Merge pull request #3031 from SciML/labelledarrays

Move labelledarrays to extension testing

Author: ChrisRackauckas

Project.toml

@@ -135,7 +135,6 @@ ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
 Ipopt = "b6b21f68-93f8-5de0-b562-5493be1d77c9"
 Ipopt_jll = "9cc047cb-c261-5740-88fc-0cf96f7bdcc7"
 JET = "c3a54625-cd67-489e-a8e7-0a5a0ff4e31b"
-LabelledArrays = "2ee39098-c373-598a-b85f-a56591580800"
 ModelingToolkitStandardLibrary = "16a59e39-deab-5bd0-87e4-056b12336739"
 NonlinearSolve = "8913a72c-1f9b-4ce2-8d82-65094dcecaec"
 Optimization = "7f7a1694-90dd-40f0-9382-eb1efda571ba"
@@ -155,4 +154,4 @@ 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", "LabelledArrays"]
+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/extensions/Project.toml

@@ -1,6 +1,7 @@
 [deps]
 BifurcationKit = "0f109fa4-8a5d-4b75-95aa-f515264e7665"
 ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
+LabelledArrays = "2ee39098-c373-598a-b85f-a56591580800"
 ModelingToolkit = "961ee093-0014-501f-94e3-6117800e7a78"
 OrdinaryDiffEq = "1dea7af3-3e70-54e6-95c3-0bf5283fa5ed"
 SciMLSensitivity = "1ed8b502-d754-442c-8d5d-10ac956f44a1"

test/labelledarrays.jl

@@ -41,3 +41,51 @@ d = LVector(x = 1.0, y = 2.0, z = 3.0)
 @test ff.jac(d, p, ForwardDiff.Dual(0.0, 1.0)) isa Array
 @inferred ff.jac(d, p, ForwardDiff.Dual(0.0, 1.0))
 @test eltype(ff.jac(d, p, ForwardDiff.Dual(0.0, 1.0))) <: ForwardDiff.Dual
+
+## https://github.com/SciML/ModelingToolkit.jl/issues/1054
+using LabelledArrays
+using ModelingToolkit
+
+# ODE model: simple SIR model with seasonally forced contact rate
+function SIR!(du, u, p, t)
+
+    # Unknowns
+    (S, I, R) = u[1:3]
+    N = S + I + R
+
+    # params
+    β = p.β
+    η = p.η
+    φ = p.φ
+    ω = 1.0 / p.ω
+    μ = p.μ
+    σ = p.σ
+
+    # FOI
+    βeff = β * (1.0 + η * cos(2.0 * π * (t - φ) / 365.0))
+    λ = βeff * I / N
+
+    # change in unknowns
+    du[1] = (μ * N - λ * S - μ * S + ω * R)
+    du[2] = (λ * S - σ * I - μ * I)
+    du[3] = (σ * I - μ * R - ω * R)
+    du[4] = (σ * I) # cumulative incidence
+end
+
+# Solver settings
+tmin = 0.0
+tmax = 10.0 * 365.0
+tspan = (tmin, tmax)
+
+# Initiate ODE problem
+theta_fix = [1.0 / (80 * 365)]
+theta_est = [0.28, 0.07, 1.0 / 365.0, 1.0, 1.0 / 5.0]
+p = @LArray [theta_est; theta_fix] (:β, :η, :ω, :φ, :σ, :μ)
+u0 = @LArray [9998.0, 1.0, 1.0, 1.0] (:S, :I, :R, :C)
+
+# Initiate ODE problem
+problem = ODEProblem(SIR!, u0, tspan, p)
+sys = complete(modelingtoolkitize(problem))
+
+@test all(isequal.(parameters(sys), getproperty.(@variables(β, η, ω, φ, σ, μ), :val)))
+@test all(isequal.(Symbol.(unknowns(sys)), Symbol.(@variables(S(t), I(t), R(t), C(t)))))

test/modelingtoolkitize.jl

@@ -1,6 +1,6 @@
 using OrdinaryDiffEq, ModelingToolkit, DataStructures, Test
 using Optimization, RecursiveArrayTools, OptimizationOptimJL
-using LabelledArrays, SymbolicIndexingInterface
+using SymbolicIndexingInterface
 using ModelingToolkit: t_nounits as t, D_nounits as D
 using SciMLBase: parameterless_type
 
@@ -210,54 +210,6 @@ tspan = (0.0, 1.0)
 prob = ODEProblem(k, x0, tspan)
 sys = modelingtoolkitize(prob)
 
