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//##########################################################################
//# #
//# CCLIB #
//# #
//# This program is free software; you can redistribute it and/or modify #
//# it under the terms of the GNU Library General Public License as #
//# published by the Free Software Foundation; version 2 or later of the #
//# License. #
//# #
//# This program is distributed in the hope that it will be useful, #
//# but WITHOUT ANY WARRANTY; without even the implied warranty of #
//# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the #
//# GNU General Public License for more details. #
//# #
//# COPYRIGHT: EDF R&D / TELECOM ParisTech (ENST-TSI) #
//# #
//##########################################################################
#ifndef NORMAL_DISTRIBUTION_HEADER
#define NORMAL_DISTRIBUTION_HEADER
//Local
#include "GenericDistribution.h"
namespace CCLib
{
//! The Normal/Gaussian statistical distribution
/** Implements the GenericDistribution interface.
**/
class CC_CORE_LIB_API NormalDistribution : public GenericDistribution
{
public:
//! NormalDistribution constructor
NormalDistribution();
//! NormalDistribution constructor
/** Distrubtion parameters can be directly set during object
construction.
\param _mu the normal distribution mean
\param _sigma2 the normal distribution variance
**/
NormalDistribution(ScalarType _mu, ScalarType _sigma2);
//inherited methods (see GenericDistribution)
bool computeParameters(const ScalarContainer& values) override;
double computeP(ScalarType x) const override;
double computePfromZero(ScalarType x) const override;
double computeP(ScalarType x1, ScalarType x2) const override;
double computeChi2Dist(const GenericCloud* Yk, unsigned numberOfClasses, int* histo = nullptr) override;
const char* getName() const override { return "Gauss"; }
//! Returns the distribution parameters
/** \param _mu a field to transmit the distribution mean
\param _sigma2 a field to transmit the distribution variance
return the parameters validity
**/
bool getParameters(ScalarType &_mu, ScalarType &_sigma2) const;
//! Sets the distribution parameters
/** \param _mu the distribution mean
\param _sigma2 the distribution variance
return the parameters validity
**/
bool setParameters(ScalarType _mu, ScalarType _sigma2);
//! Returns the distribution mean
inline ScalarType getMu() const { return m_mu; }
//! Returns the distribution variance
inline ScalarType getSigma2() const { return m_sigma2; }
//! Computes the distribution parameters from a point cloud (with scalar values)
bool computeParameters(const GenericCloud* cloud);
//! Computes robust parameters for the distribution from an array of scalar values
/** Specific method to compute the parameters directly from an array
(vector) of scalar values, without associated points. After a first pass,
only the values close enough to the mean (in terms of nSigma times the initial
variance) are kept to make a second and more robust evaluation of the parameters.
\param values the scalar values
\param nSigma the values filtering interval size ([mu -nSigma * stddev : mu + nSigma * stddev])
\return the validity of the computed parameters
**/
bool computeRobustParameters(const ScalarContainer& values, double nSigma);
protected:
//! Compute each Chi2 class limits
/** This method is used (internally) to accelerate the Chi2 distance computation.
\param numberOfClasses the number of classes that will be used for Chi2 distance computation
\return success
**/
virtual bool setChi2ClassesPositions(unsigned numberOfClasses);
//! Mean
ScalarType m_mu;
//! Variance
ScalarType m_sigma2;
//! Exponential quotient
double m_qFactor;
//! Normalization factor
double m_normFactor;
//! Chi2 classes limits
/** Used internally. Stores both limits for each class in a vector
(min_class_1, max_class_1, min_class_2, max_class_2, etc.).
**/
std::vector<ScalarType> m_chi2ClassesPositions;
//! Structure used during the Chi2 distance computation
std::vector<ScalarType> m_Pi;
};
}
#endif //NORMAL_DISTRIBUTION_HEADER
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