STK::ProjectedVariance< Array > Class Template Reference

A ProjectedVariance is an implementation of the abstract ILinearReduct interface. More...

#include <STK_ProjectedVariance.h>

Inheritance diagram for STK::ProjectedVariance< Array >:

Public Types
typedef ILinearReduct< Array, VectorX >	Base
Public Types inherited from STK::ILinearReduct< Array, VectorX >
typedef IReducer< Array, VectorX >	Base

Public Member Functions
	ProjectedVariance ()
	default constructor
	ProjectedVariance (Array const *p_data)
	Constructor.
	ProjectedVariance (Array const &data)
	Constructor.
	ProjectedVariance (ProjectedVariance const &reducer)
	Copy constructor.
virtual	~ProjectedVariance ()
	Destructor.
virtual ProjectedVariance *	clone () const
	clone pattern
Public Member Functions inherited from STK::ILinearReduct< Array, VectorX >
	ILinearReduct ()
	Default Constructor.
	ILinearReduct (Array const *p_data)
	Constructor.
	ILinearReduct (Array const &data)
	Constructor.
	ILinearReduct (ILinearReduct const &reducer)
	copy Constructor.
virtual	~ILinearReduct ()
	virtual destructor
VectorX const &	criteriaValues () const
Array const &	axis () const
virtual bool	run ()
	Compute the projection matrix axis_ by maximizing the criteria and project the data set in order to obtain p_projected_.
virtual bool	run (VectorX const &weights)
	Compute the projection matrix set by maximizing the weighted criteria and project the data set in order to obtain p_projected_.
Public Member Functions inherited from STK::IReducer< Array, Weights >
virtual	~IReducer ()
	virtual destructor.
int	dim () const
	get the number of dimension.
Array *	p_reduced () const
	get a pointer on the reduced data set
void	setDimension (const int &dim)
	set the number of dimension.
void	clear ()
	clear allocated memory
Public Member Functions inherited from STK::IRunnerUnsupervised< Array, Weights >
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.
Public Member Functions inherited from STK::IRunnerBase
String const &	error () const
	get the last error message.

Protected Attributes
ArraySquareX	covariance_
	the covariance Array
Protected Attributes inherited from STK::ILinearReduct< Array, VectorX >
VectorX	idx_values_
	The values of the index for each axis.
Array	axis_
	The computed axis.
Protected Attributes inherited from STK::IReducer< Array, Weights >
int	dim_
	dimension of the reduced data set
Array *	p_reduced_
	The reduced data set.
Protected Attributes inherited from STK::IRunnerUnsupervised< Array, Weights >
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 Member Functions
virtual void	maximizeStep ()
	Find the axis by maximizing the Index.
virtual void	maximizeStep (VectorX const &weights)
	Find the axis by maximizing the weighed Index.
void	computeAxis ()
	compute axis and index.
virtual void	update ()
	update the class if a new data set is set.

Additional Inherited Members
Public Attributes inherited from STK::ILinearReduct< Array, VectorX >
Array *	p_reduced_
	The reduced data set.
Protected Types inherited from STK::IReducer< Array, Weights >
typedef IRunnerUnsupervised< Array, Weights >	Runner
Protected Member Functions inherited from STK::IReducer< Array, Weights >
	IReducer ()
	Default constructor.
	IReducer (Array const *p_data)
	Constructor with a pointer on the constant data set.
	IReducer (Array const &data)
	Constructor with a constant reference on the data set.
	IReducer (IReducer const &reducer)
	Copy constructor.
Protected Member Functions inherited from STK::IRunnerUnsupervised< Array, Weights >
	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

Detailed Description

template<class Array>
class STK::ProjectedVariance< Array >

A ProjectedVariance is an implementation of the abstract ILinearReduct interface.

ProjectedVariance (PCA) reduce the dimension of data by maximizing the projected varaince on an affine subspace of dimension d.

Definition at line 50 of file STK_ProjectedVariance.h.

Member Typedef Documentation

Base

template<class Array >

typedef ILinearReduct<Array, VectorX> STK::ProjectedVariance< Array >::Base

Definition at line 53 of file STK_ProjectedVariance.h.

Constructor & Destructor Documentation

ProjectedVariance() [1/4]

template<class Array >

STK::ProjectedVariance< Array >::ProjectedVariance

(

)

default constructor

Definition at line 100 of file STK_ProjectedVariance.h.

: Base() {}

Referenced by STK::ProjectedVariance< Array >::clone().

