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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: