Compute an additive BSpline, multivalued, regression function using BSpline basis. More...

#include <STK_AdditiveBSplineRegression.h>

Inheritance diagram for STK::AdditiveBSplineRegression< YArray, XArray, Weights >:

Public Types
typedef IRegression< YArray, XArray, Weights >	Base

typedef Regress::KnotsPosition	KnotsPosition

Public Member Functions
	AdditiveBSplineRegression (YArray const p_y, XArray const p_x, int nbControlPoints, int degree=3, KnotsPosition const &position=Regress::uniformKnotsPositions_)
	Constructor.

	AdditiveBSplineRegression (YArray const &y, XArray const &x, int nbControlPoints, int degree=3, KnotsPosition const &position=Regress::uniformKnotsPositions_)
	Constructor.

virtual	~AdditiveBSplineRegression ()
	virtual destructor.

int	degree () const

int	nbControlPoints () const

YArray const &	controlPoints () const

ArrayXX const &	coefficients () const
	This is a matrix of size (p_x_->range(), 0:lastControlPoints).

virtual YArray	extrapolate (XArray const &x) const

Public Member Functions inherited from STK::IRegression< YArray, XArray, Weights >
virtual	~IRegression ()
	virtual destructor.

YArray const &	predicted () const

YArray const &	residuals () const

YArray *	p_predicted ()

YArray *	p_residuals ()

int	nbFreeParameter () const

virtual bool	run ()
	run the computations.

virtual bool	run (Weights const &weights)
	run the weighted computations.

Public Member Functions inherited from STK::IRunnerSupervised< YArray, XArray, Weights >
virtual void	setX (XArray const &x)
	set the x data set (predictors).

virtual void	setY (YArray const &y)
	set the data set.

virtual void	setData (YArray const &y, XArray const &x)
	set the data set.

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

Public Attributes
YArray	predicted_
	Container of the predicted output.

YArray	residuals_
	Container of the residuals.

Protected Member Functions
virtual bool	initializeStep ()
	compute the coefficients of the BSpline basis.

virtual bool	regressionStep ()
	Compute the regression function.

virtual bool	regressionStep (Weights const &weights)
	Compute the weighted regression.

virtual bool	predictionStep ()
	Compute the predicted outputs.

virtual int	computeNbFreeParameter () const

Protected Member Functions inherited from STK::IRegression< YArray, XArray, Weights >
	IRegression ()
	Default constructor.

	IRegression (ArrayBase< YArray > const p_y, ArrayBase< XArray > const p_x)
	constructor

	IRegression (ArrayBase< YArray > const &y, ArrayBase< XArray > const &x)
	Constructor.

virtual bool	finalizeStep ()
	perform any computation needed after the call of the regression method.

bool	residualsStep ()
	Compute the residuals of the model.

Protected Member Functions inherited from STK::IRunnerSupervised< YArray, XArray, Weights >
	IRunnerSupervised ()
	default constructor

	IRunnerSupervised (YArray const const &p_y, XArray const const &p_x)
	constructor

	IRunnerSupervised (YArray const &y, XArray const &x)
	default constructor

	IRunnerSupervised (IRunnerSupervised const &runner)
	copy constructor

	~IRunnerSupervised ()
	destructor

virtual void	updateY ()
	update the runner when y data set is set.

virtual void	updateX ()
	update the runner when x data set is set.

virtual void	update ()
	update the runner.

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

	IRunnerBase (IRunnerBase const &runner)
	copy constructor

virtual	~IRunnerBase ()
	destructor

Protected Attributes
int	nbControlPoints_
	number of control points of the B-spline curve.

int	degree_
	degree of the B_Spline curve

KnotsPosition	position_
	method of position of the knots of the B-spline curve

AdditiveBSplineCoefficients< XArray >	coefs_
	Coefficients of the regression matrix.

YArray	controlPoints_
	Estimated control points of the B-spline curve.

Protected Attributes inherited from STK::IRegression< YArray, XArray, Weights >
YArray	predicted_
	Container of the predicted output.

YArray	residuals_
	Container of the residuals.

Protected Attributes inherited from STK::IRunnerSupervised< YArray, XArray, Weights >
YArray const *	p_y_
	A pointer on the y data set.

XArray const *	p_x_
	A pointer on the x 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

Additional Inherited Members
Protected Types inherited from STK::IRegression< YArray, XArray, Weights >
typedef IRunnerSupervised< YArray, XArray, Weights >	Base

Detailed Description

template<class YArray, class XArray, class Weights = VectorX>
class STK::AdditiveBSplineRegression< YArray, XArray, Weights >

Compute an additive BSpline, multivalued, regression function using BSpline basis.

Definition at line 56 of file STK_AdditiveBSplineRegression.h.

