRuntimeClassId classCPointPDFGaussian
 
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::CObjectduplicate () const
 Returns a copy of the object, indepently of its class. More...
 
static mrpt::utils::CObjectCreateObject ()
 
static CPointPDFGaussianPtr Create ()
 

Member Typedef Documentation

typedef CPointPDFGaussianPtr mrpt::poses::CPointPDFGaussian::ConstPtr

Definition at line 29 of file CPointPDFGaussian.h.

typedef CPointPDFGaussianPtr mrpt::poses::CPointPDFGaussian::Ptr

A typedef for the associated smart pointer

Definition at line 29 of file CPointPDFGaussian.h.

typedef CProbabilityDensityFunction<CPoint3D , STATE_LEN> mrpt::utils::CProbabilityDensityFunction< CPoint3D , STATE_LEN >::self_t
inherited

Definition at line 33 of file CProbabilityDensityFunction.h.

The type of the state the PDF represents.

Definition at line 32 of file CProbabilityDensityFunction.h.

Member Enumeration Documentation

anonymous enum
inherited
Enumerator
is_3D_val 

Definition at line 55 of file CPointPDF.h.

anonymous enum
inherited
Enumerator
is_PDF_val 

Definition at line 57 of file CPointPDF.h.

Constructor & Destructor Documentation

CPointPDFGaussian::CPointPDFGaussian ( )

Default constructor.

Definition at line 32 of file CPointPDFGaussian.cpp.

CPointPDFGaussian::CPointPDFGaussian ( const CPoint3D init_Mean)

Constructor.

Definition at line 50 of file CPointPDFGaussian.cpp.

References cov.

CPointPDFGaussian::CPointPDFGaussian ( const CPoint3D init_Mean,
const mrpt::math::CMatrixDouble33 init_Cov 
)

Constructor.

Definition at line 40 of file CPointPDFGaussian.cpp.

Member Function Documentation

static const mrpt::utils::TRuntimeClassId* mrpt::poses::CPointPDFGaussian::_GetBaseClass ( )
staticprotected
void CPointPDFGaussian::bayesianFusion ( const CPointPDFGaussian p1,
const CPointPDFGaussian 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 160 of file CPointPDFGaussian.cpp.

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

Referenced by mrpt::poses::CPointPDFSOG::bayesianFusion(), and mrpt::maps::CLandmarksMap::fuseWith().

void CPointPDFGaussian::bayesianFusion ( const CPointPDF p1,
const CPointPDF 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
p1The first distribution to fuse
p2The second distribution to fuse
minMahalanobisDistToDropIf 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::CPointPDF.

Definition at line 287 of file CPointPDFGaussian.cpp.

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

void CPointPDFGaussian::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< CPoint3D, 3 >.

Definition at line 146 of file CPointPDFGaussian.cpp.

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

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

Cloning interface for smart pointers.

Definition at line 143 of file CObject.h.

void CPointPDFGaussian::copyFrom ( const CPointPDF o)
virtual

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

Implements mrpt::poses::CPointPDF.

Definition at line 113 of file CPointPDFGaussian.cpp.

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

static CPointPDFGaussianPtr mrpt::poses::CPointPDFGaussian::Create ( )
static
static mrpt::utils::CObject* mrpt::poses::CPointPDFGaussian::CreateObject ( )
static
virtual void mrpt::utils::CProbabilityDensityFunction< CPoint3D , 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.

void CPointPDFGaussian::drawSingleSample ( CPoint3D outSample) const
virtual void mrpt::utils::CProbabilityDensityFunction< CPoint3D , STATE_LEN >::drawSingleSample ( CPoint3D &  outPart) const
pure virtualinherited

Draws a single sample from the distribution.

virtual mrpt::utils::CObject* mrpt::poses::CPointPDFGaussian::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
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 140 of file CObject.h.

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

template<class OPENGL_SETOFOBJECTSPTR >
void mrpt::poses::CPointPDF::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::CSetOfObjectsPtr 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 65 of file CPointPDF.h.

References mrpt::opengl::posePDF2opengl().

template<class OPENGL_SETOFOBJECTSPTR , class OPENGL_SETOFOBJECTS >
OPENGL_SETOFOBJECTSPTR mrpt::poses::CPointPDF::getAs3DObject ( ) const
inlineinherited

Returns a 3D representation of this PDF.

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

Definition at line 74 of file CPointPDF.h.

References mrpt::opengl::posePDF2opengl().

void mrpt::utils::CProbabilityDensityFunction< CPoint3D , 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.

void mrpt::utils::CProbabilityDensityFunction< CPoint3D , 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.

mrpt::math::CMatrixFixedNumeric<double,STATE_LEN,STATE_LEN> mrpt::utils::CProbabilityDensityFunction< CPoint3D , 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.

virtual void mrpt::utils::CProbabilityDensityFunction< CPoint3D , STATE_LEN >::getCovarianceAndMean ( mrpt::math::CMatrixFixedNumeric< double, STATE_LEN, STATE_LEN > &  cov,
CPoint3D &  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
void CPointPDFGaussian::getCovarianceAndMean ( mrpt::math::CMatrixDouble33 cov,
CPoint3D mean_point 
) const

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

See Also
getMean

Definition at line 69 of file CPointPDFGaussian.cpp.

References cov, and mean.

void mrpt::utils::CProbabilityDensityFunction< CPoint3D , STATE_LEN >::getCovarianceDynAndMean ( mrpt::math::CMatrixDouble cov,
CPoint3D &  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.

double mrpt::utils::CProbabilityDensityFunction< CPoint3D , 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.

virtual void mrpt::utils::CProbabilityDensityFunction< CPoint3D , 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.

virtual void mrpt::utils::CProbabilityDensityFunction< CPoint3D , STATE_LEN >::getMean ( CPoint3D &  mean_point) const
pure virtualinherited

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

See Also
getCovarianceAndMean, getInformationMatrix
void CPointPDFGaussian::getMean ( CPoint3D p) const

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

Definition at line 61 of file CPointPDFGaussian.cpp.

References mean.

CPoint3D mrpt::utils::CProbabilityDensityFunction< CPoint3D , 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.

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

Returns information about the class of an object in runtime.

Reimplemented from mrpt::poses::CPointPDF.

static bool mrpt::poses::CPointPDF::is_3D ( )
inlinestaticinherited

Definition at line 56 of file CPointPDF.h.

static bool mrpt::poses::CPointPDF::is_PDF ( )
inlinestaticinherited

Definition at line 58 of file CPointPDF.h.

virtual bool mrpt::utils::CProbabilityDensityFunction< CPoint3D , 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.

double CPointPDFGaussian::mahalanobisDistanceTo ( const CPointPDFGaussian other,
bool  only_2D = false 
) const

Returns the Mahalanobis distance from this PDF to another PDF, that is, it's evaluation at (0,0,0)

Definition at line 304 of file CPointPDFGaussian.cpp.

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

Referenced by productIntegralNormalizedWith(), and productIntegralNormalizedWith2D().

void mrpt::poses::CPointPDFGaussian::operator delete ( void ptr)
throw (
)
inline

Definition at line 29 of file CPointPDFGaussian.h.

void mrpt::poses::CPointPDFGaussian::operator delete ( void memory,
void ptr 
)
throw (
)
inline

Definition at line 29 of file CPointPDFGaussian.h.

void mrpt::poses::CPointPDFGaussian::operator delete ( void ptr,
const std::nothrow_t &   
)
throw (
)
inline

Definition at line 29 of file CPointPDFGaussian.h.

void mrpt::poses::CPointPDFGaussian::operator delete[] ( void ptr)
throw (
)
inline

Definition at line 29 of file CPointPDFGaussian.h.

void* mrpt::poses::CPointPDFGaussian::operator new ( size_t  size)
inline

Definition at line 29 of file CPointPDFGaussian.h.

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

Definition at line 29 of file CPointPDFGaussian.h.

