From: Menno Fraters Date: Thu, 12 Sep 2019 14:13:22 +0000 (-0700) Subject: Apply suggestions from code review X-Git-Tag: v9.2.0-rc1~1053^2~1 X-Git-Url: https://gitweb.dealii.org/cgi-bin/gitweb.cgi?a=commitdiff_plain;h=c55dc5e76fdec80b06df0f80bca050fc6337ac7c;p=dealii.git Apply suggestions from code review Apply documentation suggestions from Timo Heister for the compute_svd function. Co-Authored-By: Timo Heister --- diff --git a/include/deal.II/lac/lapack_full_matrix.h b/include/deal.II/lac/lapack_full_matrix.h index a539f43ec7..8910add669 100644 --- a/include/deal.II/lac/lapack_full_matrix.h +++ b/include/deal.II/lac/lapack_full_matrix.h @@ -818,14 +818,14 @@ public: * 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 + * 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 * vectors corresponding the the singular values of A. * - * Note that the variable #svd_vt contains the tranposed of V. + * 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();