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ReducedBasis Class Reference

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: