DiffEq plot variables by name

Author: jonniedie

Project.toml

@@ -1,7 +1,7 @@
 name = "ComponentArrays"
 uuid = "b0b7db55-cfe3-40fc-9ded-d10e2dbeff66"
 authors = ["Jonnie Diegelman <47193959+jonniedie@users.noreply.github.com>"]
-version = "0.11.6"
+version = "0.11.7"
 
 [deps]
 ArrayInterface = "4fba245c-0d91-5ea0-9b3e-6abc04ee57a9"

examples/adaptive_control_example.jl

@@ -175,13 +175,13 @@ function simulate(plant_fun, plant_ic;
     # Reference model tracking
     top = plot(
         sol,
-        vars=["reference_model[1]", "feedback_loop.sensor"],
+        vars=Symbol.(["reference_model[1]", "feedback_loop.sensor[1]"]),
         # legend=:right,
         title="Reference Model Tracking",
     )
 
     # Parameter estimate tracking
-    bottom = plot(sol, vars="feedback_loop.parameter_estimates")
+    bottom = plot(sol, vars=Symbol.(["feedback_loop.parameter_estimates.θr", "feedback_loop.parameter_estimates.θy"]))
     plot!(
         bottom,
         [tspan...], [θ_truth.r θ_truth.y; θ_truth.r θ_truth.y],

src/compat/scimlbase.jl

@@ -5,10 +5,6 @@ function SciMLBase.getsyms(sol::SciMLBase.AbstractODESolution{T,N,C}) where {T,N
     if SciMLBase.has_syms(sol.prob.f)
         return sol.prob.f.syms
     else
-        return labels(sol.u[1])
+        return Symbol.(labels(sol.u[1]))
     end
 end
-
-# A little bit of type piracy. Should probably make this a PR to DiffEqBase
-SciMLBase.cleansyms(syms::AbstractArray{<:String}) = SciMLBase.cleansyms.(syms)
-SciMLBase.cleansyms(syms::String) = syms