Merge pull request #400 from SciML/vectorMTK

Scalarizing MTK parameters

Author: pogudingleb

ext/ModelingToolkitSIExt.jl

@@ -172,6 +172,20 @@ function clean_calls(funcs)
     return res
 end
 
+#------------------------------------------------------------------------------
+
+function scalarize(arr)
+    result = []
+    for a in arr
+        if typeof(a) <: SymbolicUtils.BasicSymbolic{<:Vector}
+            append!(result, collect(a))
+        else
+            push!(result, a)
+        end
+    end
+    return result
+end
+
 #------------------------------------------------------------------------------
 """
     function __mtk_to_si(de::ModelingToolkit.AbstractTimeDependentSystem, measured_quantities::Array{Tuple{String, SymbolicUtils.BasicSymbolic}})
@@ -209,7 +223,7 @@ function __mtk_to_si(
         filter(s -> !ModelingToolkit.isoutput(s), clean_calls(map(e -> e.lhs, diff_eqs)))
     all_funcs = collect(Set(clean_calls(ModelingToolkit.unknowns(de))))
     inputs = filter(s -> !ModelingToolkit.isoutput(s), setdiff(all_funcs, state_vars))
-    params = ModelingToolkit.parameters(de)
+    params = scalarize(ModelingToolkit.parameters(de))
     t = ModelingToolkit.arguments(clean_calls([diff_eqs[1].lhs])[1])[1]
     # very long if in order to avoid duplication
     params_from_measured_quantities = union(

test/extensions/modelingtoolkit.jl

@@ -427,6 +427,25 @@ if GROUP == "All" || GROUP == "ModelingToolkitSIExt"
         @test assess_local_identifiability(sys, measured_quantities = [x[1], x[2]]) ==
               correct
 
+        # Extension of https://github.com/SciML/StructuralIdentifiability.jl/issues/398
+        @parameters k[1:2] a
+        @variables (X(t))[1:2] (y(t))[1:2] [output = true]
+        eqs = [
+            D(X[1]) ~ k[1] - k[2] * X[2],
+            D(X[2]) ~ k[1] - k[2] * X[1],
+            y[1] ~ X[1] * X[2] + a,
+            y[2] ~ X[1] - X[2],
+        ]
+        @mtkbuild osys = ODESystem(eqs, t)
+        correct = OrderedDict(
+            X[1] => :locally,
+            X[2] => :locally,
+            k[1] => :locally,
+            k[2] => :globally,
+            a => :globally,
+        )
+        @test assess_identifiability(osys) == correct
+
         #------------------------------------
         # system from the SciML tutorial
         # https://docs.sciml.ai/ModelingToolkit/stable/tutorials/parameter_identifiability/