From 56b7927ae7c8a370a6278d8b8ad2a4b177d5d6b7 Mon Sep 17 00:00:00 2001 From: Simon Carlson Date: Tue, 7 Feb 2023 10:28:30 +0100 Subject: [PATCH] Adding SimpleDFSane to docs --- docs/src/api/simplenonlinearsolve.md | 3 ++- docs/src/solvers/NonlinearSystemSolvers.md | 8 +++++--- 2 files changed, 7 insertions(+), 4 deletions(-) diff --git a/docs/src/api/simplenonlinearsolve.md b/docs/src/api/simplenonlinearsolve.md index 2e1853348..536a486ee 100644 --- a/docs/src/api/simplenonlinearsolve.md +++ b/docs/src/api/simplenonlinearsolve.md @@ -10,7 +10,8 @@ Falsi SimpleNewtonRaphson Broyden Klement -TrustRegion +SimpleTrustRegion Ridder Brent +SimpleDFSane ``` diff --git a/docs/src/solvers/NonlinearSystemSolvers.md b/docs/src/solvers/NonlinearSystemSolvers.md index 1040cd477..b4ef3a46d 100644 --- a/docs/src/solvers/NonlinearSystemSolvers.md +++ b/docs/src/solvers/NonlinearSystemSolvers.md @@ -23,7 +23,7 @@ then `NLSolveJL`'s `:anderson` can be a good choice. ## Full List of Methods !!! note - + For the full details on the capabilities and constructors of the different solvers, see the Detailed Solver APIs section! @@ -46,15 +46,17 @@ can be used directly to reduce dependencies and improve load times. SimpleNonlin methods excel at small problems and problems defined with static arrays. - `SimpleNewtonRaphson()`: A simplified implementation of the Newton-Raphson method. - - `Broyden()`: the classic Broyden's quasi-Newton method. + - `Broyden()`: The classic Broyden's quasi-Newton method. - `Klement()`: A quasi-Newton method due to Klement. It's supposed to be more efficient than Broyden's method, and it seems to be in the cases that have been tried, but more benchmarking is required. - `SimpleTrustRegion()`: A dogleg trust-region Newton method. Improved globalizing stability for more robust fitting over basic Newton methods, though potentially with a cost. + - `SimpleDFSane()`: A low-overhead implementation of the df-sane method for solving + large-scale nonlinear systems of equations. !!! note - + When used with certain types for the states `u` such as a `Number` or `StaticArray`, these solvers are very efficient and non-allocating. These implementations are thus well-suited for small systems of equations.