Update to ModelingToolkit v9

Author: ChrisRackauckas

lib/ODEProblemLibrary/Project.toml

@@ -15,7 +15,7 @@ RuntimeGeneratedFunctions = "7e49a35a-f44a-4d26-94aa-eba1b4ca6b47"
 Aqua = "0.5"
 DiffEqBase = "6"
 Latexify = "0.15, 0.16"
-ModelingToolkit = "7,8"
+ModelingToolkit = "9"
 RuntimeGeneratedFunctions = "0.5"
 julia = "1.6"
 

lib/ODEProblemLibrary/src/ODEProblemLibrary.jl

@@ -5,6 +5,7 @@ module ODEProblemLibrary
 using DiffEqBase
 using Latexify
 using ModelingToolkit
+using ModelingToolkit: t_nounits as t, D_nounits as D
 
 using LinearAlgebra
 using Markdown

lib/ODEProblemLibrary/src/ode_simple_nonlinear_prob.jl

@@ -49,12 +49,12 @@ prob_ode_fitzhughnagumo = ODEProblem(fitz, [1.0; 1.0], (0.0, 1.0),
     (0.7, 0.8, 1 / 12.5, 0.5))
 
 #Van der Pol Equations
-@parameters t μ
+@parameters μ
 @variables x(t) y(t)
-D = Differential(t)
+
 eqs = [D(y) ~ μ * ((1 - x^2) * y - x),
     D(x) ~ y]
-de = ODESystem(eqs; name = :van_der_pol)
+de = ODESystem(eqs,t; name = :van_der_pol) |> structural_simplify |> complete
 van = ODEFunction(de, [y, x], [μ], jac = true, eval_module = @__MODULE__)
 
 """
@@ -90,13 +90,13 @@ Stiff parameters.
 prob_ode_vanderpol_stiff = ODEProblem(van, [0; sqrt(3)], (0.0, 1.0), 1e6)
 
 # ROBER
-@parameters t k₁ k₂ k₃
+@parameters k₁ k₂ k₃
 @variables y₁(t) y₂(t) y₃(t)
-D = Differential(t)
+
 eqs = [D(y₁) ~ -k₁ * y₁ + k₃ * y₂ * y₃,
     D(y₂) ~ k₁ * y₁ - k₂ * y₂^2 - k₃ * y₂ * y₃,
     D(y₃) ~ k₂ * y₂^2]
-de = ODESystem(eqs; name = :rober)
+de = ODESystem(eqs,t; name = :rober) |> structural_simplify |> complete
 rober = ODEFunction(de, [y₁, y₂, y₃], [k₁, k₂, k₃], jac = true, eval_module = @__MODULE__)
 
 """
@@ -171,13 +171,13 @@ prob_ode_threebody = ODEProblem(threebody,
 
 # Rigid Body Equations
 
-@parameters t I₁ I₂ I₃
+@parameters I₁ I₂ I₃
 @variables y₁(t) y₂(t) y₃(t)
-D = Differential(t)
+
 eqs = [D(y₁) ~ I₁ * y₂ * y₃,
     D(y₂) ~ I₂ * y₁ * y₃,
     D(y₃) ~ I₃ * y₁ * y₂]
-de = ODESystem(eqs; name = :rigid_body)
+de = ODESystem(eqs,t; name = :rigid_body) |> structural_simplify |> complete
 rigid = ODEFunction(de, [y₁, y₂, y₃], [I₁, I₂, I₃], jac = true, eval_module = @__MODULE__)
 
 """
@@ -348,9 +348,9 @@ mm_f = ODEFunction(mm_linear; analytic = (u0, p, t) -> exp(inv(MM_linear) * mm_A
     mass_matrix = MM_linear)
 prob_ode_mm_linear = ODEProblem(mm_f, rand(4), (0.0, 1.0))
 
