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CPointPDFSOG.h
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1 /* +---------------------------------------------------------------------------+
2  | Mobile Robot Programming Toolkit (MRPT) |
3  | http://www.mrpt.org/ |
4  | |
5  | Copyright (c) 2005-2017, Individual contributors, see AUTHORS file |
6  | See: http://www.mrpt.org/Authors - All rights reserved. |
7  | Released under BSD License. See details in http://www.mrpt.org/License |
8  +---------------------------------------------------------------------------+ */
9 #ifndef CPointPDFSOG_H
10 #define CPointPDFSOG_H
11 
12 #include <mrpt/poses/CPointPDF.h>
14 #include <mrpt/math/CMatrix.h>
15 #include <mrpt/math/CMatrixD.h>
16 
17 namespace mrpt
18 {
19  namespace poses
20  {
21  DEFINE_SERIALIZABLE_PRE_CUSTOM_BASE( CPointPDFSOG, CPointPDF )
22 
23  /** Declares a class that represents a Probability Density function (PDF) of a 3D point \f$ p(\mathbf{x}) = [x ~ y ~ z ]^t \f$.
24  * This class implements that PDF as the following multi-modal Gaussian distribution:
25  *
26  * \f$ p(\mathbf{x}) = \sum\limits_{i=1}^N \omega^i \mathcal{N}( \mathbf{x} ; \bar{\mathbf{x}}^i, \mathbf{\Sigma}^i ) \f$
27  *
28  * Where the number of modes N is the size of CPointPDFSOG::m_modes
29  *
30  * See mrpt::poses::CPointPDF for more details.
31  *
32  * \sa CPointPDF, CPosePDF,
33  * \ingroup poses_pdf_grp
34  */
36  {
37  // This must be added to any CSerializable derived class:
39 
40  public:
41  /** The struct for each mode:
42  */
44  {
45  TGaussianMode() : val(), log_w(0)
46  {
47  }
48 
50 
51  /** The log-weight
52  */
53  double log_w;
54  };
55 
56  typedef std::deque<TGaussianMode> CListGaussianModes;
59 
60  protected:
61  /** Assures the symmetry of the covariance matrix (eventually certain operations in the math-coprocessor lead to non-symmetric matrixes!)
62  */
63  void assureSymmetry();
64 
65  /** The list of SOG modes */
67 
68  public:
69  /** Default constructor
70  * \param nModes The initial size of CPointPDFSOG::m_modes
71  */
72  CPointPDFSOG( size_t nModes = 1 );
73 
74  void clear(); //!< Clear all the gaussian modes
75 
76  /** Access to individual beacons */
77  const TGaussianMode& operator [](size_t i) const {
78  ASSERT_(i<m_modes.size())
79  return m_modes[i];
80  }
81  /** Access to individual beacons */
83  ASSERT_(i<m_modes.size())
84  return m_modes[i];
85  }
86 
87  /** Access to individual beacons */
88  const TGaussianMode& get(size_t i) const {
89  ASSERT_(i<m_modes.size())
90  return m_modes[i];
91  }
92  /** Access to individual beacons */
93  TGaussianMode& get(size_t i) {
94  ASSERT_(i<m_modes.size())
95  return m_modes[i];
96  }
97 
98  /** Inserts a copy of the given mode into the SOG */
99  void push_back(const TGaussianMode& m) {
100  m_modes.push_back(m);
101  }
102 
103  iterator begin() { return m_modes.begin(); }
104  iterator end() { return m_modes.end(); }
105  const_iterator begin() const { return m_modes.begin(); }
106  const_iterator end()const { return m_modes.end(); }
107 
108  iterator erase(iterator i) { return m_modes.erase(i); }
109 
110  void resize(const size_t N); //!< Resize the number of SOG modes
111  size_t size() const { return m_modes.size(); } //!< Return the number of Gaussian modes.
112  bool empty() const { return m_modes.empty(); } //!< Return whether there is any Gaussian mode.
113 
114  /** Returns an estimate of the point, (the mean, or mathematical expectation of the PDF) \sa getCovariance */
115  void getMean(CPoint3D &mean_point) const MRPT_OVERRIDE;
116 
117  /** Returns an estimate of the point covariance matrix (3x3 cov matrix) and the mean, both at once. \sa getMean */
118  void getCovarianceAndMean(mrpt::math::CMatrixDouble33 &cov,CPoint3D &mean_point) const MRPT_OVERRIDE;
119 
120  /** Normalize the weights in m_modes such as the maximum log-weight is 0 */
121  void normalizeWeights();
122 
123  /** Return the Gaussian mode with the highest likelihood (or an empty Gaussian if there are no modes in this SOG) */
124  void getMostLikelyMode( CPointPDFGaussian& outVal ) const;
125 
126  /** Computes the "Effective sample size" (typical measure for Particle Filters), applied to the weights of the individual Gaussian modes, as a measure of the equality of the modes (in the range [0,total # of modes]). */
127  double ESS() const;
128 
129  void copyFrom(const CPointPDF &o) MRPT_OVERRIDE; //!< Copy operator, translating if necesary (for example, between particles and gaussian representations)
130 
131  /** Save the density to a text file, with the following format:
132  * There is one row per Gaussian "mode", and each row contains 10 elements:
133  * - w (The weight)
134  * - x_mean (gaussian mean value)
135  * - y_mean (gaussian mean value)
136  * - x_mean (gaussian mean value)
137  * - C11 (Covariance elements)
138  * - C22 (Covariance elements)
139  * - C33 (Covariance elements)
140  * - C12 (Covariance elements)
141  * - C13 (Covariance elements)
142  * - C23 (Covariance elements)
143  *
144  */
145  void saveToTextFile(const std::string &file) const MRPT_OVERRIDE;
146 
147  /** this = p (+) this. This can be used to convert a PDF from local coordinates to global, providing the point (newReferenceBase) from which
148  * "to project" the current pdf. Result PDF substituted the currently stored one in the object. */
149  void changeCoordinatesReference(const CPose3D &newReferenceBase ) MRPT_OVERRIDE;
150 
151  /** Draw a sample from the pdf. */
152  void drawSingleSample(CPoint3D &outSample) const MRPT_OVERRIDE;
153 
154  /** 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!)
