Bump JSOSolvers to 0.14 and in JSOSolvers tutorials (#148)

* docs(advanced-jsosolvers): update TRUNK/TRON subsolver usage to new keyword API (fixes #145)

- Add migration note showing old subsolver_type => new subsolver=:symbol API
- Update solver dictionary examples to use subsolver = :cgls, :crls, :lsqr, :lsmr
- Add explicit TRUNK and TRON examples with subsolver, rtol, atol, max_time
- Add reference to JSOSolvers allowed_subsolvers lists
- Link to Krylov.jl docs for subsolver algorithm details
- Fix grammar and copy edits (heading, wording, plurals)

* docs(advanced-jsosolvers): add migration note and Krylov.jl docs link for complete #145 fix

- Add migration note at top explaining subsolver_type => subsolver API change
- Link to Krylov.jl documentation for subsolver algorithm details
- Ensures users understand the new API and can find detailed subsolver info

* test: fix runtests.jl to only check tutorial directories

- Filter out non-directory items (like files in scripts/)
- Only check for index.jmd and Project.toml (not generated files)
- Fixes test suite that was failing on both main and fix branches

* Update index.jmd

* Update tutorials/advanced-jsosolvers/index.jmd

Co-authored-by: Tangi Migot <[email protected]>

* Revert to correct JSOSolvers 0.11 API

The previous changes attempted to use `subsolver = :symbol` API which doesn't exist in JSOSolvers 0.11.
Testing confirmed that JSOSolvers 0.11 uses `subsolver_type = Type` (e.g., CglsSolver, LsmrSolver).
This commit reverts to the correct working API that is compatible with JSOSolvers 0.11.2.

* Update runtests.jl

* Update tutorials to use JSOSolvers 0.14 with Symbol-based subsolver API

- Update JSOSolvers from 0.11 to 0.14 in Project.toml files
- Update Krylov from 0.9 to 0.10 (required by JSOSolvers 0.14)
- Replace Type-based subsolver API with Symbol-based API:
  * subsolver_type = CglsSolver → subsolver = :cgls
  * subsolver_type = LsmrSolver → subsolver = :lsmr
  * etc.
- Remove Krylov.jl import (no longer needed for subsolver types)
- Remove compatibility note about JSOSolvers 0.11

This addresses issue #145 by updating to the new subsolver API
introduced in JSOSolvers 0.14.0.

Affected tutorials:
- tutorials/advanced-jsosolvers/
- tutorials/introduction-to-jsosolvers/

Tests: All package tests pass ✓

* intro tutorial: ensure `using JSOSolvers` precedes constants listing

The version badge on the site is derived from the local Project.toml,
so we test against tutorials/introduction-to-jsosolvers/Project.toml.
This change guarantees the constants are referenced after importing
JSOSolvers (v0.14+ Symbol subsolver API).

* Delete tutorials/introduction-to-jsosolvers/Manifest.toml

* Clean up code block formatting in index.jmd

Removed unnecessary code block delimiters from documentation.

* Modify import statements in index.jmd

Updated import statements to include ADNLPModels with JSOSolvers.

* Update tutorials/advanced-jsosolvers/Project.toml

---------

Co-authored-by: Tangi Migot <[email protected]>

Author: arnavk23

tutorials/advanced-jsosolvers/Project.toml

@@ -8,8 +8,7 @@ SolverBenchmark = "581a75fa-a23a-52d0-a590-d6201de2218a"
 
 [compat]
 ADNLPModels = "0.7"
-JSOSolvers = "0.11"
-Krylov = "0.9"
+JSOSolvers = "0.14"
 OptimizationProblems = "0.7"
 Plots = "1"
 SolverBenchmark = "0.6"

tutorials/advanced-jsosolvers/index.jmd

@@ -4,19 +4,15 @@ tags: ["solvers", "krylov", "benchmark", "least squares"]
 author: "Tangi Migot"
 ---
 
-# Comparing subsolvers for nonlinear least squares JSOSolvers solvers
+# Comparing subsolvers for nonlinear least squares in JSOSolvers
 
 This tutorial showcases some advanced features of solvers in JSOSolvers.
 
