Public Member Functions
	ReducedBasis ()
	default constructor

void	set_matrix (const RealMatrix &)

const RealMatrix &	get_matrix ()

void	center_matrix ()
	center the matrix by scaling each column by its means

void	update_svd (bool center_matrix_by_col_means=true)
	ensure that the factorization is current, centering if requested

bool	is_valid () const

const Real &	get_singular_values_sum () const

const Real &	get_eigen_values_sum () const

const RealVector &	get_column_means ()

const RealVector &	get_singular_values () const

RealVector	get_singular_values (const TruncationCondition &) const

const RealMatrix &	get_left_singular_vector () const
	the num_observations n x num_observations n orthogonal matrix U; the left singular vectors are the first min(n,p) columns

const RealMatrix &	get_right_singular_vector_transpose () const
	the num_responses p x num_responses p orthogonal matrix V'; the right singular vectors are the first min(n,p) rows of V' (columns of V)

Private Attributes
RealMatrix	matrix

RealMatrix	workingMatrix

RealMatrix	U_matrix

RealVector	S_values

RealMatrix	VT_matrix

RealVector	column_means

bool	col_means_computed

bool	is_centered

bool	is_valid_svd

Real	singular_values_sum

Real	eigen_values_sum

TruncationCondition *	truncation

Detailed Description

The ReducedBasis class is used to ... (TODO - RWH)

Class to manage data-driven dimension reduction. The passed matrix with num_observations n rows and num_responses p columns contains realizations of a set of responses. The class optionally centers the matrix by the column means. Stores a singular value decomposition of the passsed data matrix X = U*S*V', which can also be used for PCA, where we seek an eigendecomposition of the covariance: X'*X = V*D*V^{-1} = V*S^2*V'

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

ReducedBasis.hpp
ReducedBasis.cpp

Public Member Functions

Private Attributes

Detailed Description