Main class for HD matrix valued matrix models. More...

#include <STK_HDMatrixGaussianModel.h>

Inheritance diagram for STK::HDMatrixGaussianModel< IdRow_, IdCol_, Array_ >:

Public Types
typedef IMixtureDensity< HDMatrixGaussianModel< IdRow_, IdCol_, Array_ > >	Base
	Base class.

typedef HDMatrixModelParameters< Array_ >	Parameters
	Type of the structure storing the parameters of a MixturGaussian_sjk model.

Public Types inherited from STK::IMixtureDensity< HDMatrixGaussianModel< IdRow_, IdCol_, Array_ > >
typedef hidden::MixtureTraits< HDMatrixGaussianModel< IdRow_, IdCol_, Array_ > >::Array	Array

typedef hidden::MixtureTraits< HDMatrixGaussianModel< IdRow_, IdCol_, Array_ > >::Parameters	Parameters

typedef hidden::Traits< Array >::Type	Type

Public Member Functions
	HDMatrixGaussianModel (int nbCluster)
	constructor

	HDMatrixGaussianModel (HDMatrixGaussianModel const &model)
	constructor

	~HDMatrixGaussianModel ()
	destructor

void	randomInit (CArrayXX const const &p_tik, CPointX const const &p_tk)
	Initialize randomly the parameters of the Gaussian mixture.

bool	run (CArrayXX const const &p_tik, CPointX const const &p_tk)
	Compute the weighted mean and the common standard deviation.

int	computeNbFreeParameters () const

Public Member Functions inherited from STK::IMixtureDensity< HDMatrixGaussianModel< IdRow_, IdCol_, Array_ > >
	~IMixtureDensity ()
	destructor

int	nbCluster () const

int	nbSample () const

Real	lnNbSample () const

Array const *const &	p_data () const

Parameters const &	param () const

void	setData (Array const &data)
	Set the data set.

void	setData (Array const &data, int nbRow, int nbCol, bool byRow=true)
	Set the data set and give dimensions.

bool	initializeStep ()
	This function will be called at the beginning of the estimation process once the model is created and data is set.

void	setParametersStep ()
	set the parameters obtained with the intermediate results and release the intermediate results.

void	finalizeStep ()
	This function will be called once the model is estimated.

Type	sample (int i, int j, Weights const &tk) const

Public Member Functions inherited from STK::IRecursiveTemplate< Derived >
Derived &	asDerived ()
	static cast : return a reference of this with a cast to the derived class.

Derived const &	asDerived () const
	static cast : return a const reference of this with a cast to the derived class.

Derived *	asPtrDerived ()
	static cast : return a ptr on a `Derived` of this with a cast to the derived class.

Derived const *	asPtrDerived () const
	static cast : return a ptr on a constant `Derived` of this with a cast to the derived class.

Derived *	clone () const
	create a leaf using the copy constructor of the Derived class.

Derived *	clone (bool isRef) const
	create a leaf using the copy constructor of the Derived class and a flag determining if the clone is a reference or not.

Protected Attributes
int	nbRow_
	number of rows and columns of the data

int	nbCol_

bool	isRowAj_
	Structure of the covariance matrices between clusters for the rows.

bool	isRowAk_

bool	isRowBk_

bool	isRowQk_

bool	isRowDk_

bool	isColAj_
	Structure of the covariance matrices between clusters for the columns.

bool	isColAk_

bool	isColBk_

bool	isColQk_

bool	isColDk_

Protected Attributes inherited from STK::IMixtureDensity< HDMatrixGaussianModel< IdRow_, IdCol_, Array_ > >
Parameters	param_
	parameters of the derived mixture model.

Private Member Functions
bool	runFreeOrientationByRow (CArrayXX const const &p_tik, CPointX const const &p_tk)
	Update parameters for models with free orientation by rows.

bool	runCommonOrientationByRow (CArrayXX const const &p_tik, CPointX const const &p_tk)
	Update parameters for models with common orientation by rows.

bool	runFreeOrientationByCol (CArrayXX const const &p_tik, CPointX const const &p_tk)
	Update parameters for models with free orientation by columns.

bool	runCommonOrientationByCol (CArrayXX const const &p_tik, CPointX const const &p_tk)
	Update parameters for models with common orientation by columns.

Additional Inherited Members
Protected Member Functions inherited from STK::IMixtureDensity< HDMatrixGaussianModel< IdRow_, IdCol_, Array_ > >
	IMixtureDensity (int nbCluster)
	Default constructor.

	IMixtureDensity (IMixtureDensity const &model)
	copy constructor.

void	initializeModel ()
	Initialize the model before its first use.

bool	initializeStepImpl ()
	default implementation of initializeStepImpl (do nothing and return true)

void	finalizeStepImpl ()
	default implementation of finalizeStepImpl (do nothing)

void	setNbSample (int nbSample)
	Set the number of sample of the model (needed by kernel models)

Protected Member Functions inherited from STK::IRecursiveTemplate< Derived >
	IRecursiveTemplate ()
	constructor.

