MRPT
1.9.9
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A gaussian distribution for 3D points.
Also a method for bayesian fusion is provided.
Definition at line 23 of file CPointPDFGaussian.h.
#include <mrpt/poses/CPointPDFGaussian.h>
Public Types | |
enum | { is_3D_val = 1 } |
enum | { is_PDF_val = 1 } |
using | type_value = CPoint3D |
The type of the state the PDF represents. More... | |
using | self_t = CProbabilityDensityFunction< CPoint3D, STATE_LEN > |
Public Member Functions | |
void * | operator new (size_t size) |
void * | operator new[] (size_t size) |
void | operator delete (void *ptr) noexcept |
void | operator delete[] (void *ptr) noexcept |
void | operator delete (void *memory, void *ptr) noexcept |
void * | operator new (size_t size, const std::nothrow_t &) noexcept |
void | operator delete (void *ptr, const std::nothrow_t &) noexcept |
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 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 override |
Returns an estimate of the point covariance matrix (3x3 cov matrix) and the mean, both at once. More... | |
void | copyFrom (const CPointPDF &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 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 override |
Draw a sample from the pdf. More... | |
void | bayesianFusion (const CPointPDF &p1, const CPointPDF &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 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 mxArray * | writeToMatlab () 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 (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... | |
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 void * | operator new (size_t size, void *ptr) |
static constexpr bool | is_3D () |
static constexpr bool | is_PDF () |
Public Attributes | |
CPoint3D | mean |
The mean value. More... | |
mrpt::math::CMatrixDouble33 | cov |
The 3x3 covariance matrix. More... | |
Static Public Attributes | |
static constexpr 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< CPointPDFGaussian > |
using | ConstPtr = std::shared_ptr< const CPointPDFGaussian > |
using | UniquePtr = std::unique_ptr< CPointPDFGaussian > |
using | ConstUniquePtr = std::unique_ptr< const CPointPDFGaussian > |
static mrpt::rtti::CLASSINIT | _init_CPointPDFGaussian |
static const mrpt::rtti::TRuntimeClassId | runtimeClassId |
static constexpr const char * | className = "CPointPDFGaussian" |
static const mrpt::rtti::TRuntimeClassId * | _GetBaseClass () |
static constexpr auto | getClassName () |
static const mrpt::rtti::TRuntimeClassId & | GetRuntimeClassIdStatic () |
static mrpt::rtti::CObject * | CreateObject () |
template<typename... Args> | |
static Ptr | Create (Args &&... args) |
template<typename... Args> | |
static UniquePtr | CreateUnique (Args &&... args) |
virtual const mrpt::rtti::TRuntimeClassId * | GetRuntimeClass () const override |
Returns information about the class of an object in runtime. More... | |
virtual mrpt::rtti::CObject * | clone () const override |
Returns a deep copy (clone) of the object, indepently of its class. More... | |
using mrpt::poses::CPointPDFGaussian::ConstPtr = std::shared_ptr<const CPointPDFGaussian > |
Definition at line 25 of file CPointPDFGaussian.h.
using mrpt::poses::CPointPDFGaussian::ConstUniquePtr = std::unique_ptr<const CPointPDFGaussian > |
Definition at line 25 of file CPointPDFGaussian.h.
A type for the associated smart pointer
Definition at line 25 of file CPointPDFGaussian.h.
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inherited |
Definition at line 34 of file CProbabilityDensityFunction.h.
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inherited |
The type of the state the PDF represents.
Definition at line 33 of file CProbabilityDensityFunction.h.
using mrpt::poses::CPointPDFGaussian::UniquePtr = std::unique_ptr< CPointPDFGaussian > |
Definition at line 25 of file CPointPDFGaussian.h.
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inherited |
Enumerator | |
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is_3D_val |
Definition at line 65 of file CPointPDF.h.
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inherited |
Enumerator | |
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is_PDF_val |
Definition at line 70 of file CPointPDF.h.
CPointPDFGaussian::CPointPDFGaussian | ( | ) |
Default constructor.
Definition at line 30 of file CPointPDFGaussian.cpp.
CPointPDFGaussian::CPointPDFGaussian | ( | const CPoint3D & | init_Mean | ) |
CPointPDFGaussian::CPointPDFGaussian | ( | const CPoint3D & | init_Mean, |
const mrpt::math::CMatrixDouble33 & | init_Cov | ||
) |
Constructor.
Definition at line 34 of file CPointPDFGaussian.cpp.
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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:
S = (S1-1 + S2-1)-1; x = S * ( S1-1*x1 + S2-1*x2 );
Definition at line 137 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().
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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!)
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.
Definition at line 271 of file CPointPDFGaussian.cpp.
References ASSERT_, CLASS_ID, mrpt::poses::CPointPDF::GetRuntimeClass(), MRPT_END, MRPT_START, MRPT_UNUSED_PARAM, and THROW_EXCEPTION.
