A Probability Density function (PDF) of a 2D pose
This class implements a PDF as a mono-modal Gaussian distribution in its information form, that is, keeping the inverse of the covariance matrix instead of the covariance matrix itself.
This class is the dual of CPosePDFGaussian.
Definition at line 34 of file CPosePDFGaussianInf.h.
#include <mrpt/poses/CPosePDFGaussianInf.h>
Public Types | |
enum | { is_3D_val = 0 } |
enum | { is_PDF_val = 1 } |
typedef CPose2D | type_value |
The type of the state the PDF represents. More... | |
Public Member Functions | |
const CPose2D & | getPoseMean () const |
CPose2D & | getPoseMean () |
CPosePDFGaussianInf () | |
Default constructor (mean=all zeros, inverse covariance=all zeros -> so be careful!) More... | |
CPosePDFGaussianInf (const CPose2D &init_Mean) | |
Constructor with a mean value (inverse covariance=all zeros -> so be careful!) More... | |
CPosePDFGaussianInf (const CPose2D &init_Mean, const mrpt::math::CMatrixDouble33 &init_CovInv) | |
Constructor. More... | |
CPosePDFGaussianInf (const CPosePDF &o) | |
Copy constructor, including transformations between other PDFs. More... | |
CPosePDFGaussianInf (const CPose3DPDF &o) | |
Copy constructor, including transformations between other PDFs. More... | |
void | getMean (CPose2D &mean_pose) const MRPT_OVERRIDE |
Returns an estimate of the pose, (the mean, or mathematical expectation of the PDF). More... | |
void | getCovarianceAndMean (mrpt::math::CMatrixDouble33 &cov, CPose2D &mean_point) const MRPT_OVERRIDE |
Returns an estimate of the pose covariance matrix (3x3 cov matrix) and the mean, both at once. More... | |
virtual void | getInformationMatrix (mrpt::math::CMatrixDouble33 &inf) const MRPT_OVERRIDE |
Returns the information (inverse covariance) matrix (a STATE_LEN x STATE_LEN matrix) More... | |
void | copyFrom (const CPosePDF &o) MRPT_OVERRIDE |
Copy operator, translating if necesary (for example, between particles and gaussian representations) More... | |
void | copyFrom (const CPose3DPDF &o) |
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 | changeCoordinatesReference (const CPose2D &newReferenceBase) |
this = p (+) this. More... | |
void | rotateCov (const double ang) |
Rotate the covariance matrix by replacing it by ![]() ![]() | |
void | inverseComposition (const CPosePDFGaussianInf &x, const CPosePDFGaussianInf &ref) |
Set ![]() | |
void | inverseComposition (const CPosePDFGaussianInf &x1, const CPosePDFGaussianInf &x0, const mrpt::math::CMatrixDouble33 &COV_01) |
Set ![]() | |
void | drawSingleSample (CPose2D &outPart) const MRPT_OVERRIDE |
Draws a single sample from the distribution. More... | |
void | drawManySamples (size_t N, std::vector< mrpt::math::CVectorDouble > &outSamples) const MRPT_OVERRIDE |
Draws a number of samples from the distribution, and saves as a list of 1x3 vectors, where each row contains a (x,y,phi) datum. More... | |
void | bayesianFusion (const CPosePDF &p1, const CPosePDF &p2, const double &minMahalanobisDistToDrop=0) MRPT_OVERRIDE |
Bayesian fusion of two points gauss. More... | |
void | inverse (CPosePDF &o) const MRPT_OVERRIDE |
Returns a new PDF such as: NEW_PDF = (0,0,0) - THIS_PDF. More... | |
void | operator+= (const CPose2D &Ap) |
Makes: thisPDF = thisPDF + Ap, where "+" is pose composition (both the mean, and the covariance matrix are updated). More... | |
double | evaluatePDF (const CPose2D &x) const |
Evaluates the PDF at a given point. More... | |
double | evaluateNormalizedPDF (const CPose2D &x) const |
Evaluates the ratio PDF(x) / PDF(MEAN), that is, the normalized PDF in the range [0,1]. More... | |
double | mahalanobisDistanceTo (const CPosePDFGaussianInf &theOther) |
Computes the Mahalanobis distance between the centers of two Gaussians. More... | |
void | operator+= (const CPosePDFGaussianInf &Ap) |
Makes: thisPDF = thisPDF + Ap, where "+" is pose composition (both the mean, and the covariance matrix are updated) (see formulas in jacobiansPoseComposition ). More... | |
void | operator-= (const CPosePDFGaussianInf &ref) |
Makes: thisPDF = thisPDF - Ap, where "-" is pose inverse composition (both the mean, and the covariance matrix are updated) 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 > | |
OPENGL_SETOFOBJECTSPTR | getAs3DObject () const |
Returns a 3D representation of this PDF. More... | |
virtual void | getMean (CPose2D &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, CPose2D &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, CPose2D &mean_point) const |
Returns an estimate of the pose covariance matrix (STATE_LENxSTATE_LEN cov matrix) and the mean, both at once. More... | |