ProjectedVariance() [2/4]

template<class Array >

STK::ProjectedVariance< Array >::ProjectedVariance

(

Array const *

p_data

)

Constructor.

Parameters

p_data

a pointer on the constant data set to reduce.

Definition at line 105 of file STK_ProjectedVariance.h.

                                          : Base(p_data)
{}

ProjectedVariance() [3/4]

template<class Array >

STK::ProjectedVariance< Array >::ProjectedVariance

(

Array const &

data

)

Constructor.

Parameters

data	a constant reference on the data set to reduce.

Definition at line 112 of file STK_ProjectedVariance.h.

                                          : Base(data)
{}

ProjectedVariance() [4/4]

template<class Array >

STK::ProjectedVariance< Array >::ProjectedVariance

(

ProjectedVariance< Array > const &

reducer

)

Copy constructor.

Parameters

reducer

the reducer to copy

Definition at line 119 of file STK_ProjectedVariance.h.

                                          : Base(reducer)
{}

~ProjectedVariance()

template<class Array >

STK::ProjectedVariance< Array >::~ProjectedVariance ( )

virtual

Destructor.

Definition at line 125 of file STK_ProjectedVariance.h.

{}

Member Function Documentation

clone()

template<class Array >

virtual ProjectedVariance * STK::ProjectedVariance< Array >::clone ( ) const

inlinevirtual

clone pattern

Returns

a pointer on the clone of this

Definition at line 77 of file STK_ProjectedVariance.h.

    { return new ProjectedVariance(*this);}

References STK::ProjectedVariance< Array >::ProjectedVariance().

computeAxis()

template<class Array >

void STK::ProjectedVariance< Array >::computeAxis ( )

private

compute axis and index.

Definition at line 156 of file STK_ProjectedVariance.h.

{
  SymEigen<ArraySquareX> eigen(covariance_);
  eigen.run();
 
  // compute the range of the axis
  Range range(p_data_->beginCols(), std::min(this->dim_, p_data_->sizeCols()));
  // copy axis and index values
  axis_.resize(p_data_->cols(), range);
  idx_values_.resize(range);
  axis_       = eigen.rotation().col(range);
  idx_values_ = eigen.eigenValues().sub(range);
}

References STK::IRegression< YArray, XArray, Weights >::run().

maximizeStep() [1/2]

template<class Array >

void STK::ProjectedVariance< Array >::maximizeStep ( )

privatevirtual

Find the axis by maximizing the Index.

Implements STK::ILinearReduct< Array, VectorX >.

Definition at line 130 of file STK_ProjectedVariance.h.

{
#ifdef STK_REDUCT_DEBUG
  if (!p_data_)
  { STKRUNTIME_ERROR_NO_ARG(ProjectedVariance::maximizeStep,data is not set);}
#endif
  covariance_.move(Stat::covariance(*p_data_, true));
  computeAxis();
}

References STK::Stat::covariance(), STK::ProjectedVariance< Array >::maximizeStep(), and STKRUNTIME_ERROR_NO_ARG.

Referenced by STK::ProjectedVariance< Array >::maximizeStep(), and STK::ProjectedVariance< Array >::maximizeStep().

maximizeStep() [2/2]

template<class Array >

void STK::ProjectedVariance< Array >::maximizeStep ( VectorX const &  weights )

privatevirtual

Find the axis by maximizing the weighed Index.

Parameters

weights

the weights of the samples.

Implements STK::ILinearReduct< Array, VectorX >.

Definition at line 144 of file STK_ProjectedVariance.h.

{
#ifdef STK_REDUCT_DEBUG
  if (!p_data_)
  { STKRUNTIME_ERROR_NO_ARG(ProjectedVariance::maximizeStep,data is not set);}
#endif
  covariance_.move(Stat::covariance(*p_data_, weights, true));
  computeAxis();
}

References STK::Stat::covariance(), STK::ProjectedVariance< Array >::maximizeStep(), and STKRUNTIME_ERROR_NO_ARG.

update()

template<class Array >

void STK::ProjectedVariance< Array >::update ( )

privatevirtual

update the class if a new data set is set.

Reimplemented from STK::IRunnerBase.

Definition at line 172 of file STK_ProjectedVariance.h.

{
  covariance_.clear();
}

Member Data Documentation

covariance_

template<class Array >

ArraySquareX STK::ProjectedVariance< Array >::covariance_

protected

the covariance Array

Definition at line 82 of file STK_ProjectedVariance.h.

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

• STK_ProjectedVariance.h