Member Typedef Documentation

◆ Base

template<class YArray , class XArray , class Weights = VectorX>

typedef IRegression<YArray, XArray, Weights> STK::AdditiveBSplineRegression< YArray, XArray, Weights >::Base

Definition at line 59 of file STK_AdditiveBSplineRegression.h.

◆ KnotsPosition

template<class YArray , class XArray , class Weights = VectorX>

typedef Regress::KnotsPosition STK::AdditiveBSplineRegression< YArray, XArray, Weights >::KnotsPosition

Definition at line 60 of file STK_AdditiveBSplineRegression.h.

Constructor & Destructor Documentation

◆ AdditiveBSplineRegression() [1/2]

template<class YArray , class XArray , class Weights >

STK::AdditiveBSplineRegression< YArray, XArray, Weights >::AdditiveBSplineRegression	(	YArray const *	p_y,
		XArray const *	p_x,
		int	nbControlPoints,
		int	degree = `3`,
		KnotsPosition const &	position = `Regress::uniformKnotsPositions_`
	)

Constructor.

Parameters

p_y	p-dimensional array of output to fit
p_x	d-dimensional array of predictor
nbControlPoints	number of control points of the spline
degree	degree of the BSpline basis
position	position of the knots to used

Definition at line 147 of file STK_AdditiveBSplineRegression.h.

                                                   : Base(p_y, p_x)
                                                    , nbControlPoints_(nbControlPoints)
                                                    , degree_(degree)
                                                    , position_(position)
                                                    , coefs_(p_x, nbControlPoints_, degree_, position_)
                                                    , controlPoints_()
{}

◆ AdditiveBSplineRegression() [2/2]

template<class YArray , class XArray , class Weights >

STK::AdditiveBSplineRegression< YArray, XArray, Weights >::AdditiveBSplineRegression	(	YArray const &	y,
		XArray const &	x,
		int	nbControlPoints,
		int	degree = `3`,
		KnotsPosition const &	position = `Regress::uniformKnotsPositions_`
	)

Constructor.

Parameters

y	p-dimensional array of output to fit
x	d-dimensional array of predictor
nbControlPoints	number of control points of the spline
degree	degree of the BSpline basis
position	position of the knots to used

Definition at line 169 of file STK_AdditiveBSplineRegression.h.

                                                   : Base(&y, &x)
                                                    , nbControlPoints_(nbControlPoints)
                                                    , degree_(degree)
                                                    , position_(position)
                                                    , coefs_(&x, nbControlPoints_, degree_, position_)
                                                    , controlPoints_()
{}

◆ ~AdditiveBSplineRegression()

template<class YArray , class XArray , class Weights = VectorX>

virtual STK::AdditiveBSplineRegression< YArray, XArray, Weights >::~AdditiveBSplineRegression ( )

inlinevirtual

virtual destructor.

Definition at line 92 of file STK_AdditiveBSplineRegression.h.

92{}

Member Function Documentation

◆ coefficients()

template<class YArray , class XArray , class Weights = VectorX>

ArrayXX const & STK::AdditiveBSplineRegression< YArray, XArray, Weights >::coefficients ( ) const

inline

This is a matrix of size (p_x_->range(), 0:lastControlPoints).

Returns: the coefficients of the B-spline curves

Definition at line 102 of file STK_AdditiveBSplineRegression.h.

102{ return coefs_.coefficients();}

STK::AdditiveBSplineCoefficients::coefficients

ArrayXX const & coefficients() const

give the computed coefficients of the B-spline curves.

Definition STK_AdditiveBSplineCoefficients.h:141

References STK::AdditiveBSplineCoefficients< Array >::coefficients(), and STK::AdditiveBSplineRegression< YArray, XArray, Weights >::coefs_.

◆ computeNbFreeParameter()

template<class YArray , class XArray , class Weights = VectorX>

virtual int STK::AdditiveBSplineRegression< YArray, XArray, Weights >::computeNbFreeParameter ( ) const

inlineprotectedvirtual

Returns: the number of parameter of the regression function

Implements STK::IRegression< YArray, XArray, Weights >.

Definition at line 135 of file STK_AdditiveBSplineRegression.h.

136 { return controlPoints_.sizeCols() * controlPoints_.sizeRows(); }

References STK::AdditiveBSplineRegression< YArray, XArray, Weights >::controlPoints_.

◆ controlPoints()

template<class YArray , class XArray , class Weights = VectorX>

YArray const & STK::AdditiveBSplineRegression< YArray, XArray, Weights >::controlPoints ( ) const

inline

Returns: the control points of the B-spline curves

Definition at line 98 of file STK_AdditiveBSplineRegression.h.

98{ return controlPoints_; }

References STK::AdditiveBSplineRegression< YArray, XArray, Weights >::controlPoints_.

◆ degree()

template<class YArray , class XArray , class Weights = VectorX>

int STK::AdditiveBSplineRegression< YArray, XArray, Weights >::degree ( ) const

inline

Returns: the degree of the B-spline curves

Definition at line 94 of file STK_AdditiveBSplineRegression.h.

