A gaussian distribution for 3D points.
Also a method for bayesian fusion is provided.
Definition at line 26 of file CPointPDFGaussian.h.
#include <mrpt/poses/CPointPDFGaussian.h>
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... | |
Public Member Functions | |
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 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 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 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 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 <br> | |
static const mrpt::utils::TRuntimeClassId | classCPointPDF |
Protected Member Functions | |
CSerializable virtual methods | |
void | writeToStream (mrpt::utils::CStream &out, int *getVersion) const MRPT_OVERRIDE |
void | readFromStream (mrpt::utils::CStream &in, int version) MRPT_OVERRIDE |
RTTI stuff <br> | |
typedef CPointPDFGaussianPtr | SmartPtr |
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 MRPT_OVERRIDE |
virtual mrpt::utils::CObject * | duplicate () const MRPT_OVERRIDE |
static mrpt::utils::CObject * | CreateObject () |
static CPointPDFGaussianPtr | Create () |
A typedef for the associated smart pointer
Definition at line 29 of file CPointPDFGaussian.h.
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inherited |
The type of the state the PDF represents.
Definition at line 32 of file CProbabilityDensityFunction.h.
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Enumerator | |
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is_3D_val |
Definition at line 55 of file CPointPDF.h.
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Enumerator | |
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is_PDF_val |
Definition at line 57 of file CPointPDF.h.
mrpt::poses::CPointPDFGaussian::CPointPDFGaussian | ( | ) |
Default constructor.
mrpt::poses::CPointPDFGaussian::CPointPDFGaussian | ( | const CPoint3D & | init_Mean | ) |
Constructor.
mrpt::poses::CPointPDFGaussian::CPointPDFGaussian | ( | const CPoint3D & | init_Mean, |
const mrpt::math::CMatrixDouble33 & | init_Cov | ||
) |
Constructor.
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staticprotected |
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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!)
p1 | The first distribution to fuse |
p2 | The second distribution to fuse |
minMahalanobisDistToDrop | If 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.
void mrpt::poses::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:
S = (S1-1 + S2-1)-1; x = S * ( S1-1*x1 + S2-1*x2 );
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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 >.
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virtual |
Copy operator, translating if necesary (for example, between particles and gaussian representations)
Implements mrpt::poses::CPointPDF.
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static |
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static |
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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 117 of file CProbabilityDensityFunction.h.
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pure virtualinherited |
Draws a single sample from the distribution.
void mrpt::poses::CPointPDFGaussian::drawSingleSample | ( | CPoint3D & | outSample | ) | const |
Draw a sample from the pdf.
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virtual |
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inlineinherited |
Returns a 3D representation of this PDF.
Definition at line 73 of file CPointPDF.h.
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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)
Definition at line 64 of file CPointPDF.h.
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inlineinherited |
Returns the estimate of the covariance matrix (STATE_LEN x STATE_LEN covariance matrix)
Definition at line 85 of file CProbabilityDensityFunction.h.
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inlineinherited |
Returns the estimate of the covariance matrix (STATE_LEN x STATE_LEN covariance matrix)
Definition at line 67 of file CProbabilityDensityFunction.h.
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inlineinherited |
Returns the estimate of the covariance matrix (STATE_LEN x STATE_LEN covariance matrix)
Definition at line 76 of file CProbabilityDensityFunction.h.
void mrpt::poses::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.
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pure virtualinherited |
Returns an estimate of the pose covariance matrix (STATE_LENxSTATE_LEN cov matrix) and the mean, both at once.
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inlineinherited |
Returns an estimate of the pose covariance matrix (STATE_LENxSTATE_LEN cov matrix) and the mean, both at once.
Definition at line 47 of file CProbabilityDensityFunction.h.
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inlineinherited |
Compute the entropy of the estimated covariance matrix.
Definition at line 136 of file CProbabilityDensityFunction.h.
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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.
Definition at line 98 of file CProbabilityDensityFunction.h.
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pure virtualinherited |
Returns the mean, or mathematical expectation of the probability density distribution (PDF).
void mrpt::poses::CPointPDFGaussian::getMean | ( | CPoint3D & | p | ) | const |
Returns an estimate of the point, (the mean, or mathematical expectation of the PDF)
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inlineinherited |
Returns the mean, or mathematical expectation of the probability density distribution (PDF).
Definition at line 57 of file CProbabilityDensityFunction.h.
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virtual |
Reimplemented from mrpt::poses::CPointPDF.
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inlinestaticinherited |
Definition at line 56 of file CPointPDF.h.
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inlinestaticinherited |
Definition at line 58 of file CPointPDF.h.
double mrpt::poses::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)
double mrpt::poses::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
, with
std::exception | On errors like covariance matrix with null determinant, etc... |
double mrpt::poses::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
, with
std::exception | On errors like covariance matrix with null determinant, etc... |
double mrpt::poses::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.
std::exception | On errors like covariance matrix with null determinant, etc... |
double mrpt::poses::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!!
std::exception | On errors like covariance matrix with null determinant, etc... |
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protected |
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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 >.
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staticprotected |
Definition at line 29 of file CPointPDFGaussian.h.
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staticinherited |
Definition at line 40 of file CPointPDF.h.
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Definition at line 29 of file CPointPDFGaussian.h.
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static |
Definition at line 29 of file CPointPDFGaussian.h.
mrpt::math::CMatrixDouble33 mrpt::poses::CPointPDFGaussian::cov |
The 3x3 covariance matrix.
Definition at line 45 of file CPointPDFGaussian.h.
Referenced by mrpt::maps::CLandmark::getPose().
CPoint3D mrpt::poses::CPointPDFGaussian::mean |
The mean value.
Definition at line 44 of file CPointPDFGaussian.h.
Referenced by mrpt::maps::CLandmark::getPose().
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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.
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