#include <PCA.hpp>

Inheritance diagram for PCA:

Public Member Functions
	PCA (int nvar=0)

	PCA (const Db *db, bool verbose=false)

	PCA (Db *db, double h0, double dh, const DirParam &dirparam=DirParam(), bool verbose=false)

	PCA (const PCA &m)

PCA &	operator= (const PCA &m)

virtual	~PCA ()

virtual String	toString (const AStringFormat *strfmt=nullptr) const override
	Interface for AStringable. More...

void	init (int nvar)

const VectorDouble &	getEigens () const

double	getEigen (int ivar) const

VectorDouble	getVarianceRatio () const

const VectorDouble &	getMeans () const

double	getMean (int ivar) const

int	getNVar () const

const VectorDouble &	getF2Z () const

double	getF2Z (int ivar, int jvar) const

const VectorDouble &	getZ2F () const

double	getZ2F (int ivar, int jvar) const

const VectorDouble &	getSigmas () const

double	getSigma (int ivar) const

void	setPcaZ2F (const VectorDouble &pcaz2f)

void	setPcaZ2F (int ivar, int jvar, double pcaz2f)

void	setPcaF2Z (VectorDouble &pcaf2z)

void	setEigen (VectorDouble &eigen)

void	setEigen (int ivar, double eigen)

void	setMean (const VectorDouble &mean)

void	setSigma (const VectorDouble &sigma)

int	pca_compute (const Db *db, bool verbose=false)

int	maf_compute (Db *db, double h0, double dh, const DirParam &dirparam, bool verbose=false)

int	dbZ2F (Db *db, bool verbose=false, const NamingConvention &namconv=NamingConvention("Z2F"))

int	dbF2Z (Db *db, bool verbose=false, const NamingConvention &namconv=NamingConvention("F2Z"))

VectorDouble	mafOfIndex () const

Public Member Functions inherited from AStringable
	AStringable ()

	AStringable (const AStringable &r)

AStringable &	operator= (const AStringable &r)

virtual	~AStringable ()

virtual void	display (const AStringFormat *strfmt=nullptr) const final

virtual void	display (int level) const final

Private Member Functions
int	_getAddress (int ivar, int jvar) const

VectorBool	_getVectorIsotopic (const Db *db)

void	_loadData (const Db *db, int iech, VectorDouble &data)

int	_calculateEigen (VectorDouble &c0)

int	_pcaCalculate (const Db *db, const VectorBool &isoFlag, bool verbose)

int	_normalization (const Db *db, const VectorBool &isoFlag, VectorDouble &mean, VectorDouble &sigma, bool verbose=false, bool flag_nm1=false)

void	_covariance0 (const Db *db, const VectorBool &isoFlag, const VectorDouble &mean, const VectorDouble &sigma, VectorDouble &c0, bool verbose=false, bool flag_nm1=false)

int	_covarianceh (Db *db, double h0, double dh, const DirParam &dirparam, const VectorBool &isoFlag, VectorDouble &ch, bool verbose=false)

void	_center (VectorDouble &data, const VectorDouble &mean, const VectorDouble &sigma, bool flag_center=true, bool flag_scale=false)

void	_uncenter (VectorDouble &data, const VectorDouble &mean, const VectorDouble &sigma, bool flag_center=true, bool flag_scale=false)

void	_pcaZ2F (int iptr, Db *db, const VectorBool isoFlag, const VectorDouble &mean, const VectorDouble &sigma)

void	_pcaF2Z (int iptr, Db *db, const VectorBool &isoFlag, const VectorDouble &mean, const VectorDouble &sigma)

Private Attributes
int	_nVar

VectorDouble	_mean

VectorDouble	_sigma

VectorDouble	_eigen

VectorDouble	_Z2F

VectorDouble	_F2Z

Constructor & Destructor Documentation

◆ PCA() [1/4]

PCA::PCA ( int nvar = 0 )

◆ PCA() [2/4]

PCA::PCA	(	const Db *	db,
		bool	verbose = `false`
	)

◆ PCA() [3/4]

PCA::PCA	(	Db *	db,
		double	h0,
		double	dh,
		const DirParam &	dirparam = `DirParam()`,
		bool	verbose = `false`
	)

◆ PCA() [4/4]

PCA::PCA ( const PCA & m )

◆ ~PCA()

PCA::~PCA ( )

virtual

Member Function Documentation

◆ _calculateEigen()

int PCA::_calculateEigen ( VectorDouble & c0 )

private

◆ _center()

void PCA::_center	(	VectorDouble &	data,
		const VectorDouble &	mean,
		const VectorDouble &	sigma,
		bool	flag_center = `true`,
		bool	flag_scale = `false`
	)

private

Normalize the isotropic array of values

Parameters

[in,out]	data	Array of information
[in]	mean	Array containing the mean
[in]	sigma	Array containing the standard deviation
[in]	flag_center	True if result must be centered by 'mean'
[in]	flag_scale	True if result must be scaled by 'sigma'