94{ return degree_;}

References STK::AdditiveBSplineRegression< YArray, XArray, Weights >::degree_.

◆ extrapolate()

template<class YArray , class XArray , class Weights >

YArray STK::AdditiveBSplineRegression< YArray, XArray, Weights >::extrapolate ( XArray const & x ) const

virtual

Returns: The extrapolated values of y from the value x. Given the data set x will compute the values $y = \psi(x) \hat{\beta}$ where $\psi$ represents the B-spline basis functions and $\hat{beta}$ the estimated coefficients.

Parameters

x	the input data set

Implements STK::IRegression< YArray, XArray, Weights >.

Definition at line 250 of file STK_AdditiveBSplineRegression.h.

{
  YArray res = coefs_.extrapolate(x) * controlPoints_;
  return res;
}

References STK::MultidimRegression< Array, Weight >::coefs_.

◆ initializeStep()

template<class YArray , class XArray , class Weights >

bool STK::AdditiveBSplineRegression< YArray, XArray, Weights >::initializeStep ( )

protectedvirtual

compute the coefficients of the BSpline basis.

This method will be called in the base class IRegression::run()

Reimplemented from STK::IRegression< YArray, XArray, Weights >.

Definition at line 187 of file STK_AdditiveBSplineRegression.h.

{
  coefs_.setData(p_x_, nbControlPoints_, degree_, position_);
  if (!coefs_.run())
  {
    this->msg_error_ = coefs_.error();
    return false;
  }
  return true;
}

References STK::MultidimRegression< Array, Weight >::coefs_, STK::IRunnerBase::msg_error_, and STK::IRunnerSupervised< YArray_, XArray_, Weights_ >::p_x_.

◆ nbControlPoints()

template<class YArray , class XArray , class Weights = VectorX>

int STK::AdditiveBSplineRegression< YArray, XArray, Weights >::nbControlPoints ( ) const

inline

Returns: the number of control points of the B-spline curves

Definition at line 96 of file STK_AdditiveBSplineRegression.h.

96{ return nbControlPoints_;}

References STK::AdditiveBSplineRegression< YArray, XArray, Weights >::nbControlPoints_.

◆ predictionStep()

template<class YArray , class XArray , class Weights >

bool STK::AdditiveBSplineRegression< YArray, XArray, Weights >::predictionStep ( )

protectedvirtual

Compute the predicted outputs.

Implements STK::IRegression< YArray, XArray, Weights >.

Definition at line 237 of file STK_AdditiveBSplineRegression.h.

{
  predicted_ = coefs_.coefficients() * controlPoints_;
  return true;
}

References STK::MultidimRegression< Array, Weight >::coefs_, and STK::IRegression< Array, Array, Weight >::predicted_.

◆ regressionStep() [1/2]

template<class YArray , class XArray , class Weights >

bool STK::AdditiveBSplineRegression< YArray, XArray, Weights >::regressionStep ( )

protectedvirtual

Compute the regression function.

Implements STK::IRegression< YArray, XArray, Weights >.

Definition at line 200 of file STK_AdditiveBSplineRegression.h.

{
  // coefs_.coefficients() is Array2D
#ifdef STKUSELAPACK
  lapack::MultiLeastSquare<YArray, ArrayXX> reg(*p_y_, coefs_.coefficients(), false, false);
#else
  MultiLeastSquare<YArray, ArrayXX> reg(*p_y_, coefs_.coefficients(), false, false);
#endif
  if (!reg.run())
  {
    this->msg_error_ = reg.error();
    return false;
  }
  controlPoints_.move(reg.x());
  return true;
}

References STK::MultidimRegression< Array, Weight >::coefs_, STK::IRunnerBase::error(), STK::IRunnerBase::msg_error_, STK::IRunnerSupervised< YArray_, XArray_, Weights_ >::p_y_, and STK::IRegression< YArray, XArray, Weights >::run().

◆ regressionStep() [2/2]

template<class YArray , class XArray , class Weights >

bool STK::AdditiveBSplineRegression< YArray, XArray, Weights >::regressionStep ( Weights const & weights )

protectedvirtual

Compute the weighted regression.

Parameters

weights weights of the samples

Implements STK::IRegression< YArray, XArray, Weights >.

Definition at line 219 of file STK_AdditiveBSplineRegression.h.

{
#ifdef STKUSELAPACK
  lapack::MultiLeastSquare<YArray, ArrayXX> reg(*p_y_, coefs_.coefficients(), false, false);
#else
  MultiLeastSquare<YArray, ArrayXX> reg(*p_y_, coefs_.coefficients(), false, false);
#endif
  if (!reg.run(weights))
  {
    this->msg_error_ = reg.error();
    return false;
  }
  controlPoints_ = reg.x();
  return true;
}