-@parameters t p1 p2 p3 p4 p5 p6 p7 p8 p9 p10 p11 p12
+@parameters p1 p2 p3 p4 p5 p6 p7 p8 p9 p10 p11 p12
 @variables y1(t) y2(t) y3(t) y4(t) y5(t) y6(t) y7(t) y8(t)
-D = Differential(t)
+
 eqs = [D(y1) ~ -p1 * y1 + p2 * y2 + p3 * y3 + p4,
     D(y2) ~ p1 * y1 - p5 * y2,
     D(y3) ~ -p6 * y3 + p2 * y4 + p7 * y5,
@@ -360,7 +360,7 @@ eqs = [D(y1) ~ -p1 * y1 + p2 * y2 + p3 * y3 + p4,
             p2 * y6 + p11 * y7,
     D(y7) ~ p10 * y6 * y8 - p12 * y7,
     D(y8) ~ -p10 * y6 * y8 + p12 * y7]
-de = ODESystem(eqs; name = :hires)
+de = ODESystem(eqs,t; name = :hires) |> structural_simplify |> complete
 hires = ODEFunction(de, [y1, y2, y3, y4, y5, y6, y7, y8],
     [p1, p2, p3, p4, p5, p6, p7, p8, p9, p10, p11, p12],
     jac = true)
@@ -396,13 +396,13 @@ prob_ode_hires = ODEProblem(hires, u0, (0.0, 321.8122),
         10.03, 0.035, 1.12, 1.745, 280.0,
         0.69, 1.81))
 
-@parameters t p1 p2 p3
+@parameters p1 p2 p3
 @variables y1(t) y2(t) y3(t)
-D = Differential(t)
+
 eqs = [D(y1) ~ p1 * (y2 + y1 * (1 - p2 * y1 - y2)),
     D(y2) ~ (y3 - (1 + y1) * y2) / p1,
     D(y3) ~ p3 * (y1 - y3)]
-de = ODESystem(eqs; name = :orego)
+de = ODESystem(eqs,t; name = :orego) |> structural_simplify |> complete
 jac = calculate_jacobian(de)
 orego = ODEFunction(de, [y1, y2, y3], [p1, p2, p3], jac = true, eval_module = @__MODULE__)
 

lib/ODEProblemLibrary/src/strange_attractors.jl

@@ -3,15 +3,15 @@
 # Opted for the equations as reported in papers
 
 # Thomas
-@parameters t b=0.208186
+@parameters b=0.208186
 @variables x(t)=1 y(t)=0 z(t)=0
-D = Differential(t)
+
 
 eqs = [D(x) ~ sin(y) - b * x,
     D(y) ~ sin(z) - b * y,
     D(z) ~ sin(x) - b * z]
 
-@named thomas = ODESystem(eqs)
+@mtkbuild thomas = ODESystem(eqs,t)
 
 """
 Thomas' cyclically symmetric attractor equations
@@ -27,15 +27,15 @@ $(latexify(thomas))
 prob_ode_thomas = ODEProblem(thomas, [], (0.0, 1.0))
 
 # Lorenz
-@parameters t σ=10 ρ=28 β=8 / 3
+@parameters σ=10 ρ=28 β=8 / 3
 @variables x(t)=1 y(t)=0 z(t)=0
-D = Differential(t)
+
 
 eqs = [D(x) ~ σ * (y - x),
     D(y) ~ x * (ρ - z) - y,
     D(z) ~ x * y - β * z]
 
-@named lorenz = ODESystem(eqs)
+@mtkbuild lorenz = ODESystem(eqs,t)
 
 """
 Lorenz equations
@@ -51,15 +51,15 @@ $(latexify(lorenz))
 prob_ode_lorenz = ODEProblem(lorenz, [], (0.0, 1.0))
 
 # Aizawa
-@parameters t a=0.95 b=0.7 c=0.6 d=3.5 e=0.25 f=0.1
+@parameters a=0.95 b=0.7 c=0.6 d=3.5 e=0.25 f=0.1
 @variables x(t)=1 y(t)=0 z(t)=0
-D = Differential(t)
+
 
 eqs = [D(x) ~ (z - b) * x - d * y,
     D(y) ~ d * x + (z - b) * y,
     D(z) ~ c + a * z - z^3 / 3 - (x^2 + y^2) * (1 + e * z) + f * z * x^3]
 
-@named aizawa = ODESystem(eqs)
+@mtkbuild aizawa = ODESystem(eqs,t)
 
 """
 Aizawa equations
@@ -74,15 +74,15 @@ $(latexify(aizawa))
 prob_ode_aizawa = ODEProblem(aizawa, [], (0.0, 1.0))
 