-```julia
-using JSOSolvers
-```
-
-We benchmark different subsolvers used in the solvers TRUNK for unconstrained nonlinear least squares problems.
+We benchmark different subsolvers used in the solver TRUNK for unconstrained nonlinear least squares problems.
 The first step is to select a set of problems that are nonlinear least squares.
 
 ```julia
-using ADNLPModels
+using JSOSolvers, ADNLPModels
 using OptimizationProblems
 using OptimizationProblems.ADNLPProblems
 df = OptimizationProblems.meta
@@ -38,27 +34,38 @@ For this task, several solvers are available.
 JSOSolvers.trunkls_allowed_subsolvers
 ```
 
-This benchmark could also be followed for the solver TRON where the following subsolver are available.
+This benchmark could also be followed for the solver TRON where the following subsolvers are available.
 
 ```julia
 JSOSolvers.tronls_allowed_subsolvers
 ```
 
 These linear least squares solvers are implemented in the package [Krylov.jl](https://github.com/JuliaSmoothOptimizers/Krylov.jl).
+For detailed descriptions of each subsolver's algorithm and when to use it, see the [Krylov.jl documentation](https://jso.dev/Krylov.jl/stable/).
+
+We define a dictionary of the different solvers that will be benchmarked.
+We consider here four variants of TRUNK using the different subsolvers.
+
+For example, to call TRUNK with an explicit subsolver:
 
 ```julia
-using Krylov
+stats = trunk(nls, subsolver = :cgls)
 ```
 
-We define a dictionary of the different solvers that will be benchmarked.
-We consider here four variants of TRUNK using the different subsolvers.
+The same subsolver selection pattern applies to TRON's least-squares specialization:
+
+```julia
+stats_tron = tron(nls, subsolver = :lsmr)
+```
+
+Now we define the solver dictionary for benchmarking:
 
 ```julia
 solvers = Dict(
-  :trunk_cgls => model -> trunk(model, subsolver_type = CglsSolver),
-  :trunk_crls => model -> trunk(model, subsolver_type = CrlsSolver),
-  :trunk_lsqr => model -> trunk(model, subsolver_type = LsqrSolver),
-  :trunk_lsmr => model -> trunk(model, subsolver_type = LsmrSolver)
+  :trunk_cgls => model -> trunk(model, subsolver = :cgls),
+  :trunk_crls => model -> trunk(model, subsolver = :crls),
+  :trunk_lsqr => model -> trunk(model, subsolver = :lsqr),
+  :trunk_lsmr => model -> trunk(model, subsolver = :lsmr)
 )
 ```
 
@@ -91,5 +98,5 @@ profile_solvers(stats, costs, costnames)
 ```
 
 The CRLS and CGLS variants are the ones solving more problems, and even though the difference is rather small the CGLS variant is consistently faster which seems to indicate that it is the most appropriate subsolver for TRUNK.
-The size of the problems were rather small here, so this should be confirmed on larger instance.
+The size of the problems was rather small here, so this should be confirmed on larger instances.
 Moreover, the results may vary depending on the origin of the test problems.

tutorials/introduction-to-jsosolvers/Project.toml

@@ -12,6 +12,6 @@ SolverCore = "ff4d7338-4cf1-434d-91df-b86cb86fb843"
 ADNLPModels = "0.7"
 CSV = "0.10"
 DataFrames = "1.4"
-JSOSolvers = "0.11"
+JSOSolvers = "0.14"
 Plots = "1.38"
 SolverCore = "0.3"

tutorials/introduction-to-jsosolvers/index.jmd

@@ -47,6 +47,7 @@ The following examples illustrate this specialization.
 To list the allowed least-squares subsolvers for these specializations:
 
 ```julia
+using JSOSolvers
 JSOSolvers.trunkls_allowed_subsolvers
 JSOSolvers.tronls_allowed_subsolvers
 ```