155  * \param p1 The first distribution to fuse
156  * \param p2 The second distribution to fuse
157  * \param 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.
158  */
159  void bayesianFusion( const CPointPDF &p1, const CPointPDF &p2, const double &minMahalanobisDistToDrop = 0) MRPT_OVERRIDE;
160 
161 
162  /** Evaluates the PDF within a rectangular grid and saves the result in a matrix (each row contains values for a fixed y-coordinate value).
163  */
164  void evaluatePDFInArea(
165  float x_min,
166  float x_max,
167  float y_min,
168  float y_max,
169  float resolutionXY,
170  float z,
171  mrpt::math::CMatrixD &outMatrix,
172  bool sumOverAllZs = false );
173 
174  /** Evaluates the PDF at a given point */
175  double evaluatePDF( const CPoint3D &x, bool sumOverAllZs ) const;
176 
177  }; // End of class def.
179  } // End of namespace
180 } // End of namespace
181 #endif
DEFINE_SERIALIZABLE_POST_CUSTOM_BASE(CPose3DPDFGaussianInf, CPose3DPDF)
GLdouble GLdouble z
Definition: glext.h:3734
#define MRPT_OVERRIDE
C++11 "override" for virtuals:
std::deque< TGaussianMode > CListGaussianModes
Definition: CPointPDFSOG.h:56
Declares a class that represents a Probability Density function (PDF) of a 3D point ...
Definition: CPointPDFSOG.h:35
The struct for each mode:
Definition: CPointPDFSOG.h:43
Scalar * iterator
Definition: eigen_plugins.h:23
void saveToTextFile(const std::string &file, mrpt::math::TMatrixTextFileFormat fileFormat=mrpt::math::MATRIX_FORMAT_ENG, bool appendMRPTHeader=false, const std::string &userHeader=std::string()) const
Save matrix to a text file, compatible with MATLAB text format (see also the methods of matrix classe...
const Scalar * const_iterator
Definition: eigen_plugins.h:24
void clear()
Clear the contents of this container.
Definition: ts_hash_map.h:113
bool empty() const
Return whether there is any Gaussian mode.
Definition: CPointPDFSOG.h:112
Eigen::Matrix< typename MATRIX::Scalar, MATRIX::ColsAtCompileTime, MATRIX::ColsAtCompileTime > cov(const MATRIX &v)
Computes the covariance matrix from a list of samples in an NxM matrix, where each row is a sample...
Definition: ops_matrices.h:135
void push_back(const TGaussianMode &m)
Inserts a copy of the given mode into the SOG.
Definition: CPointPDFSOG.h:99
std::deque< TGaussianMode >::const_iterator const_iterator
Definition: CPointPDFSOG.h:57
VALUE & operator[](const KEY &key)
Write/read via [i] operator, that creates an element if it didn&#39;t exist already.
Definition: ts_hash_map.h:123
int val
Definition: mrpt_jpeglib.h:953
#define DEFINE_SERIALIZABLE_PRE_CUSTOM_BASE(class_name, base_name)
This declaration must be inserted in all CSerializable classes definition, before the class declarati...
GLsizei const GLchar ** string
Definition: glext.h:3919
A class used to store a 3D point.
Definition: CPoint3D.h:32
iterator erase(iterator i)
Definition: CPointPDFSOG.h:108
This is the global namespace for all Mobile Robot Programming Toolkit (MRPT) libraries.
#define DEFINE_SERIALIZABLE(class_name)
This declaration must be inserted in all CSerializable classes definition, within the class declarati...
A class used to store a 3D pose (a 3D translation + a rotation in 3D).
Definition: CPose3D.h:72
size_t size() const
Return the number of Gaussian modes.
Definition: CPointPDFSOG.h:111
const_iterator begin() const
Definition: CPointPDFSOG.h:105
const_iterator end() const
Definition: CPointPDFSOG.h:106
#define ASSERT_(f)
std::deque< TGaussianMode >::iterator iterator
Definition: CPointPDFSOG.h:58
GLenum GLint x
Definition: glext.h:3516
Declares a class that represents a Probability Distribution function (PDF) of a 3D point (x...
Definition: CPointPDF.h:38
CListGaussianModes m_modes
The list of SOG modes.
Definition: CPointPDFSOG.h:66
A gaussian distribution for 3D points.



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