-## https://github.com/SciML/ModelingToolkit.jl/issues/1054
-using LabelledArrays
-using ModelingToolkit
-
-# ODE model: simple SIR model with seasonally forced contact rate
-function SIR!(du, u, p, t)
-
-    # Unknowns
-    (S, I, R) = u[1:3]
-    N = S + I + R
-
-    # params
-    β = p.β
-    η = p.η
-    φ = p.φ
-    ω = 1.0 / p.ω
-    μ = p.μ
-    σ = p.σ
-
-    # FOI
-    βeff = β * (1.0 + η * cos(2.0 * π * (t - φ) / 365.0))
-    λ = βeff * I / N
-
-    # change in unknowns
-    du[1] = (μ * N - λ * S - μ * S + ω * R)
-    du[2] = (λ * S - σ * I - μ * I)
-    du[3] = (σ * I - μ * R - ω * R)
-    du[4] = (σ * I) # cumulative incidence
-end
-
-# Solver settings
-tmin = 0.0
-tmax = 10.0 * 365.0
-tspan = (tmin, tmax)
-
-# Initiate ODE problem
-theta_fix = [1.0 / (80 * 365)]
-theta_est = [0.28, 0.07, 1.0 / 365.0, 1.0, 1.0 / 5.0]
-p = @LArray [theta_est; theta_fix] (:β, :η, :ω, :φ, :σ, :μ)
-u0 = @LArray [9998.0, 1.0, 1.0, 1.0] (:S, :I, :R, :C)
-
-# Initiate ODE problem
-problem = ODEProblem(SIR!, u0, tspan, p)
-sys = complete(modelingtoolkitize(problem))
-
-@test all(isequal.(parameters(sys), getproperty.(@variables(β, η, ω, φ, σ, μ), :val)))
-@test all(isequal.(Symbol.(unknowns(sys)), Symbol.(@variables(S(t), I(t), R(t), C(t)))))
-
 # https://github.com/SciML/ModelingToolkit.jl/issues/1158
 
 function ode_prob(du, u, p::NamedTuple, t)
@@ -361,10 +313,6 @@ sys = modelingtoolkitize(prob)
             (1.0, [:p]),
             (1.0, Dict(1 => :p)),
             (Dict(:a => 2, :b => 4), Dict(:a => :p, :b => :q)),
-            (LVector(a = 1, b = 2), [:p, :q]),
-            (SLVector(a = 1, b = 2), [:p, :q]),
-            (LVector(a = 1, b = 2), Dict(1 => :p, 2 => :q)),
-            (SLVector(a = 1, b = 2), Dict(1 => :p, 2 => :q)),
             ((a = 1, b = 2), (a = :p, b = :q)),
             ((a = 1, b = 2), Dict(:a => :p, :b => :q))
         ]
@@ -390,10 +338,6 @@ sys = modelingtoolkitize(prob)
             (1.0, [:p, :q]),
             (1.0, Dict(1 => :p, 2 => :q)),
             (Dict(:a => 2, :b => 4), Dict(:a => :p, :b => :q, :c => :r)),
-            (LVector(a = 1, b = 2), [:p, :q, :r]),
-            (SLVector(a = 1, b = 2), [:p, :q, :r]),
-            (LVector(a = 1, b = 2), Dict(1 => :p, 2 => :q, 3 => :r)),
-            (SLVector(a = 1, b = 2), Dict(1 => :p, 2 => :q, 3 => :r)),
             ((a = 1, b = 2), (a = :p, b = :q, c = :r)),
             ((a = 1, b = 2), Dict(:a => :p, :b => :q, :c => :r))
         ]

test/runtests.jl

@@ -31,7 +31,6 @@ end
             @safetestset "ODESystem Test" include("odesystem.jl")
             @safetestset "Dynamic Quantities Test" include("dq_units.jl")
             @safetestset "Unitful Quantities Test" include("units.jl")
-            @safetestset "LabelledArrays Test" include("labelledarrays.jl")
             @safetestset "Mass Matrix Test" include("mass_matrix.jl")
             @safetestset "InitializationSystem Test" include("initializationsystem.jl")
             @safetestset "Guess Propagation" include("guess_propagation.jl")
@@ -110,5 +109,6 @@ end
         activate_extensions_env()
         @safetestset "BifurcationKit Extension Test" include("extensions/bifurcationkit.jl")
         @safetestset "Auto Differentiation Test" include("extensions/ad.jl")
+        @safetestset "LabelledArrays Test" include("labelledarrays.jl")
     end
 end