Computation of the Multivariate Statistics of a 2D Container of Real. More...

#include <STK_Stat_MultivariateReal.h>

Inheritance diagram for STK::Stat::Multivariate< Array, Real >:

Public Member Functions
	Multivariate ()
	Default Constructor.

	Multivariate (Array const &data)
	Constructor.

	Multivariate (Array const *p_data)
	Constructor.

	Multivariate (Multivariate const &stat)
	copy constructor.

virtual	~Multivariate ()
	virtual destructor.

virtual Multivariate *	clone () const
	clone pattern

int	nbVariable () const

int	nbSamples () const

PointX const &	min () const

PointX const &	max () const

PointX const &	mean () const

PointX const &	variance () const

ArraySquareX const &	covariance () const

virtual bool	run ()
	run the estimation of the Multivariate statistics.

virtual bool	run (ColVector const &weights)
	run the estimation of the weighted multivariate statistics.

Public Member Functions inherited from STK::IRunnerUnsupervised< Array, hidden::Traits< Array >::Col >
Array const *	p_data () const
	get the data set

virtual void	setData (Array const *p_data)
	Set the data set.

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

virtual bool	run (hidden::Traits< Array >::Col const &weights)=0
	run the weighted computations.

Public Member Functions inherited from STK::IRunnerBase
String const &	error () const
	get the last error message.

Protected Member Functions
virtual void	update ()
	udpating method in case we set a new data set

Protected Member Functions inherited from STK::IRunnerUnsupervised< Array, hidden::Traits< Array >::Col >
	IRunnerUnsupervised ()
	default constructor.

	IRunnerUnsupervised (Array const *const p_data)
	constructor with a pointer on the constant data set

	IRunnerUnsupervised (Array const &data)
	constructor with a constant reference on the data set

	IRunnerUnsupervised (IRunnerUnsupervised const &runner)
	copy constructor

	~IRunnerUnsupervised ()
	destructor

Protected Member Functions inherited from STK::IRunnerBase
	IRunnerBase ()
	default constructor

	IRunnerBase (IRunnerBase const &runner)
	copy constructor

virtual	~IRunnerBase ()
	destructor

Protected Attributes
int	nbSamples_
	number of samples

int	nbVar_
	Number of variables.

PointX	min_
	Vector of the mean of the Variables.

PointX	max_
	Vector of the mean of the Variables.

PointX	mean_
	Vector of the mean of the Variables.

PointX	var_
	Vector of the variance of the variables.

ArraySquareX	cov_
	Array of the covariance of the variables.

Protected Attributes inherited from STK::IRunnerUnsupervised< Array, hidden::Traits< Array >::Col >
Array const *	p_data_
	A pointer on the original data set.

Protected Attributes inherited from STK::IRunnerBase
String	msg_error_
	String with the last error message.

bool	hasRun_
	`true` if run has been used, `false` otherwise

Private Types
enum	{ value_ = hidden::isSame<Type_, Real>::value_ }

typedef hidden::Traits< Array >::Row	RowVector

typedef hidden::Traits< Array >::Col	ColVector

typedef IRunnerUnsupervised< Array, ColVector >	Runner
	type of runner

typedef Array::Type	Type_

Detailed Description

template<class Array>
class STK::Stat::Multivariate< Array, Real >

Computation of the Multivariate Statistics of a 2D Container of Real.

The class Multivariate is just a factory class for computing the mean, the variance and the covariance square matrix of a p_data set stored in a Array with n rows (the samples) and p columns (the variables).

Definition at line 59 of file STK_Stat_MultivariateReal.h.

Member Typedef Documentation

◆ ColVector

template<class Array >

typedef hidden::Traits<Array>::Col STK::Stat::Multivariate< Array, Real >::ColVector

private

Definition at line 62 of file STK_Stat_MultivariateReal.h.

◆ RowVector

template<class Array >

typedef hidden::Traits<Array>::Row STK::Stat::Multivariate< Array, Real >::RowVector

private

Definition at line 61 of file STK_Stat_MultivariateReal.h.

◆ Runner

template<class Array >

typedef IRunnerUnsupervised< Array, ColVector> STK::Stat::Multivariate< Array, Real >::Runner

private

type of runner

Definition at line 64 of file STK_Stat_MultivariateReal.h.

◆ Type_

template<class Array >

typedef Array::Type STK::Stat::Multivariate< Array, Real >::Type_

private

Definition at line 65 of file STK_Stat_MultivariateReal.h.

Member Enumeration Documentation

◆ anonymous enum

template<class Array >

anonymous enum

private

Enumerator
value_

Definition at line 66 of file STK_Stat_MultivariateReal.h.