CPose2D | 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 (CPose2D &outPart) const=0 |
Draws a single sample from the distribution. More... | |
double | getCovarianceEntropy () const |
Compute the entropy of the estimated covariance matrix. More... | |
Static Public Member Functions | |
static void | jacobiansPoseComposition (const CPose2D &x, const CPose2D &u, mrpt::math::CMatrixDouble33 &df_dx, mrpt::math::CMatrixDouble33 &df_du, const bool compute_df_dx=true, const bool compute_df_du=true) |
This static method computes the pose composition Jacobians, with these formulas: More... | |
static void | jacobiansPoseComposition (const CPosePDFGaussian &x, const CPosePDFGaussian &u, mrpt::math::CMatrixDouble33 &df_dx, mrpt::math::CMatrixDouble33 &df_du) |
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts. More... | |
static bool | is_3D () |
static bool | is_PDF () |
Public Attributes | |
Data fields | |
CPose2D | mean |
The mean value. More... | |
mrpt::math::CMatrixDouble33 | cov_inv |
The inverse of the 3x3 covariance matrix (the "information" 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 | classCPosePDF |
Protected Member Functions | |
void | assureSymmetry () |
Assures the symmetry of the covariance matrix (eventually certain operations in the math-coprocessor lead to non-symmetric matrixes!) More... | |
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 CPosePDFGaussianInfPtr | SmartPtr |
static mrpt::utils::CLASSINIT | _init_CPosePDFGaussianInf |
static mrpt::utils::TRuntimeClassId | classCPosePDFGaussianInf |
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 CPosePDFGaussianInfPtr | Create () |
A typedef for the associated smart pointer
Definition at line 37 of file CPosePDFGaussianInf.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 91 of file CPosePDF.h.
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Enumerator | |
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is_PDF_val |
Definition at line 93 of file CPosePDF.h.
mrpt::poses::CPosePDFGaussianInf::CPosePDFGaussianInf | ( | ) |
Default constructor (mean=all zeros, inverse covariance=all zeros -> so be careful!)
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explicit |
Constructor with a mean value (inverse covariance=all zeros -> so be careful!)
mrpt::poses::CPosePDFGaussianInf::CPosePDFGaussianInf | ( | const CPose2D & | init_Mean, |
const mrpt::math::CMatrixDouble33 & | init_CovInv | ||
) |
Constructor.
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inlineexplicit |
Copy constructor, including transformations between other PDFs.
Definition at line 66 of file CPosePDFGaussianInf.h.
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inlineexplicit |
Copy constructor, including transformations between other PDFs.
Definition at line 69 of file CPosePDFGaussianInf.h.
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staticprotected |
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protected |
Assures the symmetry of the covariance matrix (eventually certain operations in the math-coprocessor lead to non-symmetric matrixes!)
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virtual |
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 );
Implements mrpt::poses::CPosePDF.
void mrpt::poses::CPosePDFGaussianInf::changeCoordinatesReference | ( | const CPose2D & | newReferenceBase | ) |
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.
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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
Implements mrpt::utils::CProbabilityDensityFunction< CPose2D, 3 >.
void mrpt::poses::CPosePDFGaussianInf::copyFrom | ( | const CPose3DPDF & | o | ) |
Copy operator, translating if necesary (for example, between particles and gaussian representations)
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virtual |
Copy operator, translating if necesary (for example, between particles and gaussian representations)
Implements mrpt::poses::CPosePDF.
Referenced by mrpt::graphs::detail::graph_ops< graph_t >::write_EDGE_line().
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static |
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Draws a number of samples from the distribution, and saves as a list of 1x3 vectors, where each row contains a (x,y,phi) datum.
Reimplemented from mrpt::utils::CProbabilityDensityFunction< CPose2D, 3 >.
void mrpt::poses::CPosePDFGaussianInf::drawSingleSample | ( | CPose2D & | outPart | ) | const |
Draws a single sample from the distribution.
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pure virtualinherited |
Draws a single sample from the distribution.
