Main MRPT website > C++ reference for MRPT 1.9.9
List of all members | Public Types | Public Member Functions | Static Public Member Functions | Public Attributes | Static Public Attributes
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 23 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 }
 
using type_value = CPoint2D
 The type of the state the PDF represents. More...
 
using self_t = CProbabilityDensityFunction< CPoint2D, STATE_LEN >
 

Public Member Functions

voidoperator new (size_t size)
 
voidoperator new[] (size_t size)
 
void operator delete (void *ptr) noexcept
 
void operator delete[] (void *ptr) noexcept
 
void operator delete (void *memory, void *ptr) noexcept
 
voidoperator new (size_t size, const std::nothrow_t &) noexcept
 
void operator delete (void *ptr, const std::nothrow_t &) noexcept
 
 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 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 override
 Returns an estimate of the point covariance matrix (2x2 cov matrix) and the mean, both at once. More...
 
void copyFrom (const CPoint2DPDF &o) override
 Copy operator, translating if necesary (for example, between particles and gaussian representations) More...
 
bool saveToTextFile (const std::string &file) const 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) 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 override
 Draw a sample from the pdf. More...
 
void bayesianFusion (const CPoint2DPDF &p1, const CPoint2DPDF &p2, const double minMahalanobisDistToDrop=0) 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...
 
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 for polymorphic hierarchies
mrpt::rtti::CObject::Ptr 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 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...
 

Protected Member Functions

CSerializable virtual methods
uint8_t serializeGetVersion () const override
 Must return the current versioning number of the object. More...
 
void serializeTo (mrpt::serialization::CArchive &out) const override
 Pure virtual method for writing (serializing) to an abstract archive. More...
 
void serializeFrom (mrpt::serialization::CArchive &in, uint8_t serial_version) override
 Pure virtual method for reading (deserializing) from an abstract archive. More...
 

RTTI stuff

using Ptr = std::shared_ptr< CPoint2DPDFGaussian >
 
using ConstPtr = std::shared_ptr< const CPoint2DPDFGaussian >
 
using UniquePtr = std::unique_ptr< CPoint2DPDFGaussian >
 
using ConstUniquePtr = std::unique_ptr< const CPoint2DPDFGaussian >
 
static mrpt::rtti::CLASSINIT _init_CPoint2DPDFGaussian
 
static const mrpt::rtti::TRuntimeClassId runtimeClassId
 
static constexpr const char * className = "CPoint2DPDFGaussian"
 
static const mrpt::rtti::TRuntimeClassId_GetBaseClass ()
 
static constexpr auto getClassName ()
 
static const mrpt::rtti::TRuntimeClassIdGetRuntimeClassIdStatic ()
 
static mrpt::rtti::CObjectCreateObject ()
 
template<typename... Args>
static Ptr Create (Args &&... args)
 
template<typename... Args>
static UniquePtr CreateUnique (Args &&... args)
 
virtual const mrpt::rtti::TRuntimeClassIdGetRuntimeClass () const override
 Returns information about the class of an object in runtime. More...
 
virtual mrpt::rtti::CObjectclone () const override
 Returns a deep copy (clone) of the object, indepently of its class. More...
 

Member Typedef Documentation

◆ ConstPtr

Definition at line 25 of file CPoint2DPDFGaussian.h.

◆ ConstUniquePtr

Definition at line 25 of file CPoint2DPDFGaussian.h.

◆ Ptr

A type for the associated smart pointer

Definition at line 25 of file CPoint2DPDFGaussian.h.

◆ self_t

using mrpt::math::CProbabilityDensityFunction< CPoint2D , STATE_LEN >::self_t = CProbabilityDensityFunction<CPoint2D , STATE_LEN>
inherited

Definition at line 36 of file CProbabilityDensityFunction.h.

◆ type_value

The type of the state the PDF represents.

Definition at line 35 of file CProbabilityDensityFunction.h.

◆ UniquePtr

Definition at line 25 of file CPoint2DPDFGaussian.h.

Member Enumeration Documentation

◆ anonymous enum

anonymous enum
inherited
Enumerator
is_3D_val 

Definition at line 63 of file CPoint2DPDF.h.

◆ anonymous enum

anonymous enum
inherited
Enumerator
is_PDF_val 

Definition at line 68 of file CPoint2DPDF.h.

Constructor & Destructor Documentation

◆ CPoint2DPDFGaussian() [1/3]

CPoint2DPDFGaussian::CPoint2DPDFGaussian ( )

Default constructor.

Definition at line 32 of file CPoint2DPDFGaussian.cpp.

◆ CPoint2DPDFGaussian() [2/3]

CPoint2DPDFGaussian::CPoint2DPDFGaussian ( const CPoint2D init_Mean)

Constructor.

Definition at line 45 of file CPoint2DPDFGaussian.cpp.

◆ CPoint2DPDFGaussian() [3/3]

CPoint2DPDFGaussian::CPoint2DPDFGaussian ( const CPoint2D init_Mean,
const mrpt::math::CMatrixDouble22 init_Cov 
)

Constructor.

