From be6d69eb6e4c088be3e93723c1d158c9add30519 Mon Sep 17 00:00:00 2001
From: Avik Pal <avikpal@mit.edu>
Date: Sun, 5 Nov 2023 22:15:36 -0500
Subject: [PATCH] Add to docs

---
 docs/src/api/nonlinearsolve.md                   |  2 ++
 docs/src/solvers/NonlinearLeastSquaresSolvers.md | 12 ++++--------
 test/23_test_problems.jl                         |  2 +-
 3 files changed, 7 insertions(+), 9 deletions(-)

diff --git a/docs/src/api/nonlinearsolve.md b/docs/src/api/nonlinearsolve.md
index 5da204f07..3e6009017 100644
--- a/docs/src/api/nonlinearsolve.md
+++ b/docs/src/api/nonlinearsolve.md
@@ -16,7 +16,9 @@ GeneralKlement
 ## Polyalgorithms
 
 ```@docs
+NonlinearSolvePolyAlgorithm
 FastShortcutNonlinearPolyalg
+FastShortcutNLLSPolyalg
 RobustMultiNewton
 ```
 
diff --git a/docs/src/solvers/NonlinearLeastSquaresSolvers.md b/docs/src/solvers/NonlinearLeastSquaresSolvers.md
index e414acdd8..1690671d9 100644
--- a/docs/src/solvers/NonlinearLeastSquaresSolvers.md
+++ b/docs/src/solvers/NonlinearLeastSquaresSolvers.md
@@ -7,7 +7,10 @@ Solves the nonlinear least squares problem defined by `prob` using the algorithm
 
 ## Recommended Methods
 
-`LevenbergMarquardt` is a good choice for most problems.
+The default method `FastShortcutNLLSPolyalg` is a good choice for most
+problems. It is a polyalgorithm that attempts to use a fast algorithm
+(`GaussNewton`) and if that fails it falls back to a more robust
+algorithm (`LevenbergMarquardt`).
 
 ## Full List of Methods
 
@@ -21,10 +24,3 @@ Solves the nonlinear least squares problem defined by `prob` using the algorithm
     problems.
   - `SimpleNewtonRaphson()`: Simple Gauss Newton Implementation with `QRFactorization` to
     solve a linear least squares problem at each step!
-
-## Example usage
-
-```julia
-using NonlinearSolve
-sol = solve(prob, LevenbergMarquardt())
-```
diff --git a/test/23_test_problems.jl b/test/23_test_problems.jl
index ee5b6b991..72843c42e 100644
--- a/test/23_test_problems.jl
+++ b/test/23_test_problems.jl
@@ -88,7 +88,7 @@ end
     alg_ops = (GeneralBroyden(; max_resets = 10),)
 
     broken_tests = Dict(alg => Int[] for alg in alg_ops)
-    broken_tests[alg_ops[1]] = [1, 2, 4, 5, 6, 11, 12, 13, 14, 22]
+    broken_tests[alg_ops[1]] = [1, 2, 4, 5, 6, 11, 12, 13, 14]
 
     test_on_library(problems, dicts, alg_ops, broken_tests)
 end