◆ _covariance0()

void PCA::_covariance0	(	const Db *	db,
		const VectorBool &	isoFlag,
		const VectorDouble &	mean,
		const VectorDouble &	sigma,
		VectorDouble &	c0,
		bool	verbose = `false`,
		bool	flag_nm1 = `false`
	)

private

Internal PCA covariance calculation

Parameters

[in]	db	Db descriptor
[in]	isoFlag	Vector of active samples
[in]	mean	Array containing the mean
[in]	sigma	Array containing the standard deviation
[in]	verbose	Verbose flag
[in]	flag_nm1	When TRUE, variance is scaled by N-1; otherwise by N
[out]	c0	Vector of covariances at distance 0

◆ _covarianceh()

int PCA::_covarianceh	(	Db *	db,
		double	h0,
		double	dh,
		const DirParam &	dirparam,
		const VectorBool &	isoFlag,
		VectorDouble &	ch,
		bool	verbose = `false`
	)

private

Internal PCA translated covariance calculation

Error returned case

Parameters

[in]	db	Db descriptor
[in]	h0	Reference distance
[in]	dh	Tolerance on distance
[in]	dirparam	DirParam structure
[in]	isoFlag	Vector of active samples
[in]	verbose	Verbose flag
[out]	ch	Vector of covariances at distance h

◆ _getAddress()

int PCA::_getAddress	(	int	ivar,
		int	jvar
	)		const

inlineprivate

◆ _getVectorIsotopic()

VectorBool PCA::_getVectorIsotopic ( const Db * db )

private

◆ _loadData()

void PCA::_loadData	(	const Db *	db,
		int	iech,
		VectorDouble &	data
	)

private

◆ _normalization()

int PCA::_normalization	(	const Db *	db,
		const VectorBool &	isoFlag,
		VectorDouble &	mean,
		VectorDouble &	sigma,
		bool	verbose = `false`,
		bool	flag_nm1 = `false`
	)

private

Fill the mean and variance arrays

Parameters

[in]	db	Db descriptor
[in]	isoFlag	Vector of active samples
[in]	verbose	Verbose flag
[in]	flag_nm1	When TRUE, variance is scaled by N-1; otherwise by N
[out]	mean	Array of means
[out]	sigma	Array of standard deviations

◆ _pcaCalculate()

int PCA::_pcaCalculate	(	const Db *	db,
		const VectorBool &	isoFlag,
		bool	verbose
	)

private

Internal function to calculate MAF

Returns: Error return code

Parameters

[in]	db	Db descriptor
[in]	isoFlag	Vector of active samples
[in]	verbose	Verbose flag

◆ _pcaF2Z()

void PCA::_pcaF2Z	(	int	iptr,
		Db *	db,
		const VectorBool &	isoFlag,
		const VectorDouble &	mean,
		const VectorDouble &	sigma
	)

private

Procedure for transforming the factors into variables using PCA

Parameters

[in]	iptr	Pointer to the storage
[in]	db	Db descriptor
[in]	isoFlag	Vector of active samples
[in]	mean	Array containing the mean
[in]	sigma	Array containing the standard deviation

◆ _pcaZ2F()

void PCA::_pcaZ2F	(	int	iptr,
		Db *	db,
		const VectorBool	isoFlag,
		const VectorDouble &	mean,
		const VectorDouble &	sigma
	)

private

Procedure for transforming the variables into factors using PCA

Parameters

[in]	iptr	Pointer for storing the result in db
[in]	db	Db descriptor
[in]	isoFlag	Vector of active samples
[in]	mean	Array containing the mean
[in]	sigma	Array containing the standard deviation

◆ _uncenter()

void PCA::_uncenter	(	VectorDouble &	data,
		const VectorDouble &	mean,
		const VectorDouble &	sigma,
		bool	flag_center = `true`,
		bool	flag_scale = `false`
	)

private

Un-normalize the isotropic array of values

Parameters

[in,out]	data	Array of information
[in]	mean	Array containing the mean
[in]	sigma	Array containing the standard deviation
[in]	flag_center	True if result must be uncentered by 'mean'
[in]	flag_scale	True if result must be suncaled by 'sigma'

◆ dbF2Z()

int PCA::dbF2Z	(	Db *	db,
		bool	verbose = `false`,
		const NamingConvention &	namconv = `NamingConvention("F2Z")`
	)

◆ dbZ2F()

int PCA::dbZ2F	(	Db *	db,
		bool	verbose = `false`,
		const NamingConvention &	namconv = `NamingConvention("Z2F")`
	)

