test: remove MTK as test dependency

Author: AayushSabharwal

Project.toml

@@ -71,7 +71,6 @@ LinearAlgebra = "1.10"
 Logging = "1.10"
 Makie = "0.20, 0.21"
 Markdown = "1.10"
-ModelingToolkit = "8.75, 9"
 PartialFunctions = "1.1"
 PrecompileTools = "1.2"
 Preferences = "1.3"
@@ -100,7 +99,6 @@ ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
 DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
 DelayDiffEq = "bcd4f6db-9728-5f36-b5f7-82caef46ccdb"
 ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
-ModelingToolkit = "961ee093-0014-501f-94e3-6117800e7a78"
 OrdinaryDiffEq = "1dea7af3-3e70-54e6-95c3-0bf5283fa5ed"
 PartialFunctions = "570af359-4316-4cb7-8c74-252c00c2016b"
 Pkg = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
@@ -118,4 +116,4 @@ UnicodePlots = "b8865327-cd53-5732-bb35-84acbb429228"
 Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
 
 [targets]
-test = ["Pkg", "Plots", "UnicodePlots", "PyCall", "PythonCall", "SafeTestsets", "Serialization", "Test", "StableRNGs", "StaticArrays", "StochasticDiffEq", "Aqua", "Zygote", "PartialFunctions", "DataFrames", "ModelingToolkit", "OrdinaryDiffEq", "ForwardDiff"]
+test = ["Pkg", "Plots", "UnicodePlots", "PyCall", "PythonCall", "SafeTestsets", "Serialization", "Test", "StableRNGs", "StaticArrays", "StochasticDiffEq", "Aqua", "Zygote", "PartialFunctions", "DataFrames", "OrdinaryDiffEq", "ForwardDiff"]

test/traits.jl

@@ -1,6 +1,5 @@
 using SciMLBase, Test
-using ModelingToolkit, OrdinaryDiffEq, DataFrames
-using ModelingToolkit: t_nounits as t, D_nounits as D
+using OrdinaryDiffEq, DataFrames, SymbolicIndexingInterface
 
 @test SciMLBase.Tables.isrowtable(ODESolution)
 @test SciMLBase.Tables.isrowtable(RODESolution)
@@ -10,13 +9,13 @@ using ModelingToolkit: t_nounits as t, D_nounits as D
 @test !SciMLBase.Tables.isrowtable(SciMLBase.QuadratureSolution)
 @test !SciMLBase.Tables.isrowtable(SciMLBase.OptimizationSolution)
 
-@variables x(t) = 1
-eqs = [D(x) ~ -x]
-@named sys = ODESystem(eqs, t)
-sys = complete(sys)
-prob = ODEProblem(sys)
-sol = solve(prob, Tsit5(), tspan = (0.0, 1.0))
+function rhs(u, p, t)
+    return -u
+end
+sys = SymbolCache([:x], Symbol[], :t)
+prob = ODEProblem(ODEFunction(rhs; sys), [1.0], (0.0, 1.0))
+sol = solve(prob, Tsit5())
 df = DataFrame(sol)
 @test size(df) == (length(sol.u), 2)
 @test df.timestamp == sol.t
-@test df.x == sol[x]
+@test df.x == sol[:x]