 # Dadras
-@parameters t a=3 b=2.7 c=1.7 d=2 e=9
+@parameters a=3 b=2.7 c=1.7 d=2 e=9
 @variables x(t)=1 y(t)=0 z(t)=0
-D = Differential(t)
+
 
 eqs = [D(x) ~ y - a * x + b * y * z,
     D(y) ~ c * y - x * z + z,
     D(z) ~ d * x * y - e * z]
 
-@named dadras = ODESystem(eqs)
+@mtkbuild dadras = ODESystem(eqs,t)
 
 """
 Dadras equations
@@ -97,15 +97,15 @@ $(latexify(dadras))
 prob_ode_dadras = ODEProblem(dadras, [], (0.0, 1.0))
 
 # chen
-@parameters t a=35 b=3 c=28
+@parameters a=35 b=3 c=28
 @variables x(t)=1 y(t)=0 z(t)=0
-D = Differential(t)
+
 
 eqs = [D(x) ~ a * (y - x),
     D(y) ~ (c - a) * x - x * z + c * y,
     D(z) ~ x * y - b * z]
 
-@named chen = ODESystem(eqs)
+@mtkbuild chen = ODESystem(eqs,t)
 
 """
 chen equations
@@ -120,15 +120,15 @@ $(latexify(chen))
 prob_ode_chen = ODEProblem(chen, [], (0.0, 1.0))
 
 # rossler
-@parameters t a=0.2 b=0.2 c=5.7
+@parameters a=0.2 b=0.2 c=5.7
 @variables x(t)=1 y(t)=0 z(t)=0
-D = Differential(t)
+
 
 eqs = [D(x) ~ -(y + z),
     D(y) ~ x + a * y,
     D(z) ~ b + z * (x - c)]
 
-@named rossler = ODESystem(eqs)
+@mtkbuild rossler = ODESystem(eqs,t)
 
 """
 rossler equations
@@ -144,15 +144,15 @@ $(latexify(rossler))
 prob_ode_rossler = ODEProblem(rossler, [], (0.0, 1.0))
 
 # rabinovich_fabrikant
-@parameters t a=0.14 b=0.10
+@parameters a=0.14 b=0.10
 @variables x(t)=1 y(t)=0 z(t)=0
-D = Differential(t)
+
 
 eqs = [D(x) ~ y * (z - 1 + x^2) + b * x,
     D(y) ~ x * (3 * z + 1 - x^2) + b * y,
     D(z) ~ -2 * z * (a + x * y)]
 
-@named rabinovich_fabrikant = ODESystem(eqs)
+@mtkbuild rabinovich_fabrikant = ODESystem(eqs,t)
 
 """
 rabinovich_fabrikant equations
@@ -167,15 +167,15 @@ $(latexify(rabinovich_fabrikant))
 prob_ode_rabinovich_fabrikant = ODEProblem(rabinovich_fabrikant, [], (0.0, 1.0))
 
 # sprott
-@parameters t a=2.07 b=1.79
+@parameters a=2.07 b=1.79
 @variables x(t)=1 y(t)=0 z(t)=0
-D = Differential(t)
+
 
 eqs = [D(x) ~ y + a * x * y + x * z,
     D(y) ~ 1 - b * x^2 + y * z,
     D(z) ~ x - x^2 - y^2]
 
-@named sprott = ODESystem(eqs)
+@mtkbuild sprott = ODESystem(eqs,t)
 
 """
 sprott equations
@@ -190,15 +190,15 @@ $(latexify(sprott))
 prob_ode_sprott = ODEProblem(sprott, [], (0.0, 1.0))
 
 # hindmarsh_rose
-@parameters t a=1 b=3 c=1 d=5 r=1e-2 s=4 xr=-8 / 5 i=5
+@parameters a=1 b=3 c=1 d=5 r=1e-2 s=4 xr=-8 / 5 i=5
 @variables x(t)=1 y(t)=0 z(t)=0
-D = Differential(t)
+
 
 eqs = [D(x) ~ y - a * x^3 + b * x^2 - z + i,
     D(y) ~ c - d * x^2 - y,
     D(z) ~ r * (s * (x - xr) - z)]
 
-@named hindmarsh_rose = ODESystem(eqs)
+@mtkbuild hindmarsh_rose = ODESystem(eqs,t)
 
 """
 hindmarsh_rose equations