From 4bdc14a6fe80019eed8486ac8f70ba3c9e9e7eab Mon Sep 17 00:00:00 2001 From: Alexis Montoison Date: Sun, 16 Oct 2022 22:48:08 -0400 Subject: [PATCH 1/2] Change the category of USYMLQ and USYMQR --- docs/src/solvers/ln.md | 7 +++++++ docs/src/solvers/ls.md | 7 +++++++ docs/src/solvers/unsymmetric.md | 14 -------------- src/usymlq.jl | 2 +- src/usymqr.jl | 3 ++- 5 files changed, 17 insertions(+), 16 deletions(-) diff --git a/docs/src/solvers/ln.md b/docs/src/solvers/ln.md index c5396ffdd..b638b8247 100644 --- a/docs/src/solvers/ln.md +++ b/docs/src/solvers/ln.md @@ -36,3 +36,10 @@ craig! craigmr craigmr! ``` + +## USYMLQ + +```@docs +usymlq +usymlq! +``` diff --git a/docs/src/solvers/ls.md b/docs/src/solvers/ls.md index f77057d94..fecfbc417 100644 --- a/docs/src/solvers/ls.md +++ b/docs/src/solvers/ls.md @@ -36,3 +36,10 @@ lsqr! lsmr lsmr! ``` + +## USYMQR + +```@docs +usymqr +usymqr! +``` diff --git a/docs/src/solvers/unsymmetric.md b/docs/src/solvers/unsymmetric.md index e559145a2..2c596361a 100644 --- a/docs/src/solvers/unsymmetric.md +++ b/docs/src/solvers/unsymmetric.md @@ -16,20 +16,6 @@ qmr qmr! ``` -## USYMLQ - -```@docs -usymlq -usymlq! -``` - -## USYMQR - -```@docs -usymqr -usymqr! -``` - ## CGS ```@docs diff --git a/src/usymlq.jl b/src/usymlq.jl index 1d6d3e1d8..adb4f52e2 100644 --- a/src/usymlq.jl +++ b/src/usymlq.jl @@ -32,7 +32,7 @@ export usymlq, usymlq! USYMLQ can be warm-started from an initial guess `x0` where `kwargs` are the same keyword arguments as above. -Solve the linear system Ax = b of size m × n using the USYMLQ method. +USYMLQ determines the least-norm solution of the consistent linear system Ax = b of size m × n. USYMLQ is based on the orthogonal tridiagonalization process and requires two initial nonzero vectors `b` and `c`. The vector `c` is only used to initialize the process and a default value can be `b` or `Aᴴb` depending on the shape of `A`. diff --git a/src/usymqr.jl b/src/usymqr.jl index 003a46dc5..990422f24 100644 --- a/src/usymqr.jl +++ b/src/usymqr.jl @@ -31,7 +31,8 @@ export usymqr, usymqr! USYMQR can be warm-started from an initial guess `x0` where `kwargs` are the same keyword arguments as above. -Solve the linear system Ax = b of size m × n using USYMQR. +USYMQR solves the linear least-squares problem min ‖b - Ax‖² of size m × n. +If A is square and nonsingular, USYMQR solves Ax = b. USYMQR is based on the orthogonal tridiagonalization process and requires two initial nonzero vectors `b` and `c`. The vector `c` is only used to initialize the process and a default value can be `b` or `Aᴴb` depending on the shape of `A`. From fbe9412dd2fa8da08c28e406f6e967c95aa73c60 Mon Sep 17 00:00:00 2001 From: Alexis <35051714+amontoison@users.noreply.github.com> Date: Fri, 28 Oct 2022 11:58:24 -0400 Subject: [PATCH 2/2] Update src/usymqr.jl --- src/usymqr.jl | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/usymqr.jl b/src/usymqr.jl index 990422f24..5d9caa525 100644 --- a/src/usymqr.jl +++ b/src/usymqr.jl @@ -32,7 +32,7 @@ export usymqr, usymqr! USYMQR can be warm-started from an initial guess `x0` where `kwargs` are the same keyword arguments as above. USYMQR solves the linear least-squares problem min ‖b - Ax‖² of size m × n. -If A is square and nonsingular, USYMQR solves Ax = b. +USYMQR solves Ax = b if it is consistent. USYMQR is based on the orthogonal tridiagonalization process and requires two initial nonzero vectors `b` and `c`. The vector `c` is only used to initialize the process and a default value can be `b` or `Aᴴb` depending on the shape of `A`.