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mrpt::poses::CPoint2DPDFGaussian Class Referenceabstract

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:
Inheritance graph

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

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 ()
 
 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 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...
 
CObjectclone () 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 voidoperator 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::TRuntimeClassIdclassinfo
 
static const mrpt::utils::TRuntimeClassId_GetBaseClass ()
 
virtual const mrpt::utils::TRuntimeClassIdGetRuntimeClass () 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 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

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
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::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

◆ 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::exceptionOn 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::exceptionOn 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
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 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
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 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

◆ mean

CPoint2D mrpt::poses::CPoint2DPDFGaussian::mean

◆ 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().




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