Merge pull request #2734 from oscardssmith/os/start-upgrade-to-MTK-v10

start upgrade to MTK@10

Author: oscardssmith

lib/OrdinaryDiffEqBDF/Project.toml

@@ -63,7 +63,6 @@ DiffEqDevTools = "f3b72e0c-5b89-59e1-b016-84e28bfd966d"
 Enzyme = "7da242da-08ed-463a-9acd-ee780be4f1d9"
 ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
 LinearSolve = "7ed4a6bd-45f5-4d41-b270-4a48e9bafcae"
-NonlinearSolve = "8913a72c-1f9b-4ce2-8d82-65094dcecaec"
 ODEProblemLibrary = "fdc4e326-1af4-4b90-96e7-779fcce2daa5"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 SafeTestsets = "1bc83da4-3b8d-516f-aca4-4fe02f6d838f"
@@ -73,4 +72,4 @@ JET = "c3a54625-cd67-489e-a8e7-0a5a0ff4e31b"
 Aqua = "4c88cf16-eb10-579e-8560-4a9242c79595"
 
 [targets]
-test = ["DiffEqDevTools", "ForwardDiff", "Random", "SafeTestsets", "Test", "ODEProblemLibrary", "StaticArrays", "Enzyme", "LinearSolve", "JET", "Aqua", "NonlinearSolve"]
+test = ["DiffEqDevTools", "ForwardDiff", "Random", "SafeTestsets", "Test", "ODEProblemLibrary", "StaticArrays", "Enzyme", "LinearSolve", "JET", "Aqua"]

lib/OrdinaryDiffEqBDF/test/inference_tests.jl

@@ -1,4 +1,4 @@
-using OrdinaryDiffEqBDF, NonlinearSolve, Test
+using OrdinaryDiffEqBDF, Test
 
 prob = ODEProblem((du,u,p,t) -> du .= u, zeros(1), (0.0,1.0))
 nlalg = FBDF(autodiff=false, nlsolve = OrdinaryDiffEqBDF.NonlinearSolveAlg(TrustRegion(autodiff = AutoFiniteDiff())))

lib/OrdinaryDiffEqFIRK/test/ode_firk_tests.jl

@@ -44,7 +44,7 @@ sys = prob_ode_vanderpol.f.sys
 
 # test adaptivity
 for iip in (true, false)
-    vanstiff = ODEProblem{iip}(sys, [sys.y => 0, sys.x => sqrt(3)], (0.0, 1.0), [sys.μ => 1e6])
+    vanstiff = ODEProblem{iip}(sys, [sys.y => 0, sys.x => sqrt(3), sys.μ => 1e6], (0.0, 1.0))
     sol = solve(vanstiff, RadauIIA5())
     if iip
         @test sol.stats.naccept + sol.stats.nreject > sol.stats.njacs # J reuse
@@ -69,7 +69,7 @@ end
 
 # test adaptivity
 for iip in (true, false)
-    vanstiff = ODEProblem{iip}(sys, [sys.y => 0, sys.x => sqrt(3)], (0.0, 1.0), [sys.μ => 1e6])
+    vanstiff = ODEProblem{iip}(sys, [sys.y => 0, sys.x => sqrt(3), sys.μ => 1e6], (0.0, 1.0))
     sol = solve(vanstiff, RadauIIA3())
     if iip
         @test sol.stats.naccept + sol.stats.nreject > sol.stats.njacs # J reuse

test/interface/dae_initialize_integration.jl

@@ -7,12 +7,12 @@ single_neuron_eqs = [
     D(v) ~ min(max(-2 - v, v), 2 - v) - w + F, # add the flux term
     D(w) ~ e * (v - g * w + b)
 ]
-n1 = ODESystem(single_neuron_eqs, t, [v, w, F], [g, e, b], name = :n1)
-n2 = ODESystem(single_neuron_eqs, t, [v, w, F], [g, e, b], name = :n2)
+n1 = System(single_neuron_eqs, t, [v, w, F], [g, e, b], name = :n1)
+n2 = System(single_neuron_eqs, t, [v, w, F], [g, e, b], name = :n2)
 @parameters Di Dk
 connections = [0 ~ n1.F - Di * Dk * max(n1.v - n2.v, 0)
                0 ~ n2.F - Di * max(n2.v - n1.v, 0)]
-connected = ODESystem(connections, t, [], [Di, Dk], systems = [n1, n2], name = :connected)
+connected = System(connections, t, [], [Di, Dk], systems = [n1, n2], name = :connected)
 connected = complete(connected)
 
 u0 = [
@@ -82,7 +82,7 @@ sol = solve(prob, Rodas5P(), dt = 1e-10)
     # https://github.com/SciML/ModelingToolkit.jl/issues/3504
     @variables x(t) y(t)
     @parameters c1 c2
-    @mtkbuild sys = ODESystem([D(x) ~ -c1 * x + c2 * y, D(y) ~ c1 * x - c2 * y], t)
+    @mtkbuild sys = System([D(x) ~ -c1 * x + c2 * y, D(y) ~ c1 * x - c2 * y], t)
     prob = ODEProblem(sys, [1.0, 2.0], (0.0, 1.0), [c1 => 1.0, c2 => 2.0])
     @test prob.ps[Initial(x)] ≈ 1.0
     @test prob.ps[Initial(y)] ≈ 2.0

test/interface/jacobian_tests.jl

@@ -56,7 +56,7 @@ end
 
 prob = ODEProblem(lotka, [1.0, 1.0], (0.0, 1.0), [1.5, 1.0, 3.0, 1.0])
 de = ModelingToolkit.modelingtoolkitize(prob) |> complete
-prob2 = ODEProblem(de; jac = true)
+prob2 = ODEProblem(de, [], prob.tspan; jac = true)
 
 sol = solve(prob, TRBDF2())
 

test/interface/stiffness_detection_test.jl

@@ -3,7 +3,7 @@ import ODEProblemLibrary: prob_ode_vanderpol
 using ForwardDiff: Dual
 
 sys = prob_ode_vanderpol.f.sys
-prob1 = ODEProblem(sys, [sys.y => 0, sys.x => 2.0], (0.0, 6), [sys.μ => inv(0.003)])
+prob1 = ODEProblem(sys, [sys.y => 0, sys.x => 2.0, sys.μ => inv(0.003)], (0.0, 6))
 function __van(du, u, p, t)
     μ = p[1]
     du[1] = μ * ((1 - u[2]^2) * u[1] - u[2])