feat: add utility function for obtaining defaults and guesses

Author: AayushSabharwal

src/systems/abstractsystem.jl

@@ -1020,6 +1020,10 @@ function defaults(sys::AbstractSystem)
     isempty(systems) ? defs : mapfoldr(namespace_defaults, merge, systems; init = defs)
 end
 
+function defaults_and_guesses(sys::AbstractSystem)
+    merge(guesses(sys), defaults(sys))
+end
+
 unknowns(sys::Union{AbstractSystem, Nothing}, v) = renamespace(sys, v)
 for vType in [Symbolics.Arr, Symbolics.Symbolic{<:AbstractArray}]
     @eval unknowns(sys::AbstractSystem, v::$vType) = renamespace(sys, v)

test/downstream/linearize.jl

@@ -121,13 +121,13 @@ lsyss, _ = ModelingToolkit.linearize_symbolic(pid, [reference.u, measurement.u],
     [ctr_output.u])
 
 @test substitute(
-    lsyss.A, merge(ModelingToolkit.defaults(pid), ModelingToolkit.guesses(pid))) == lsys.A
+    lsyss.A, ModelingToolkit.defaults_and_guesses(pid)) == lsys.A
 @test substitute(
-    lsyss.B, merge(ModelingToolkit.defaults(pid), ModelingToolkit.guesses(pid))) == lsys.B
+    lsyss.B, ModelingToolkit.defaults_and_guesses(pid)) == lsys.B
 @test substitute(
-    lsyss.C, merge(ModelingToolkit.defaults(pid), ModelingToolkit.guesses(pid))) == lsys.C
+    lsyss.C, ModelingToolkit.defaults_and_guesses(pid)) == lsys.C
 @test substitute(
-    lsyss.D, merge(ModelingToolkit.defaults(pid), ModelingToolkit.guesses(pid))) == lsys.D
+    lsyss.D, ModelingToolkit.defaults_and_guesses(pid)) == lsys.D
 
 # Test with the reverse desired unknown order as well to verify that similarity transform and reoreder_unknowns really works
 lsys = ModelingToolkit.reorder_unknowns(lsys, unknowns(ssys), reverse(desired_order))

test/input_output_handling.jl

@@ -145,7 +145,7 @@ if VERSION >= v"1.8" # :opaque_closure not supported before
         x = randn(size(A, 1))
         u = randn(size(B, 2))
         p = getindex.(
-            Ref(merge(ModelingToolkit.defaults(ssys), ModelingToolkit.guesses(ssys))),
+            Ref(ModelingToolkit.defaults_and_guesses(ssys)),
             parameters(ssys))
         y1 = obsf(x, u, p, 0)
         y2 = C * x + D * u