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SciML · May 26, 2024 · 3e833da · 3e833da
1 parent aa028b3
commit 3e833da
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Showing 2 changed files with 4 additions and 6 deletions.
diff --git a/docs/pages.jl b/docs/pages.jl
@@ -1,5 +1,5 @@
 pages = Any[
-    #"Home" => "home.md",
+    "Home" => "home.md",
     "Introduction to Catalyst" => Any[
         "introduction_to_catalyst/catalyst_for_new_julia_users.md",
         # "introduction_to_catalyst/introduction_to_catalyst.md"
@@ -26,13 +26,11 @@ pages = Any[
     ],
     "Model simulation" => Any[
         "model_simulation/simulation_introduction.md",
-        # Simulation introduction.
         "model_simulation/simulation_plotting.md",
         "model_simulation/simulation_structure_interfacing.md",
         "model_simulation/ensemble_simulations.md",
         # Stochastic simulation statistical analysis.
         "model_simulation/ode_simulation_performance.md",
-        # ODE Performance considerations/advice.
         # SDE Performance considerations/advice.
         # Jump Performance considerations/advice.
         # Finite state projection
@@ -50,7 +48,7 @@ pages = Any[
         # "inverse_problems/petab_ode_param_fitting.md",
         # ODE parameter fitting using Turing.
         # SDE/Jump fitting.
-        # "inverse_problems/behaviour_optimisation.md", # Currently fails due to an Optimization.jl issue.
+        "inverse_problems/behaviour_optimisation.md",
         "inverse_problems/structural_identifiability.md",
         # Practical identifiability.
         "inverse_problems/global_sensitivity_analysis.md",

diff --git a/docs/src/inverse_problems/behaviour_optimisation.md b/docs/src/inverse_problems/behaviour_optimisation.md
@@ -34,7 +34,7 @@ function pulse_amplitude(p, _)
     ps = Dict([:pX => p[1], :pY => p[2], :pZ => p[2]])
     u0_new = [:X => ps[:pX], :Y => ps[:pX]*ps[:pY], :Z => ps[:pZ]/ps[:pY]^2]
     oprob_local = remake(oprob; u0=  u0_new, p = ps)
-    sol = solve(oprob_local, verbose = false, maxiters = 10000)
+    sol = solve(oprob_local, Tsit5(); verbose = false, maxiters = 10000)
     SciMLBase.successful_retcode(sol) || return Inf
     return -(maximum(sol[:Z]) - sol[:Z][1])
 end
@@ -61,7 +61,7 @@ Finally, we plot a simulation using the found parameter set (stored in `opt_sol.
 ps_res = Dict([:pX => opt_sol.u[1], :pY => opt_sol.u[2], :pZ => opt_sol.u[2]])
 u0_res = [:X => ps_res[:pX], :Y => ps_res[:pX]*ps_res[:pY], :Z => ps_res[:pZ]/ps_res[:pY]^2]
 oprob_res = remake(oprob; u0 = u0_res, p = ps_res)
-sol_res = solve(oprob_res)
+sol_res = solve(oprob_res, Tsit5())
 plot(sol_res; idxs=:Z)
 ```
 For this model, it turns out that $Z$'s maximum pulse amplitude is equal to twice its steady state concentration. Hence, the maximisation of its pulse amplitude is equivalent to maximising its steady state concentration.