Definition at line 36 of file CPoint2DPDFGaussian.cpp.

Member Function Documentation

◆ _GetBaseClass()

static const mrpt::rtti::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 118 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 
)
overridevirtual

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 203 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)
overridevirtual

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::poses::CPoint2DPDF.

Definition at line 101 of file CPoint2DPDFGaussian.cpp.

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

◆ clone()

virtual mrpt::rtti::CObject* mrpt::poses::CPoint2DPDFGaussian::clone ( ) const
overridevirtual

Returns a deep copy (clone) of the object, indepently of its class.

Implements mrpt::rtti::CObject.

◆ copyFrom()

void CPoint2DPDFGaussian::copyFrom ( const CPoint2DPDF o)
overridevirtual

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

Implements mrpt::poses::CPoint2DPDF.

Definition at line 70 of file CPoint2DPDFGaussian.cpp.

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

◆ Create()

template<typename... Args>
static Ptr mrpt::poses::CPoint2DPDFGaussian::Create ( Args &&...  args)
inlinestatic

Definition at line 25 of file CPoint2DPDFGaussian.h.

◆ CreateObject()

static mrpt::rtti::CObject* mrpt::poses::CPoint2DPDFGaussian::CreateObject ( )
static

◆ CreateUnique()

template<typename... Args>
static UniquePtr mrpt::poses::CPoint2DPDFGaussian::CreateUnique ( Args &&...  args)
inlinestatic

Definition at line 25 of file CPoint2DPDFGaussian.h.

◆ drawManySamples()

virtual void mrpt::math::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 154 of file CProbabilityDensityFunction.h.

◆ drawSingleSample() [1/2]

void CPoint2DPDFGaussian::drawSingleSample ( CPoint2D outSample) const
override

◆ drawSingleSample() [2/2]

virtual void mrpt::math::CProbabilityDensityFunction< CPoint2D , STATE_LEN >::drawSingleSample ( CPoint2D &  outPart) const
pure virtualinherited

Draws a single sample from the distribution.

◆ duplicateGetSmartPtr()

mrpt::rtti::CObject::Ptr 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 169 of file CObject.h.

References mrpt::rtti::CObject::clone().

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

◆ getClassName()

static constexpr auto mrpt::poses::CPoint2DPDFGaussian::getClassName ( )
inlinestatic

Definition at line 25 of file CPoint2DPDFGaussian.h.

◆ getCovariance() [1/3]

void mrpt::math::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 80 of file CProbabilityDensityFunction.h.

◆ getCovariance() [2/3]

void mrpt::math::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 90 of file CProbabilityDensityFunction.h.

◆ getCovariance() [3/3]

mrpt::math::CMatrixFixedNumeric<double, STATE_LEN, STATE_LEN> mrpt::math::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 103 of file CProbabilityDensityFunction.h.

◆ getCovarianceAndMean() [1/2]

void mrpt::poses::CPoint2DPDFGaussian::getCovarianceAndMean ( mrpt::math::CMatrixDouble22 out_cov,
CPoint2D mean_point 
) const
inlineoverride

Returns an estimate of the point covariance matrix (2x2 cov matrix) and the mean, both at once.

See also
getMean

Definition at line 46 of file CPoint2DPDFGaussian.h.

References cov, and mean.

◆ getCovarianceAndMean() [2/2]

virtual void mrpt::math::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

◆ getCovarianceDynAndMean()

void mrpt::math::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 56 of file CProbabilityDensityFunction.h.

◆ getCovarianceEntropy()

double mrpt::math::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 170 of file CProbabilityDensityFunction.h.

◆ getInformationMatrix()

virtual void mrpt::math::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 126 of file CProbabilityDensityFunction.h.

◆ getMean() [1/2]

virtual void mrpt::math::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

◆ getMean() [2/2]

void mrpt::poses::CPoint2DPDFGaussian::getMean ( CPoint2D p) const
inlineoverride

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

Definition at line 43 of file CPoint2DPDFGaussian.h.

References mean.

◆ getMeanVal()

CPoint2D mrpt::math::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 69 of file CProbabilityDensityFunction.h.

◆ GetRuntimeClass()

virtual const mrpt::rtti::TRuntimeClassId* mrpt::poses::CPoint2DPDFGaussian::GetRuntimeClass ( ) const
overridevirtual

Returns information about the class of an object in runtime.

Reimplemented from mrpt::poses::CPoint2DPDF.

◆ GetRuntimeClassIdStatic()

static const mrpt::rtti::TRuntimeClassId& mrpt::poses::CPoint2DPDFGaussian::GetRuntimeClassIdStatic ( )
static

◆ is_3D()

static bool mrpt::poses::CPoint2DPDF::is_3D ( )
inlinestaticinherited

Definition at line 67 of file CPoint2DPDF.h.

References mrpt::poses::CPoint2DPDF::is_3D_val.

◆ is_PDF()

static bool mrpt::poses::CPoint2DPDF::is_PDF ( )
inlinestaticinherited

Definition at line 72 of file CPoint2DPDF.h.

References mrpt::poses::CPoint2DPDF::is_PDF_val.

