diff --git a/test/discrete_system.jl b/test/discrete_system.jl index 874d045aa9..0d215052d8 100644 --- a/test/discrete_system.jl +++ b/test/discrete_system.jl @@ -34,21 +34,16 @@ eqs = [S ~ S(k - 1) - infection * h, syss = structural_simplify(sys) @test syss == syss -for df in [ - DiscreteFunction(syss), - eval(DiscreteFunctionExpr(syss)) -] - - # iip - du = zeros(3) - u = collect(1:3) - p = MTKParameters(syss, [c, nsteps, δt, β, γ] .=> collect(1:5)) - df.f(du, u, p, 0) - @test du ≈ [0.01831563888873422, 0.9816849729159067, 4.999999388195359] - - # oop - @test df.f(u, p, 0) ≈ [0.01831563888873422, 0.9816849729159067, 4.999999388195359] -end +df = DiscreteFunction(syss) +# iip +du = zeros(3) +u = collect(1:3) +p = MTKParameters(syss, [c, nsteps, δt, β, γ] .=> collect(1:5)) +df.f(du, u, p, 0) +@test du ≈ [0.01831563888873422, 0.9816849729159067, 4.999999388195359] + +# oop +@test df.f(u, p, 0) ≈ [0.01831563888873422, 0.9816849729159067, 4.999999388195359] # Problem u0 = [S(k - 1) => 990.0, I(k - 1) => 10.0, R(k - 1) => 0.0] diff --git a/test/nonlinearsystem.jl b/test/nonlinearsystem.jl index 9475f24006..a315371141 100644 --- a/test/nonlinearsystem.jl +++ b/test/nonlinearsystem.jl @@ -30,7 +30,7 @@ eqs = [0 ~ σ * (y - x) * h, @test eval(toexpr(ns)) == ns test_nlsys_inference("standard", ns, (x, y, z), (σ, ρ, β)) @test begin - f = eval(generate_function(ns, [x, y, z], [σ, ρ, β])[2]) + f = generate_function(ns, [x, y, z], [σ, ρ, β], expression = Val{false})[2] du = [0.0, 0.0, 0.0] f(du, [1, 2, 3], [1, 2, 3]) du ≈ [1, -3, -7] diff --git a/test/odesystem.jl b/test/odesystem.jl index 78218c5107..a45ed99f35 100644 --- a/test/odesystem.jl +++ b/test/odesystem.jl @@ -54,42 +54,38 @@ jac = calculate_jacobian(de) jacfun = eval(jac_expr[2]) de = complete(de) -for f in [ - ODEFunction(de, [x, y, z], [σ, ρ, β], tgrad = true, jac = true), - eval(ODEFunctionExpr(de, [x, y, z], [σ, ρ, β], tgrad = true, jac = true)) -] - # system - @test f.sys === de - - # iip - du = zeros(3) - u = collect(1:3) - p = ModelingToolkit.MTKParameters(de, [σ, ρ, β] .=> 4.0:6.0) - f.f(du, u, p, 0.1) - @test du == [4, 0, -16] - - # oop - du = @SArray zeros(3) - u = SVector(1:3...) - p = ModelingToolkit.MTKParameters(de, SVector{3}([σ, ρ, β] .=> 4.0:6.0)) - @test f.f(u, p, 0.1) === @SArray [4.0, 0.0, -16.0] - - # iip vs oop - du = zeros(3) - g = similar(du) - J = zeros(3, 3) - u = collect(1:3) - p = ModelingToolkit.MTKParameters(de, [σ, ρ, β] .=> 4.0:6.0) - f.f(du, u, p, 0.1) - @test du == f(u, p, 0.1) - f.tgrad(g, u, p, t) - @test g == f.tgrad(u, p, t) - f.jac(J, u, p, t) - @test J == f.jac(u, p, t) -end +f = ODEFunction(de, [x, y, z], [σ, ρ, β], tgrad = true, jac = true) +# system +@test f.sys === de + +# iip +du = zeros(3) +u = collect(1:3) +p = ModelingToolkit.MTKParameters(de, [σ, ρ, β] .=> 4.0:6.0) +f.f(du, u, p, 0.1) +@test du == [4, 0, -16] + +# oop +du = @SArray zeros(3) +u = SVector(1:3...) +p = ModelingToolkit.MTKParameters(de, SVector{3}([σ, ρ, β] .