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

Definition at line 29 of file CPointPDFGaussian.h.

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

Definition at line 29 of file CPointPDFGaussian.h.

double CPointPDFGaussian::productIntegralNormalizedWith ( const CPointPDFGaussian 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::exceptionOn errors like covariance matrix with null determinant, etc...

Definition at line 253 of file CPointPDFGaussian.cpp.

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

double CPointPDFGaussian::productIntegralNormalizedWith2D ( const CPointPDFGaussian 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]. This versions ignores the "z" coordinate.

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::exceptionOn errors like covariance matrix with null determinant, etc...

Definition at line 261 of file CPointPDFGaussian.cpp.

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

Referenced by mrpt::maps::CLandmarksMap::computeLikelihood_RSLC_2007().

double CPointPDFGaussian::productIntegralWith ( const CPointPDFGaussian 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::exceptionOn errors like covariance matrix with null determinant, etc...

Definition at line 194 of file CPointPDFGaussian.cpp.

References cov, M_2PI, mean, MRPT_END, MRPT_START, mrpt::utils::CProbabilityDensityFunction< CPoint3D, 3 >::state_length, mrpt::math::UNINITIALIZED_MATRIX, mrpt::poses::CPoseOrPoint< DERIVEDCLASS >::x(), and mrpt::poses::CPoseOrPoint< DERIVEDCLASS >::y().

double CPointPDFGaussian::productIntegralWith2D ( const CPointPDFGaussian 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. NOTE: This version ignores the "z" coordinates!!

See Also
productIntegralNormalizedWith
Exceptions
std::exceptionOn errors like covariance matrix with null determinant, etc...

Definition at line 223 of file CPointPDFGaussian.cpp.

References cov, M_2PI, mean, MRPT_END, MRPT_START, mrpt::utils::CProbabilityDensityFunction< CPoint3D, 3 >::state_length, mrpt::math::UNINITIALIZED_MATRIX, mrpt::poses::CPoseOrPoint< DERIVEDCLASS >::x(), and mrpt::poses::CPoseOrPoint< DERIVEDCLASS >::y().

void CPointPDFGaussian::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
inThe input binary stream where the object data must read from.
versionThe 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::exceptionOn any error, see CStream::ReadBuffer
See Also
CStream

Implements mrpt::utils::CSerializable.

Definition at line 91 of file CPointPDFGaussian.cpp.

References cov, mean, and MRPT_THROW_UNKNOWN_SERIALIZATION_VERSION.

void CPointPDFGaussian::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< CPoint3D, 3 >.

Definition at line 124 of file CPointPDFGaussian.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().

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.

void CPointPDFGaussian::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
outThe output binary stream where object must be dumped.
getVersionIf 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::exceptionOn any error, see CStream::WriteBuffer
See Also
CStream

Implements mrpt::utils::CSerializable.

Definition at line 78 of file CPointPDFGaussian.cpp.

References cov, and mean.

Member Data Documentation

mrpt::utils::CLASSINIT mrpt::poses::CPointPDFGaussian::_init_CPointPDFGaussian
staticprotected

Definition at line 29 of file CPointPDFGaussian.h.

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

Definition at line 128 of file CObject.h.

const mrpt::utils::TRuntimeClassId mrpt::poses::CPointPDF::classCPointPDF
staticinherited

Definition at line 40 of file CPointPDF.h.

mrpt::utils::TRuntimeClassId mrpt::poses::CPointPDFGaussian::classCPointPDFGaussian
static

Definition at line 29 of file CPointPDFGaussian.h.

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

Definition at line 42 of file CSerializable.h.

const mrpt::utils::TRuntimeClassId* mrpt::poses::CPointPDFGaussian::classinfo
static

Definition at line 29 of file CPointPDFGaussian.h.

mrpt::math::CMatrixDouble33 mrpt::poses::CPointPDFGaussian::cov
CPoint3D mrpt::poses::CPointPDFGaussian::mean
const size_t mrpt::utils::CProbabilityDensityFunction< CPoint3D , 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(), and productIntegralWith2D().




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