From 5223e94717344fb8a0fd797f1d477d03f4941824 Mon Sep 17 00:00:00 2001
From: Tangi Migot <tangi.migot@gmail.com>
Date: Fri, 4 Oct 2024 08:01:09 -0400
Subject: [PATCH] Add documentation for `isnls` in tuto (#182)

* Add documentation for `isnls` in tuto
---
 docs/Project.toml                             |  1 +
 ...0-nls.md => 20-nonlinear-least-squares.md} | 34 +++++++++++++++++++
 2 files changed, 35 insertions(+)
 rename docs/src/{20-nls.md => 20-nonlinear-least-squares.md} (81%)

diff --git a/docs/Project.toml b/docs/Project.toml
index 29d9bbcb..b4aa29eb 100644
--- a/docs/Project.toml
+++ b/docs/Project.toml
@@ -3,6 +3,7 @@ ADNLPModels = "54578032-b7ea-4c30-94aa-7cbd1cce6c9a"
 CaNNOLeS = "5a1c9e79-9c58-5ec0-afc4-3298fdea2875"
 DCISolver = "bee2e536-65f6-11e9-3844-e5bb4c9c55c9"
 Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
+ExpressionTreeForge = "93090adf-0e31-445f-8c8f-44d91f61d7ad"
 GR = "28b8d3ca-fb5f-59d9-8090-bfdbd6d07a71"
 JSOSolvers = "10dff2fc-5484-5881-a0e0-c90441020f8a"
 JSOSuite = "ed6ae0be-a024-11e9-2788-05dbf8cd15d9"
diff --git a/docs/src/20-nls.md b/docs/src/20-nonlinear-least-squares.md
similarity index 81%
rename from docs/src/20-nls.md
rename to docs/src/20-nonlinear-least-squares.md
index 2e492fa3..6fe23ba6 100644
--- a/docs/src/20-nls.md
+++ b/docs/src/20-nonlinear-least-squares.md
@@ -82,6 +82,40 @@ nls = MathOptNLSModel(model, [F1, F2], name="Ju-Rosenbrock")
 stats = minimize(nls)
 ```
 
+### JSOSuite automatic detection
+
+The package can be used to try detecting NLS-pattern in a model.
+
+```@example autodetection
+using ADNLPModels, JSOSuite
+f(x) = (x[2] - x[1]^3)^2 + (x[1] - 1)^2
+x0 = [-1.2; 1.0]
+nlp = ADNLPModel(f, x0)
+stats_nlp = minimize(nlp)
+```
+
+The function `isnls` requires the package [ExpressionTreeForge.jl](https://github.com/JuliaSmoothOptimizers/ExpressionTreeForge.jl).
+In this example, it detects that the objective function is a nonlinear least squares.
+
+```@example autodetection
+using ExpressionTreeForge
+JSOSuite.isnls(nlp)
+```
+
+Therefore, defining an `ADNLSModel` might improve the solver's behavior.
+
+```@example autodetection
+F(x) = [x[2] - x[1]^3, x[1] - 1]
+x0 = [-1.2; 1.0]
+nls = ADNLSModel(F, x0, 2)
+stats_nls = minimize(nls)
+```
+
+```@example autodetection
+using NLPModels
+(neval_obj(nlp), neval_obj(nls))
+```
+
 ## Find a feasible point of an optimization problem or solve a nonlinear system
 
 We show here how to find the feasible point of a given model.