◆ getEigen()

double PCA::getEigen ( int ivar ) const

inline

◆ getEigens()

const VectorDouble& PCA::getEigens ( ) const

inline

◆ getF2Z() [1/2]

const VectorDouble& PCA::getF2Z ( ) const

inline

◆ getF2Z() [2/2]

double PCA::getF2Z	(	int	ivar,
		int	jvar
	)		const

inline

◆ getMean()

double PCA::getMean ( int ivar ) const

inline

◆ getMeans()

const VectorDouble& PCA::getMeans ( ) const

inline

◆ getNVar()

int PCA::getNVar ( ) const

inline

◆ getSigma()

double PCA::getSigma ( int ivar ) const

inline

◆ getSigmas()

const VectorDouble& PCA::getSigmas ( ) const

inline

◆ getVarianceRatio()

VectorDouble PCA::getVarianceRatio ( ) const

◆ getZ2F() [1/2]

const VectorDouble& PCA::getZ2F ( ) const

inline

◆ getZ2F() [2/2]

double PCA::getZ2F	(	int	ivar,
		int	jvar
	)		const

inline

◆ init()

void PCA::init ( int nvar )

◆ maf_compute()

int PCA::maf_compute	(	Db *	db,
		double	h0,
		double	dh,
		const DirParam &	dirparam,
		bool	verbose = `false`
	)

Evaluate the MAF on irregular data

Returns: PCA structure (or nullptr)

Parameters

[in]	db	Db descriptor
[in]	dirparam	DirParam structure
[in]	h0	Reference distance
[in]	dh	Tolerance on distance
[in]	verbose	Verbose flag

◆ mafOfIndex()

VectorDouble PCA::mafOfIndex ( ) const

◆ operator=()

PCA & PCA::operator= ( const PCA & m )

◆ pca_compute()

int PCA::pca_compute	(	const Db *	db,
		bool	verbose = `false`
	)

◆ setEigen() [1/2]

void PCA::setEigen ( VectorDouble & eigen )

inline

◆ setEigen() [2/2]

void PCA::setEigen	(	int	ivar,
		double	eigen
	)

inline

◆ setMean()

void PCA::setMean ( const VectorDouble & mean )

inline

◆ setPcaF2Z()

void PCA::setPcaF2Z ( VectorDouble & pcaf2z )

inline

◆ setPcaZ2F() [1/2]

void PCA::setPcaZ2F ( const VectorDouble & pcaz2f )

inline

◆ setPcaZ2F() [2/2]

void PCA::setPcaZ2F	(	int	ivar,
		int	jvar,
		double	pcaz2f
	)

inline

◆ setSigma()

void PCA::setSigma ( const VectorDouble & sigma )

inline

◆ toString()

String PCA::toString ( const AStringFormat * strfmt = nullptr ) const

overridevirtual

Interface for AStringable.

Reimplemented from AStringable.

Member Data Documentation

◆ _eigen

VectorDouble PCA::_eigen

private

◆ _F2Z

VectorDouble PCA::_F2Z

private

◆ _mean

VectorDouble PCA::_mean

private

◆ _nVar

int PCA::_nVar

private

◆ _sigma

VectorDouble PCA::_sigma

private

◆ _Z2F

VectorDouble PCA::_Z2F

private

The documentation for this class was generated from the following files:

include/Stats/PCA.hpp
src/Stats/PCA.cpp

Public Member Functions

Private Member Functions

Private Attributes

Constructor & Destructor Documentation

◆ PCA() [1/4]

◆ PCA() [2/4]

◆ PCA() [3/4]

◆ PCA() [4/4]

◆ ~PCA()

Member Function Documentation

◆ _calculateEigen()

◆ _center()

◆ _covariance0()

◆ _covarianceh()

◆ _getAddress()

◆ _getVectorIsotopic()

◆ _loadData()

◆ _normalization()

◆ _pcaCalculate()

◆ _pcaF2Z()

◆ _pcaZ2F()

◆ _uncenter()

◆ dbF2Z()

◆ dbZ2F()

◆ getEigen()

◆ getEigens()

◆ getF2Z() [1/2]

◆ getF2Z() [2/2]

◆ getMean()

◆ getMeans()

◆ getNVar()

◆ getSigma()

◆ getSigmas()

◆ getVarianceRatio()

◆ getZ2F() [1/2]

◆ getZ2F() [2/2]

◆ init()

◆ maf_compute()

◆ mafOfIndex()

◆ operator=()

◆ pca_compute()

◆ setEigen() [1/2]

◆ setEigen() [2/2]

◆ setMean()

◆ setPcaF2Z()

◆ setPcaZ2F() [1/2]

◆ setPcaZ2F() [2/2]

◆ setSigma()

◆ toString()

Member Data Documentation

◆ _eigen

◆ _F2Z

◆ _mean

◆ _nVar

◆ _sigma

◆ _Z2F