◆ isInfType()

virtual bool mrpt::math::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 119 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 222 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 236 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)
inlinenoexcept

Definition at line 25 of file CPoint2DPDFGaussian.h.

◆ operator delete() [2/3]

void mrpt::poses::CPoint2DPDFGaussian::operator delete ( void ptr,
const std::nothrow_t &   
)
inlinenoexcept

Definition at line 25 of file CPoint2DPDFGaussian.h.

◆ operator delete() [3/3]

void mrpt::poses::CPoint2DPDFGaussian::operator delete ( void memory,
void ptr 
)
inlinenoexcept

Definition at line 25 of file CPoint2DPDFGaussian.h.

◆ operator delete[]()

void mrpt::poses::CPoint2DPDFGaussian::operator delete[] ( void ptr)
inlinenoexcept

Definition at line 25 of file CPoint2DPDFGaussian.h.

◆ operator new() [1/3]

void* mrpt::poses::CPoint2DPDFGaussian::operator new ( size_t  size)
inline

Definition at line 25 of file CPoint2DPDFGaussian.h.

◆ operator new() [2/3]

static void* mrpt::poses::CPoint2DPDFGaussian::operator new ( size_t  size,
void ptr 
)
inlinestatic

Definition at line 25 of file CPoint2DPDFGaussian.h.

◆ operator new() [3/3]

void* mrpt::poses::CPoint2DPDFGaussian::operator new ( size_t  size,
const std::nothrow_t &   
)
inlinenoexcept

Definition at line 25 of file CPoint2DPDFGaussian.h.

◆ operator new[]()

void* mrpt::poses::CPoint2DPDFGaussian::operator new[] ( size_t  size)
inline

Definition at line 25 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 175 of file CPoint2DPDFGaussian.cpp.

References mahalanobisDistanceTo(), and mrpt::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 147 of file CPoint2DPDFGaussian.cpp.

References cov, M_2PI, mean, MRPT_END, MRPT_START, mrpt::math::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().

◆ saveToTextFile()

bool CPoint2DPDFGaussian::saveToTextFile ( const std::string file) const
overridevirtual

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::math::CProbabilityDensityFunction< CPoint2D, 2 >.

Definition at line 81 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().

◆ serializeFrom()

void CPoint2DPDFGaussian::serializeFrom ( mrpt::serialization::CArchive in,
uint8_t  serial_version 
)
overrideprotectedvirtual

Pure virtual method for reading (deserializing) from an abstract archive.

Users don't call this method directly. Instead, use stream >> object;.

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 I/O error

Implements mrpt::serialization::CSerializable.

Definition at line 55 of file CPoint2DPDFGaussian.cpp.

References cov, mean, and MRPT_THROW_UNKNOWN_SERIALIZATION_VERSION.

◆ serializeGetVersion()

uint8_t CPoint2DPDFGaussian::serializeGetVersion ( ) const
overrideprotectedvirtual

Must return the current versioning number of the object.

Start in zero for new classes, and increments each time there is a change in the stored format.

Implements mrpt::serialization::CSerializable.

Definition at line 50 of file CPoint2DPDFGaussian.cpp.

◆ serializeTo()

void CPoint2DPDFGaussian::serializeTo ( mrpt::serialization::CArchive out) const
overrideprotectedvirtual

Pure virtual method for writing (serializing) to an abstract archive.

Users don't call this method directly. Instead, use stream << object;.

Exceptions
std::exceptionOn any I/O error

Implements mrpt::serialization::CSerializable.

Definition at line 51 of file CPoint2DPDFGaussian.cpp.

References cov, and mean.

◆ writeToMatlab()

virtual mxArray* mrpt::serialization::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 nullptr is class does not support conversion to MATLAB.

Definition at line 70 of file CSerializable.h.

Member Data Documentation

◆ _init_CPoint2DPDFGaussian

mrpt::rtti::CLASSINIT mrpt::poses::CPoint2DPDFGaussian::_init_CPoint2DPDFGaussian
staticprotected

Definition at line 25 of file CPoint2DPDFGaussian.h.

◆ className

constexpr const char* mrpt::poses::CPoint2DPDFGaussian::className = "CPoint2DPDFGaussian"
static

Definition at line 25 of file CPoint2DPDFGaussian.h.

◆ cov

mrpt::math::CMatrixDouble22 mrpt::poses::CPoint2DPDFGaussian::cov

◆ mean

CPoint2D mrpt::poses::CPoint2DPDFGaussian::mean

◆ runtimeClassId

const mrpt::rtti::TRuntimeClassId mrpt::poses::CPoint2DPDFGaussian::runtimeClassId
staticprotected

Definition at line 25 of file CPoint2DPDFGaussian.h.

◆ state_length

const size_t mrpt::math::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 33 of file CProbabilityDensityFunction.h.

Referenced by productIntegralWith().




Page generated by Doxygen 1.8.14 for MRPT 1.9.9 Git: ad3a9d8ae Tue May 1 23:10:22 2018 -0700 at lun oct 28 00:14:14 CET 2019