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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::CPointPDF.
Definition at line 122 of file CPointPDFGaussian.cpp.
References cov, mrpt::poses::CPose3D::getRotationMatrix(), and mean.
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overridevirtual |
Returns a deep copy (clone) of the object, indepently of its class.
Implements mrpt::rtti::CObject.
Copy operator, translating if necesary (for example, between particles and gaussian representations)
Implements mrpt::poses::CPointPDF.
Definition at line 94 of file CPointPDFGaussian.cpp.
References cov, mrpt::math::CProbabilityDensityFunction< TDATA, STATE_LEN >::getCovarianceAndMean(), and mean.
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inlinestatic |
Definition at line 25 of file CPointPDFGaussian.h.
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static |
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inlinestatic |
Definition at line 25 of file CPointPDFGaussian.h.
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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 152 of file CProbabilityDensityFunction.h.
Draw a sample from the pdf.
Definition at line 253 of file CPointPDFGaussian.cpp.
References ASSERT_, cov, mrpt::random::CRandomGenerator::drawGaussianMultivariate(), mrpt::random::getRandomGenerator(), mean, MRPT_END, MRPT_START, mrpt::poses::CPoseOrPoint< DERIVEDCLASS >::x(), and mrpt::poses::CPoseOrPoint< DERIVEDCLASS >::y().
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pure virtualinherited |
Draws a single sample from the distribution.
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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 168 of file CObject.h.
References mrpt::rtti::CObject::clone().
Referenced by mrpt::obs::CRawlog::addActions(), and mrpt::obs::CRawlog::addObservations().
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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 84 of file CPointPDF.h.
References mrpt::opengl::posePDF2opengl().
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inlineinherited |
Returns a 3D representation of this PDF.
Definition at line 95 of file CPointPDF.h.
References mrpt::opengl::posePDF2opengl().
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inlinestatic |
Definition at line 25 of file CPointPDFGaussian.h.
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inlineinherited |
Returns the estimate of the covariance matrix (STATE_LEN x STATE_LEN covariance matrix)
Definition at line 78 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 88 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 101 of file CProbabilityDensityFunction.h.
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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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override |
Returns an estimate of the point covariance matrix (3x3 cov matrix) and the mean, both at once.
Definition at line 58 of file CPointPDFGaussian.cpp.
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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 54 of file CProbabilityDensityFunction.h.
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inlineinherited |
Compute the entropy of the estimated covariance matrix.
Definition at line 168 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 124 of file CProbabilityDensityFunction.h.
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pure virtualinherited |
Returns the mean, or mathematical expectation of the probability density distribution (PDF).
Returns an estimate of the point, (the mean, or mathematical expectation of the PDF)
Definition at line 54 of file CPointPDFGaussian.cpp.
References mean.
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inlineinherited |
Returns the mean, or mathematical expectation of the probability density distribution (PDF).
Definition at line 67 of file CProbabilityDensityFunction.h.
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overridevirtual |
Returns information about the class of an object in runtime.
Reimplemented from mrpt::poses::CPointPDF.
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static |
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inlinestaticinherited |
Definition at line 69 of file CPointPDF.h.
References mrpt::poses::CPointPDF::is_3D_val.
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inlinestaticinherited |
Definition at line 74 of file CPointPDF.h.
References mrpt::poses::CPointPDF::is_PDF_val.
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inlinevirtualinherited |
Returns whether the class instance holds the uncertainty in covariance or information form.
Definition at line 117 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 290 of file CPointPDFGaussian.cpp.
References cov, mean, mrpt::poses::CPoseOrPoint< DERIVEDCLASS >::x(), and mrpt::poses::CPoseOrPoint< DERIVEDCLASS >::y().
Referenced by productIntegralNormalizedWith(), and productIntegralNormalizedWith2D().
Definition at line 25 of file CPointPDFGaussian.h.
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inlinenoexcept |
Definition at line 25 of file CPointPDFGaussian.h.
Definition at line 25 of file CPointPDFGaussian.h.
Definition at line 25 of file CPointPDFGaussian.h.
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inline |
Definition at line 25 of file CPointPDFGaussian.h.
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inlinenoexcept |
Definition at line 25 of file CPointPDFGaussian.h.
Definition at line 25 of file CPointPDFGaussian.h.
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inline |
Definition at line 25 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
, with being the square Mahalanobis distance between the two pdfs.
std::exception | On errors like covariance matrix with null determinant, etc... |
Definition at line 235 of file CPointPDFGaussian.cpp.
References mahalanobisDistanceTo(), and mrpt::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
, with being the square Mahalanobis distance between the two pdfs.
std::exception | On errors like covariance matrix with null determinant, etc... |
Definition at line 244 of file CPointPDFGaussian.cpp.
References mahalanobisDistanceTo(), and mrpt::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.
std::exception | On errors like covariance matrix with null determinant, etc... |
Definition at line 175 of file CPointPDFGaussian.cpp.