	~IRecursiveTemplate ()
	destructor.

Detailed Description

template<int IdRow_, int IdCol_, class Array_>
class STK::HDMatrixGaussianModel< IdRow_, IdCol_, Array_ >

Main class for HD matrix valued matrix models.

Definition at line 67 of file STK_HDMatrixGaussianModel.h.

Member Typedef Documentation

◆ Base

template<int IdRow_, int IdCol_, class Array_ >

typedef IMixtureDensity<HDMatrixGaussianModel<IdRow_, IdCol_, Array_> > STK::HDMatrixGaussianModel< IdRow_, IdCol_, Array_ >::Base

Base class.

Definition at line 72 of file STK_HDMatrixGaussianModel.h.

◆ Parameters

template<int IdRow_, int IdCol_, class Array_ >

typedef HDMatrixModelParameters<Array_> STK::HDMatrixGaussianModel< IdRow_, IdCol_, Array_ >::Parameters

Type of the structure storing the parameters of a MixturGaussian_sjk model.

Definition at line 74 of file STK_HDMatrixGaussianModel.h.

Constructor & Destructor Documentation

◆ HDMatrixGaussianModel() [1/2]

template<int IdRow_, int IdCol_, class Array_ >

STK::HDMatrixGaussianModel< IdRow_, IdCol_, Array_ >::HDMatrixGaussianModel ( int nbCluster )

inline

constructor

Parameters

nbCluster number of clusters

Definition at line 84 of file STK_HDMatrixGaussianModel.h.

                         : Base(nbCluster)
                         , isRowAj_(hidden::HDCovarianceChooser<IdRow_>::isAj_)
                         , isRowAk_(hidden::HDCovarianceChooser<IdRow_>::isAk_)
                         , isRowBk_(hidden::HDCovarianceChooser<IdRow_>::isBk_)
                         , isRowQk_(hidden::HDCovarianceChooser<IdRow_>::isQk_)
                         , isRowDk_(hidden::HDCovarianceChooser<IdRow_>::isDk_)
                         , isColAj_(hidden::HDCovarianceChooser<IdCol_>::isAj_)
                         , isColAk_(hidden::HDCovarianceChooser<IdCol_>::isAk_)
                         , isColBk_(hidden::HDCovarianceChooser<IdCol_>::isBk_)
                         , isColQk_(hidden::HDCovarianceChooser<IdCol_>::isQk_)
                         , isColDk_(hidden::HDCovarianceChooser<IdCol_>::isDk_)
    {}

◆ HDMatrixGaussianModel() [2/2]

template<int IdRow_, int IdCol_, class Array_ >

STK::HDMatrixGaussianModel< IdRow_, IdCol_, Array_ >::HDMatrixGaussianModel ( HDMatrixGaussianModel< IdRow_, IdCol_, Array_ > const & model )

inline

constructor

Parameters

nbCluster number of clusters

Definition at line 100 of file STK_HDMatrixGaussianModel.h.

                         : Base(model)
                         , nbRow_(model.nbRow_)
                         , nbCol_(model.nbCol_)
                         , isRowAj_(model.isRowAj_), isRowAk_(model.isRowAk_)
                         , isRowBk_(model.isRowBk_)
                         , isRowQk_(model.isRowQk_)
                         , isRowDk_(model.isRowDk_)
                         , isColAj_(model.isColAj_), isColAk_(model.isColAk_)
                         , isColBk_(model.isColBk_)
                         , isColQk_(model.isColQk_)
                         , isColDk_(model.isColDk_)
    {}

◆ ~HDMatrixGaussianModel()

template<int IdRow_, int IdCol_, class Array_ >

STK::HDMatrixGaussianModel< IdRow_, IdCol_, Array_ >::~HDMatrixGaussianModel ( )

inline

destructor

Definition at line 114 of file STK_HDMatrixGaussianModel.h.

114{}

Member Function Documentation

◆ computeNbFreeParameters()

template<int IdRow_, int IdCol_, class Array_ >

int STK::HDMatrixGaussianModel< IdRow_, IdCol_, Array_ >::computeNbFreeParameters ( ) const

Returns: the number of free parameters of the model

Definition at line 146 of file STK_HDMatrixGaussianModel.h.

{
  int sum = nbRow_*nbCol_;
  int maxRowDk = param_.rowDk_.maxElt();
  int maxColDk = param_.colDk_.maxElt();
  // for Bk
  sum += (isRowBk_)? nbCluster :1;
  sum += (isColBk_)? nbCluster :1;
  // for Ajk
  sum += (isRowAk_) ? ((isRowAj_) ? param_.rowDk_.sum() : nbCluster_) : maxRowDk;
  sum += (isColAk_) ? ((isColAj_) ? param_.colDk_.sum() : nbCluster_) : maxColDk;
  // for Qk
  if (isRowQk_)
  {
    int dk = param_.rowDk_[k];
    sum += dk*nbRow_ - (dk*(dk+1))/2;
  }
  else
  { sum += maxRowDk*nbRow - (maxRowDk*(maxRowDk+1))/2;}
  if (isColQk_)
  {
    int dk = param_.colDk_[k];
    sum += dk*nbCol_ - (dk*(dk+1))/2;
  }
  else
  { sum += maxColDk*nbRow - (maxColDk*(maxColDk+1))/2;}
  //
  return sum;
}

References STK::sum().

◆ randomInit()

template<int IdRow_, int IdCol_, class Array_ >

void STK::HDMatrixGaussianModel< IdRow_, IdCol_, Array_ >::randomInit	(	CArrayXX const *const &	p_tik,
		CPointX const *const &	p_tk
	)

Initialize randomly the parameters of the Gaussian mixture.

The centers will be selected randomly among the data set and the standard-deviation will be set to 1.

Definition at line 184 of file STK_HDMatrixGaussianModel.h.

{
  VectorXi indexes(p_data()->rows());
  for(int i=indexes.begin(); i< indexes.end(); ++i) { indexes[i] = i;}
  Range rind(p_data()->rows());
  // sample mean between individuals without repetition
  for (int k= p_tk->begin(); k < p_tk->end(); ++k)
  {
    // random number in [0, end-k[
    int i = Law::UniformDiscrete::rand(rind.begin(), rind.end()-1);
    // get ith individuals
    param_.meank_[k] = p_data()->row(indexes[i]);
    // exchange it with nth
    indexes.swap(i, rind.lastIdx());
    // decrease
    rind.decLast(1);
  }
  //
  Real rowB = Law::Exponential::rand(1);
  Real colB = Law::Exponential::rand(1);;
  Real rowA = rowB + Law::Exponential::rand(1);
  Real colA = colB + Law::Exponential::rand(1);
  //
  for (int k= p_tk->begin(); k < p_tk->end(); ++k)
  {
    Real v = Law::Normal::rand(0,1), w = Law::Normal::rand(0,1);
    param_.rowQk_[k]  = v * Const::Identity(nbRow_);
    param_.colQk_[k]  = w * Const::Identity(nbCol_);
    param_.rowAjk_[k] = rowA;
    param_.rowBk_[k]  = rowB;
    param_.colAjk_[k] = colA;
    param_.colBk_[k]  = colB;
  }
}

References STK::Law::Exponential::rand(), STK::Law::Normal::rand(), and STK::Law::UniformDiscrete::rand().

◆ run()

template<int IdRow_, int IdCol_, class Array_ >

bool STK::HDMatrixGaussianModel< IdRow_, IdCol_, Array_ >::run	(	CArrayXX const *const &	p_tik,
		CPointX const *const &	p_tk
	)

Compute the weighted mean and the common standard deviation.

Definition at line 177 of file STK_HDMatrixGaussianModel.h.

{
 
  return true;
}

◆ runCommonOrientationByCol()

template<int IdRow_, int IdCol_, class Array_ >

bool STK::HDMatrixGaussianModel< IdRow_, IdCol_, Array_ >::runCommonOrientationByCol	(	CArrayXX const *const &	p_tik,
		CPointX const *const &	p_tk
	)

private

Update parameters for models with common orientation by columns.

◆ runCommonOrientationByRow()

template<int IdRow_, int IdCol_, class Array_ >

bool STK::HDMatrixGaussianModel< IdRow_, IdCol_, Array_ >::runCommonOrientationByRow	(	CArrayXX const *const &	p_tik,
		CPointX const *const &	p_tk
	)

private

Update parameters for models with common orientation by rows.

◆ runFreeOrientationByCol()

template<int IdRow_, int IdCol_, class Array_ >

bool STK::HDMatrixGaussianModel< IdRow_, IdCol_, Array_ >::runFreeOrientationByCol	(	CArrayXX const *const &	p_tik,
		CPointX const *const &	p_tk
	)

private

Update parameters for models with free orientation by columns.

◆ runFreeOrientationByRow()

template<int IdRow_, int IdCol_, class Array_ >

bool STK::HDMatrixGaussianModel< IdRow_, IdCol_, Array_ >::runFreeOrientationByRow	(	CArrayXX const *const &	p_tik,
		CPointX const *const &	p_tk
	)

private

Update parameters for models with free orientation by rows.

Definition at line 221 of file STK_HDMatrixGaussianModel.h.

{
  CSquareX w;
  STK::lapack::SymEigen<CSquareX> decomp(w);
  for (int k=p_tk->begin(); k< p_tk->end(); ++k)
  {
 
    // compute the unbiased covariance function
    Stat::Covariance(*p_data(), p_tik()->col(k), false);
  }
}