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virtual |
double mrpt::poses::CPosePDFGaussianInf::evaluateNormalizedPDF | ( | const CPose2D & | x | ) | const |
Evaluates the ratio PDF(x) / PDF(MEAN), that is, the normalized PDF in the range [0,1].
double mrpt::poses::CPosePDFGaussianInf::evaluatePDF | ( | const CPose2D & | x | ) | const |
Evaluates the PDF at a given point.
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inlineinherited |
Returns a 3D representation of this PDF.
Definition at line 109 of file CPosePDF.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 100 of file CPosePDF.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.
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inline |
Returns an estimate of the pose covariance matrix (3x3 cov matrix) and the mean, both at once.
Definition at line 79 of file CPosePDFGaussianInf.h.
References mean().
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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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inlinevirtual |
Returns the information (inverse covariance) matrix (a STATE_LEN x STATE_LEN matrix)
Definition at line 85 of file CPosePDFGaussianInf.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).
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inline |
Returns an estimate of the pose, (the mean, or mathematical expectation of the PDF).
Definition at line 73 of file CPosePDFGaussianInf.h.
References mean().
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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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Definition at line 54 of file CPosePDFGaussianInf.h.
References mean().
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Definition at line 53 of file CPosePDFGaussianInf.h.
References mean().
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Reimplemented from mrpt::poses::CPosePDF.
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Returns a new PDF such as: NEW_PDF = (0,0,0) - THIS_PDF.
Implements mrpt::poses::CPosePDF.
void mrpt::poses::CPosePDFGaussianInf::inverseComposition | ( | const CPosePDFGaussianInf & | x, |
const CPosePDFGaussianInf & | ref | ||
) |
Set
void mrpt::poses::CPosePDFGaussianInf::inverseComposition | ( | const CPosePDFGaussianInf & | x1, |
const CPosePDFGaussianInf & | x0, | ||
const mrpt::math::CMatrixDouble33 & | COV_01 | ||
) |
Set
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inlinestaticinherited |
Definition at line 92 of file CPosePDF.h.
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inlinestaticinherited |
Definition at line 94 of file CPosePDF.h.
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staticinherited |
This static method computes the pose composition Jacobians, with these formulas:
Referenced by mrpt::math::jacobians::jacobs_2D_pose_comp().
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staticinherited |
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
double mrpt::poses::CPosePDFGaussianInf::mahalanobisDistanceTo | ( | const CPosePDFGaussianInf & | theOther | ) |
Computes the Mahalanobis distance between the centers of two Gaussians.
void mrpt::poses::CPosePDFGaussianInf::operator+= | ( | const CPose2D & | Ap | ) |
Makes: thisPDF = thisPDF + Ap, where "+" is pose composition (both the mean, and the covariance matrix are updated).
void mrpt::poses::CPosePDFGaussianInf::operator+= | ( | const CPosePDFGaussianInf & | Ap | ) |
Makes: thisPDF = thisPDF + Ap, where "+" is pose composition (both the mean, and the covariance matrix are updated) (see formulas in jacobiansPoseComposition ).
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inline |
Makes: thisPDF = thisPDF - Ap, where "-" is pose inverse composition (both the mean, and the covariance matrix are updated)
Definition at line 153 of file CPosePDFGaussianInf.h.
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void mrpt::poses::CPosePDFGaussianInf::rotateCov | ( | const double | ang | ) |
Rotate the covariance matrix by replacing it by
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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< CPose2D, 3 >.
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staticprotected |
Definition at line 37 of file CPosePDFGaussianInf.h.
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Definition at line 41 of file CPosePDF.h.
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Definition at line 37 of file CPosePDFGaussianInf.h.
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Definition at line 37 of file CPosePDFGaussianInf.h.
mrpt::math::CMatrixDouble33 mrpt::poses::CPosePDFGaussianInf::cov_inv |
The inverse of the 3x3 covariance matrix (the "information" matrix)
Definition at line 49 of file CPosePDFGaussianInf.h.
Referenced by mrpt::graphs::detail::graph_ops< graph_t >::auxMaha2Dist(), and mrpt::graphs::detail::graph_ops< graph_t >::write_EDGE_line().
CPose2D mrpt::poses::CPosePDFGaussianInf::mean |
The mean value.
Definition at line 48 of file CPosePDFGaussianInf.h.
Referenced by mrpt::graphs::detail::TPosePDFHelper< CPose2D >::copyFrom2D(), mrpt::graphs::detail::TPosePDFHelper< CPose3D >::copyFrom2D(), and mrpt::graphs::detail::graph_ops< graph_t >::write_EDGE_line().
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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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