=> 4.0:6.0)) +@test f.f(u, p, 0.1) === @SArray [4.0, 0.0, -16.0] + +# iip vs oop +du = zeros(3) +g = similar(du) +J = zeros(3, 3) +u = collect(1:3) +p = ModelingToolkit.MTKParameters(de, [σ, ρ, β] .=> 4.0:6.0) +f.f(du, u, p, 0.1) +@test du == f(u, p, 0.1) +f.tgrad(g, u, p, t) +@test g == f.tgrad(u, p, t) +f.jac(J, u, p, t) +@test J == f.jac(u, p, t) #check iip_config -f = eval(ODEFunctionExpr(de, [x, y, z], [σ, ρ, β], iip_config = (false, true))) +f = ODEFunction(de, [x, y, z], [σ, ρ, β], iip_config = (false, true)) du = zeros(3) u = collect(1:3) p = ModelingToolkit.MTKParameters(de, [σ, ρ, β] .=> 4.0:6.0) @@ -146,7 +142,7 @@ eqs = [D(x) ~ σ′ * (y - x), @named de = ODESystem(eqs, t) test_diffeq_inference("global iv-varying", de, t, (x, y, z), (σ′, ρ, β)) -f = eval(generate_function(de, [x, y, z], [σ′, ρ, β])[2]) +f = generate_function(de, [x, y, z], [σ′, ρ, β], expression = Val{false})[2] du = [0.0, 0.0, 0.0] f(du, [1.0, 2.0, 3.0], [x -> x + 7, 2, 3], 5.0) @test du ≈ [11, -3, -7] @@ -157,7 +153,7 @@ eqs = [D(x) ~ σ(t - 1) * (y - x), D(z) ~ x * y - β * z * κ] @named de = ODESystem(eqs, t) test_diffeq_inference("single internal iv-varying", de, t, (x, y, z), (σ, ρ, β)) -f = eval(generate_function(de, [x, y, z], [σ, ρ, β])[2]) +f = generate_function(de, [x, y, z], [σ, ρ, β], expression = Val{false})[2] du = [0.0, 0.0, 0.0] f(du, [1.0, 2.0, 3.0], [x -> x + 7, 2, 3], 5.0) @test du ≈ [11, -3, -7] @@ -165,7 +161,7 @@ f(du, [1.0, 2.0, 3.0], [x -> x + 7, 2, 3], 5.0) eqs = [D(x) ~ x + 10σ(t - 1) + 100σ(t - 2) + 1000σ(t^2)] @named de = ODESystem(eqs, t) test_diffeq_inference("many internal iv-varying", de, t, (x,), (σ,)) -f = eval(generate_function(de, [x], [σ])[2]) +f = generate_function(de, [x], [σ], expression = Val{false})[2] du = [0.0] f(du, [1.0], [t -> t + 2], 5.0) @test du ≈ [27561] @@ -218,11 +214,11 @@ eqs = [D(x) ~ -A * x, @named de = ODESystem(eqs, t) @test begin local f, du - f = eval(generate_function(de, [x, y], [A, B, C])[2]) + f = generate_function(de, [x, y], [A, B, C], expression = Val{false})[2] du = [0.0, 0.0] f(du, [1.0, 2.0], [1, 2, 3], 0.0) du ≈ [-1, -1 / 3] - f = eval(generate_function(de, [x, y], [A, B, C])[1]) + f = generate_function(de, [x, y], [A, B, C], expression = Val{false})[1] du ≈ f([1.0, 2.0], [1, 2, 3], 0.0) end diff --git a/test/steadystatesystems.jl b/test/steadystatesystems.jl index d29c809325..4f1b5ed063 100644 --- a/test/steadystatesystems.jl +++ b/test/steadystatesystems.jl @@ -17,7 +17,7 @@ for factor in [1e-1, 1e0, 1e10], ss_prob = SteadyStateProblem(de, u0, p) sol = solve(ss_prob, SSRootfind()).u[1] @test abs(sol^2 - factor * u0_p[2]) < 1e-8 - ss_prob = SteadyStateProblemExpr(de, u0, p) - sol_expr = solve(eval(ss_prob), SSRootfind()).u[1] + ss_prob = SteadyStateProblem(de, u0, p) + sol_expr = solve(ss_prob, SSRootfind()).u[1] @test all(x -> x == 0, sol - sol_expr) end