References cov, M_2PI, mean, MRPT_END, MRPT_START, mrpt::math::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!!
std::exception | On errors like covariance matrix with null determinant, etc... |
Definition at line 204 of file CPointPDFGaussian.cpp.
References cov, M_2PI, mean, MRPT_END, MRPT_START, mrpt::math::CProbabilityDensityFunction< CPoint3D, 3 >::state_length, mrpt::math::UNINITIALIZED_MATRIX, mrpt::poses::CPoseOrPoint< DERIVEDCLASS >::x(), and mrpt::poses::CPoseOrPoint< DERIVEDCLASS >::y().
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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< CPoint3D, 3 >.
Definition at line 105 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().
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overrideprotectedvirtual |
Pure virtual method for reading (deserializing) from an abstract archive.
Users don't call this method directly. Instead, use stream >> object;
.
in | The input binary stream where the object data must read from. |
version | The version of the object stored in the stream: use this version number in your code to know how to read the incoming data. |
std::exception | On any I/O error |
Implements mrpt::serialization::CSerializable.
Definition at line 70 of file CPointPDFGaussian.cpp.
References cov, mean, and MRPT_THROW_UNKNOWN_SERIALIZATION_VERSION.
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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 65 of file CPointPDFGaussian.cpp.
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overrideprotectedvirtual |
Pure virtual method for writing (serializing) to an abstract archive.
Users don't call this method directly. Instead, use stream << object;
.
std::exception | On any I/O error |
Implements mrpt::serialization::CSerializable.
Definition at line 66 of file CPointPDFGaussian.cpp.
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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.
mxArray
(caller is responsible of memory freeing) or nullptr is class does not support conversion to MATLAB. Definition at line 68 of file CSerializable.h.
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staticprotected |
Definition at line 25 of file CPointPDFGaussian.h.
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static |
Definition at line 25 of file CPointPDFGaussian.h.
mrpt::math::CMatrixDouble33 mrpt::poses::CPointPDFGaussian::cov |
The 3x3 covariance matrix.
Definition at line 44 of file CPointPDFGaussian.h.
Referenced by bayesianFusion(), mrpt::poses::CPointPDFSOG::bayesianFusion(), changeCoordinatesReference(), mrpt::maps::CLandmarksMap::computeLikelihood_SIFT_LandmarkMap(), mrpt::maps::CLandmarksMap::computeMatchingWith3DLandmarks(), copyFrom(), CPointPDFGaussian(), drawSingleSample(), mrpt::maps::CBeacon::generateRingSOG(), mrpt::slam::CRangeBearingKFSLAM::getAs3DObject(), mrpt::maps::CLandmarksMap::getAs3DObject(), getCovarianceAndMean(), mrpt::maps::CLandmark::getPose(), mrpt::maps::CBeaconMap::internal_computeObservationLikelihood(), mrpt::maps::CBeaconMap::internal_insertObservation(), mrpt::maps::CLandmarksMap::loadSiftFeaturesFromImageObservation(), mahalanobisDistanceTo(), mrpt::maps::CMultiMetricMapPDF::prediction_and_update_pfOptimalProposal(), productIntegralWith(), productIntegralWith2D(), saveToTextFile(), serializeFrom(), serializeTo(), and mrpt::maps::CLandmark::setPose().
CPoint3D mrpt::poses::CPointPDFGaussian::mean |
The mean value.
Definition at line 42 of file CPointPDFGaussian.h.
Referenced by bayesianFusion(), mrpt::poses::CPointPDFSOG::bayesianFusion(), changeCoordinatesReference(), mrpt::maps::CLandmarksMap::computeMatchingWith3DLandmarks(), copyFrom(), drawSingleSample(), mrpt::maps::CBeacon::generateRingSOG(), mrpt::slam::CRangeBearingKFSLAM::getAs3DObject(), mrpt::maps::CLandmarksMap::getAs3DObject(), getCovarianceAndMean(), getMean(), mrpt::maps::CLandmark::getPose(), mrpt::maps::CBeaconMap::internal_computeObservationLikelihood(), mrpt::maps::CLandmarksMap::internal_computeObservationLikelihood(), mrpt::maps::CBeaconMap::internal_insertObservation(), mrpt::maps::CLandmarksMap::loadSiftFeaturesFromImageObservation(), mahalanobisDistanceTo(), mrpt::maps::CMultiMetricMapPDF::prediction_and_update_pfOptimalProposal(), productIntegralWith(), productIntegralWith2D(), saveToTextFile(), serializeFrom(), serializeTo(), mrpt::maps::CLandmark::setPose(), mrpt::maps::CLandmarksMap::simulateBeaconReadings(), and mrpt::maps::CLandmarksMap::simulateRangeBearingReadings().
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staticprotected |
Definition at line 25 of file CPointPDFGaussian.h.
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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.
Referenced by productIntegralWith(), and productIntegralWith2D().
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