*
* Requires that the #state is LAPACKSupport::matrix, fills the data members
* #wr, #svd_u, and #svd_vt, and leaves the object in the #state
- * LAPACKSupport::svd.
- *
- * The singular value decomposition factorizes the provided matrix (A) into
- * three parts: U, sigma, and the transpose of V (V^T), such that A = U sigma
- * V^T. Sigma is a MxN matrix which contains the singular values of A on
- * the diagonal while all the other elements are zero. U is a MxM orthogonal
+ * LAPACKSupport::svd.
+ *
+ * The singular value decomposition factorizes the provided matrix (A) into
+ * three parts: U, sigma, and the transpose of V (V^T), such that A = U sigma
+ * V^T. Sigma is a MxN matrix which contains the singular values of A on
+ * the diagonal while all the other elements are zero. U is a MxM orthogonal
* matrix containing the left singular vectors corresponding to the singular
- * values of A. V is a NxN orthonal matrix containing the right singular
+ * values of A. V is a NxN orthonal matrix containing the right singular
* vectors corresponding the the singular values of A.
- *
- * Note that the variable #svd_vt contains the tranpose of V and can be accessed by get_svd_vt(), while U is accessed with get_svd_u().
+ *
+ * Note that the variable #svd_vt contains the tranpose of V and can be
+ * accessed by get_svd_vt(), while U is accessed with get_svd_u().
*/
void
compute_svd();
get_svd_u() const;
/**
- * Retrieve the matrix #svd_vt after compute_svd() or compute_inverse_svd() was
- * called.
+ * Retrieve the matrix #svd_vt after compute_svd() or compute_inverse_svd()
+ * was called.
*/
- inline const LAPACKFullMatrix<number>&
+ inline const LAPACKFullMatrix<number> &
get_svd_vt() const;
/**