  {
    value_ = hidden::isSame<Type_, Real>::value_
  };

Constructor & Destructor Documentation

◆ Multivariate() [1/4]

template<class Array >

STK::Stat::Multivariate< Array, Real >::Multivariate ( )

inline

Default Constructor.

Definition at line 73 of file STK_Stat_MultivariateReal.h.

                  : Runner()
                  , nbSamples_(0), nbVar_(0)
                  , min_(), max_(), mean_(), var_(), cov_()
  { STK_STATIC_ASSERT(value_, YOU_CANNOT_USED_THIS_TYPE_OF_DATA_WITH_THIS_OBJECT);}

References STK_STATIC_ASSERT.

◆ Multivariate() [2/4]

template<class Array >

STK::Stat::Multivariate< Array, Real >::Multivariate ( Array const & data )

inline

Constructor.

Parameters

data	a reference on the data set

Definition at line 80 of file STK_Stat_MultivariateReal.h.

                : Runner(&data)
                , nbSamples_(data.sizeRows()), nbVar_(data.sizeCols())
                , min_(), max_(), mean_(), var_(), cov_()
    { STK_STATIC_ASSERT(value_, YOU_CANNOT_USED_THIS_TYPE_OF_DATA_WITH_THIS_OBJECT);}

References STK_STATIC_ASSERT.

◆ Multivariate() [3/4]

template<class Array >

STK::Stat::Multivariate< Array, Real >::Multivariate ( Array const * p_data )

inline

Constructor.

Parameters

p_data a pointer on the data set

Definition at line 88 of file STK_Stat_MultivariateReal.h.

                : Runner(p_data)
                , nbSamples_((p_data) ? p_data->sizeRows() : 0)
                , nbVar_((p_data) ? p_data->sizeCols() : 0)
                , min_(), max_(), mean_(), var_(), cov_()
    { STK_STATIC_ASSERT(value_, YOU_CANNOT_USED_THIS_TYPE_OF_DATA_WITH_THIS_OBJECT);}

References STK_STATIC_ASSERT.

◆ Multivariate() [4/4]

template<class Array >

STK::Stat::Multivariate< Array, Real >::Multivariate ( Multivariate< Array, Real > const & stat )

inline

copy constructor.

Parameters

stat	the statistics to copy

Definition at line 97 of file STK_Stat_MultivariateReal.h.

                : Runner(stat)
                , nbSamples_(stat.nbSamples_), nbVar_(stat.nbVar_)
                , min_(stat.min_), max_(stat.max_), mean_(stat.mean_)
                , var_(stat.var_), cov_(stat.cov_)
    {}

◆ ~Multivariate()

template<class Array >

virtual STK::Stat::Multivariate< Array, Real >::~Multivariate ( )

inlinevirtual

virtual destructor.

Definition at line 104 of file STK_Stat_MultivariateReal.h.

104{ }

Member Function Documentation

◆ clone()

template<class Array >

virtual Multivariate * STK::Stat::Multivariate< Array, Real >::clone ( ) const

inlinevirtual

clone pattern

Definition at line 106 of file STK_Stat_MultivariateReal.h.

106{ return new Multivariate(*this);}

STK::Stat::Multivariate< Array, Real >::Multivariate

Multivariate()

Default Constructor.

Definition STK_Stat_MultivariateReal.h:73

◆ covariance()

template<class Array >

ArraySquareX const & STK::Stat::Multivariate< Array, Real >::covariance ( ) const

inline

Returns: the covariance of the variables in a square matrix

Definition at line 120 of file STK_Stat_MultivariateReal.h.

120{ return cov_;}

◆ max()

template<class Array >

PointX const & STK::Stat::Multivariate< Array, Real >::max ( ) const

inline

Returns: the maximal values of the variables in a RowVector

Definition at line 114 of file STK_Stat_MultivariateReal.h.

114{ return max_;}

◆ mean()

template<class Array >

PointX const & STK::Stat::Multivariate< Array, Real >::mean ( ) const

inline

Returns: the mean of the variables in a RowVector

Definition at line 116 of file STK_Stat_MultivariateReal.h.

116{ return mean_;}

◆ min()

template<class Array >

PointX const & STK::Stat::Multivariate< Array, Real >::min ( ) const

inline

Returns: the minimal values of the variables in a RowVector

Definition at line 112 of file STK_Stat_MultivariateReal.h.

112{ return min_;}

◆ nbSamples()

template<class Array >

int STK::Stat::Multivariate< Array, Real >::nbSamples ( ) const

inline

Returns: the number of samples in the p_data_ set (the number of rows)

Definition at line 110 of file STK_Stat_MultivariateReal.h.

110{return nbSamples_;}

References STK::Stat::Multivariate< Array, WColVector, Type >::nbSamples_.

◆ nbVariable()

template<class Array >

int STK::Stat::Multivariate< Array, Real >::nbVariable ( ) const

inline

Returns: the number of variables in the p_data_ set (the number of columns)

Definition at line 108 of file STK_Stat_MultivariateReal.h.

108{return nbVar_;}

References STK::Stat::Multivariate< Array, WColVector, Type >::nbVar_.

◆ run() [1/2]

template<class Array >

virtual bool STK::Stat::Multivariate< Array, Real >::run ( )

inlinevirtual

run the estimation of the Multivariate statistics.

Implements STK::IRunnerUnsupervised< Array, hidden::Traits< Array >::Col >.

Definition at line 123 of file STK_Stat_MultivariateReal.h.

    {
      if (!this->p_data_)
      { this->msg_error_ = STKERROR_NO_ARG(MultivariateArray::run(),data is not set);
        return false;
      }
      try
      {
        mean_.move(Stat::mean(*this->p_data_));
        min_.move(Stat::min(*this->p_data_));
        max_.move(Stat::max(*this->p_data_));
        var_.move(varianceWithFixedMean(*this->p_data_, mean_, false));
 
        cov_.resize(this->p_data_->cols());
        for (int j=this->p_data_->beginCols(); j<this->p_data_->endCols(); j++)
        {
          cov_(j, j) = var_[j];
          for (int i=this->p_data_->beginCols(); i<j; i++)
          {
            cov_(i, j) = covarianceWithFixedMean(this->p_data_->col(i), this->p_data_->col(j), mean_[i], mean_[j], false);
            cov_(j, i) = cov_(i, j);
          }
        }
      }
      catch (Exception const& error)
      {
        this->msg_error_ += _T("Error in Multivariate::run():\nWhat: ");
        this->msg_error_ += error.error();
        return false;
      }
      // no error
      return true;
    }

References _T, STK::Stat::covarianceWithFixedMean(), STK::Exception::error(), STK::IRunnerBase::error(), STK::Stat::max(), STK::Stat::mean(), STK::Stat::min(), STK::IRunnerBase::msg_error_, STK::IRunnerUnsupervised< Array, WColVector >::p_data_, STKERROR_NO_ARG, and STK::Stat::varianceWithFixedMean().

◆ run() [2/2]

template<class Array >

virtual bool STK::Stat::Multivariate< Array, Real >::run ( ColVector const & weights )

inlinevirtual

run the estimation of the weighted multivariate statistics.

Parameters

weights the weights of the samples

Definition at line 159 of file STK_Stat_MultivariateReal.h.

    {
      if (!this->p_data_)
      { this->msg_error_ = STKERROR_NO_ARG(MultivariateArray::run(weights),data is not set);
        return false;
      }
      if (this->p_data_->rows() != weights.range())
      { this->msg_error_ = STKERROR_NO_ARG(MultivariateArray::run(weights),p_data_->rows() != weights.range());
        return false;
      }
      try
      {
        mean_.move(Stat::mean(*this->p_data_, weights));
        min_.move(Stat::min(*this->p_data_,weights));
        max_.move(Stat::max(*this->p_data_, weights));
        var_.move(varianceWithFixedMean(*this->p_data_, weights, mean_, false));
 
        cov_.resize(this->p_data_->cols());
        // for each variables
        for (int j= this->p_data_->beginCols(); j< this->p_data_->endCols(); j++)
        {
          cov_(j, j) = var_[j];
          // compute the covariances
          for (int i= this->p_data_->beginCols(); i<j; i++)
          {
            cov_(i, j) = covarianceWithFixedMean(this->p_data_->col(i), this->p_data_->col(j), weights, mean_[i], mean_[j]);
            cov_(j, i) = cov_(i, j);
          }
        }
      }
      catch (Exception const& error)
      {
        this->msg_error_  = _T("Error in Multivariate::run(weights): ");
        this->msg_error_ += error.error();
        return false;
      }
      // no error
      return true;
    }

References _T, STK::Stat::covarianceWithFixedMean(), STK::Exception::error(), STK::IRunnerBase::error(), STK::Stat::max(), STK::Stat::mean(), STK::Stat::min(), STK::IRunnerBase::msg_error_, STK::IRunnerUnsupervised< Array, WColVector >::p_data_, STKERROR_NO_ARG, and STK::Stat::varianceWithFixedMean().

◆ update()

template<class Array >

virtual void STK::Stat::Multivariate< Array, Real >::update ( )

inlineprotectedvirtual

udpating method in case we set a new data set

Reimplemented from STK::IRunnerBase.

Definition at line 217 of file STK_Stat_MultivariateReal.h.

    {
      // if there is no data there is nothing to update
      if (this->p_data_)
      {
        nbSamples_ = this->p_data_->sizeRows();
        nbVar_     = this->p_data_->sizeCols();
      }
    }