fixup! feat: support callable parameters

SciML · Sep 16, 2024 · ab2788f · ab2788f
1 parent 6d2aed8
commit ab2788f
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Showing 2 changed files with 44 additions and 21 deletions.
diff --git a/Project.toml b/Project.toml
@@ -77,6 +77,7 @@ ChainRulesCore = "1"
 Combinatorics = "1"
 Compat = "3.42, 4"
 ConstructionBase = "1"
+DataInterpolations = "6.4"
 DataStructures = "0.17, 0.18"
 DeepDiffs = "1"
 DiffEqBase = "6.103.0"
@@ -131,6 +132,7 @@ julia = "1.9"
 AmplNLWriter = "7c4d4715-977e-5154-bfe0-e096adeac482"
 BenchmarkTools = "6e4b80f9-dd63-53aa-95a3-0cdb28fa8baf"
 ControlSystemsBase = "aaaaaaaa-a6ca-5380-bf3e-84a91bcd477e"
+DataInterpolations = "82cc6244-b520-54b8-b5a6-8a565e85f1d0"
 DeepDiffs = "ab62b9b5-e342-54a8-a765-a90f495de1a6"
 DelayDiffEq = "bcd4f6db-9728-5f36-b5f7-82caef46ccdb"
 ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
@@ -156,4 +158,4 @@ Sundials = "c3572dad-4567-51f8-b174-8c6c989267f4"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [targets]
-test = ["AmplNLWriter", "BenchmarkTools", "ControlSystemsBase", "DelayDiffEq", "NonlinearSolve", "ForwardDiff", "Ipopt", "Ipopt_jll", "ModelingToolkitStandardLibrary", "Optimization", "OptimizationOptimJL", "OptimizationMOI", "OrdinaryDiffEq", "Random", "ReferenceTests", "SafeTestsets", "StableRNGs", "Statistics", "SteadyStateDiffEq", "Test", "StochasticDiffEq", "Sundials", "StochasticDelayDiffEq", "Pkg", "JET"]
+test = ["AmplNLWriter", "BenchmarkTools", "ControlSystemsBase", "DataInterpolations", "DelayDiffEq", "NonlinearSolve", "ForwardDiff", "Ipopt", "Ipopt_jll", "ModelingToolkitStandardLibrary", "Optimization", "OptimizationOptimJL", "OptimizationMOI", "OrdinaryDiffEq", "Random", "ReferenceTests", "SafeTestsets", "StableRNGs", "Statistics", "SteadyStateDiffEq", "Test", "StochasticDiffEq", "Sundials", "StochasticDelayDiffEq", "Pkg", "JET"]
diff --git a/test/split_parameters.jl b/test/split_parameters.jl
@@ -1,6 +1,7 @@
 using ModelingToolkit, Test
 using ModelingToolkitStandardLibrary.Blocks
 using OrdinaryDiffEq
+using DataInterpolations
 using BlockArrays: BlockedArray
 using ModelingToolkit: t_nounits as t, D_nounits as D
 using ModelingToolkit: MTKParameters, ParameterIndex, NONNUMERIC_PORTION
@@ -222,24 +223,44 @@ S = get_sensitivity(closed_loop, :u)
 end
 
 @testset "Callable parameters" begin
-    _f1(x) = 2x
-    struct Foo end
-    (::Foo)(x) = 3x
-    @variables x(t)
-    @parameters fn(..) = _f1
-    @mtkbuild sys = ODESystem(D(x) ~ fn(x), t, [x], [fn])
-    @test is_parameter(sys, fn)
-    @test ModelingToolkit.defaults(sys)[fn] == _f1
-
-    prob = ODEProblem(sys, [x => 1.0], (0.0, 1.0))
-    @test_broken @inferred prob.ps[fn]
-    @test_broken @inferred prob.f(prob.u0, prob.p, prob.tspan[1])
-    sol = solve(prob; abstol = 1e-10, reltol = 1e-10)
-    @test sol.u[end][] ≈ exp(2.0)
-
-    prob = ODEProblem(sys, [x => 1.0], (0.0, 1.0), [fn => Foo()])
-    @test_broken @inferred prob.ps[fn]
-    @test_broken @inferred prob.f(prob.u0, prob.p, prob.tspan[1])
-    sol = solve(prob; abstol = 1e-10, reltol = 1e-10)
-    @test sol.u[end][] ≈ exp(3.0)
+    @testset "As FunctionWrapper" begin
+        _f1(x) = 2x
+        struct Foo end
+        (::Foo)(x) = 3x
+        @variables x(t)
+        @parameters fn(::Real) = _f1
+        @mtkbuild sys = ODESystem(D(x) ~ fn(t), t)
+        @test is_parameter(sys, fn)
+        @test ModelingToolkit.defaults(sys)[fn] == _f1
+
+        getter = getp(sys, fn)
+        prob = ODEProblem(sys, [x => 1.0], (0.0, 1.0))
+        @inferred getter(prob)
+        # cannot be inferred better since `FunctionWrapper` is only known to return `Real`
+        @inferred Vector{<:Real} prob.f(prob.u0, prob.p, prob.tspan[1])
+        sol = solve(prob, Tsit5(); abstol = 1e-10, reltol = 1e-10)
+        @test sol.u[end][] ≈ 2.0
+
+        prob = ODEProblem(sys, [x => 1.0], (0.0, 1.0), [fn => Foo()])
+        @inferred getter(prob)
+        @inferred Vector{<:Real} prob.f(prob.u0, prob.p, prob.tspan[1])
+        sol = solve(prob; abstol = 1e-10, reltol = 1e-10)
+        @test sol.u[end][] ≈ 2.5
+    end
+
+    @testset "Concrete function type" begin
+        ts = 0.0:0.1:1.0
+        interp = LinearInterpolation(ts .^ 2, ts; extrapolate = true)
+        @variables x(t)
+        @parameters (fn::typeof(interp))(..)
+        @mtkbuild sys = ODESystem(D(x) ~ fn(x), t)
+        @test is_parameter(sys, fn)
+        getter = getp(sys, fn)
+        prob = ODEProblem(sys, [x => 1.0], (0.0, 1.0), [fn => interp])
+        @inferred getter(prob)
+        @inferred prob.f(prob.u0, prob.p, prob.tspan[1])
+        @test_nowarn sol = solve(prob, Tsit5())
+        @test_nowarn prob.ps[fn] = LinearInterpolation(ts .^ 3, ts; extrapolate = true)
+        @test_nowarn sol = solve(prob)
+    end
 end