Increase size thresholds and fix typo in tutorial-symbolics

Author: ocots

docs/make.jl

@@ -61,6 +61,7 @@ makedocs(;
         repolink="https://" * repo_url,
         prettyurls=false,
         example_size_threshold=1_000_000,
+        size_threshold_warn=1_000_000,
         size_threshold=1_000_000,
         # size_threshold_ignore=[
         #     "tutorial-discretisation.md",

docs/src/assets/Manifest.toml

@@ -1,6 +1,6 @@
 # This file is machine-generated - editing it directly is not advised
 
-julia_version = "1.12.6"
+julia_version = "1.12.5"
 manifest_format = "2.0"
 project_hash = "1d73fc8b7306dbb42eb2a1fdd2ae0c8be50a6d19"
 
@@ -227,9 +227,9 @@ version = "0.18.7"
 
 [[deps.CTDirect]]
 deps = ["ADNLPModels", "CTModels", "CTSolvers", "DocStringExtensions", "ExaModels", "SolverCore", "SparseArrays", "SparseConnectivityTracer"]
-git-tree-sha1 = "db1699ffab2f31aeda5dbb61dfa9015773cb70fc"
+git-tree-sha1 = "a4d812f60412f47bf29e685a921d0d675f581d55"
 uuid = "790bbbee-bee9-49ee-8912-a9de031322d5"
-version = "1.0.6"
+version = "1.0.7-beta"
 
 [[deps.CTFlows]]
 deps = ["CTBase", "CTModels", "DocStringExtensions", "ForwardDiff", "LinearAlgebra", "MLStyle", "MacroTools"]

docs/src/tutorial-symbolics.md

@@ -230,7 +230,7 @@ end
 
 ### Solving the NLP
 
-The problem is transcribed into a nonlinear program using direct collocation on a uniform grid of 100 intervals, then handed to `Ipopt` via ``NLPModelsIpopt.jl``. We provide a simple initial guess for the state and control trajectories. See [the documentation](https://control-toolbox.org/OptimalControl.jl/stable/manual-solve.html) for more informations.
+The problem is transcribed into a nonlinear program using direct collocation on a uniform grid of 100 intervals, then handed to `Ipopt` via `NLPModelsIpopt.jl`. We provide a simple initial guess for the state and control trajectories. See [the documentation](@extref OptimalControl manual-solve) for more information.
 
 ```@example main
 initial_guess = @init cartpole begin
@@ -261,7 +261,6 @@ plot(p1, p2, p3, layout=(3, 1), size=(800, 700))
 
 The plots show the cart position ``x`` and pendulum angle ``\theta``, the corresponding velocities, and the optimal control force ``u`` required to stabilize the system back to its initial state within 2 seconds.
 
-
 ### Animation
 
 The animation below shows the cart-pole evolving along the optimal limit-cycle trajectory. The blue cart slides on the horizontal rail while the pendulum swings around the upright equilibrium.