Convert LabelledArrays to ComponentArrays (#144)

* Convert LabelledArrays to ComponentArrays

Project.toml

@@ -5,8 +5,8 @@ version = "0.2.2"
 
 [deps]
 Catlab = "134e5e36-593f-5add-ad60-77f754baafbe"
+ComponentArrays = "b0b7db55-cfe3-40fc-9ded-d10e2dbeff66"
 Compose = "a81c6b42-2e10-5240-aca2-a61377ecd94b"
-LabelledArrays = "2ee39098-c373-598a-b85f-a56591580800"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 LinearMaps = "7a12625a-238d-50fd-b39a-03d52299707e"
 Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
@@ -32,7 +32,6 @@ AlgebraicPetri = "0.9"
 Catlab = "0.15, 0.16"
 Compose = "^0.9.1"
 DelayDiffEq = "5"
-LabelledArrays = "1"
 LinearAlgebra = "1.9"
 LinearMaps = "^3.1.0"
 OrdinaryDiffEq = "^5.49.0, 6"

docs/Project.toml

@@ -2,11 +2,11 @@
 AlgebraicDynamics = "5fd6ff03-a254-427e-8840-ba658f502e32"
 AlgebraicPetri = "4f99eebe-17bf-4e98-b6a1-2c4f205a959b"
 Catlab = "134e5e36-593f-5add-ad60-77f754baafbe"
+ComponentArrays = "b0b7db55-cfe3-40fc-9ded-d10e2dbeff66"
 DelayDiffEq = "bcd4f6db-9728-5f36-b5f7-82caef46ccdb"
 DifferentialEquations = "0c46a032-eb83-5123-abaf-570d42b7fbaa"
 Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
 DynamicalSystems = "61744808-ddfa-5f27-97ff-6e42cc95d634"
-LabelledArrays = "2ee39098-c373-598a-b85f-a56591580800"
 Literate = "98b081ad-f1c9-55d3-8b20-4c87d4299306"
 NLSolvers = "337daf1e-9722-11e9-073e-8b9effe078ba"
 NonlinearSolve = "8913a72c-1f9b-4ce2-8d82-65094dcecaec"

docs/src/AlgebraicPetri.md

@@ -58,15 +58,13 @@ open_bruss = Open([:A, :D], Brusselator, [:A, :B])
 rs = ContinuousResourceSharer{Float64}(open_bruss)
 ````
 
-!!! note
-@example AlgPetri
-    SciML integration for LabelledArrays is broken due to this [issue](https://github.com/SciML/LabelledArrays.jl/issues/162) on LabelledArrays.jl. Once that issue is closed, you should be able to solve LabelledPetriNets with SciML Solvers.
 
 ````julia
-using LabelledArrays
+using ComponentArrays
 tspan = (0.0,100.0)
-params = LVector(t1=1.0, t2=1.2, t3=3.14, t4=0.1)
-u0 = LVector(A=1.0, B=3.17, D=0.0, E=0.0, X=1.0, Y=1.9)
+params = ComponentArray(t1=1.0, t2=1.2, t3=3.14, t4=0.1)
+u0 = ComponentArray(A=1.0, B=3.17, D=0.0, E=0.0, X=1.0, Y=1.9)
+eval_dynamics(rs, u0, params, 0.0)
 prob = ODEProblem((u,p,t) -> eval_dynamics(rs, u, p, t), u0, tspan, params)
 sol = solve(prob, Tsit5())
 plot(sol, idxs=[:X, :Y])

examples/Cyber-Physical.jl

@@ -10,8 +10,7 @@
 
 using AlgebraicDynamics
 using Catlab
-
-using LabelledArrays
+using ComponentArrays
 using DifferentialEquations
 using Plots
 
@@ -58,10 +57,11 @@ to_graphviz(UAV)
 
 
 # Then we assign behaviors to inhabit the boxes.
+
 function 𝗟(𝐖)
     𝐿(u, x, p, t) = [ -p.𝓐l * (u[1] - x[1] - x[2]) ] # sc
     𝐶(u, x, p, t) = [ -p.𝓐c * (u[1] + p.𝓑c*x[1] - x[2]) ] # sl
-    𝐷(u, x, p, t) = LVector(α = -0.313*u[1] +  56.7*u[2] +  0.232*x[1],
+    𝐷(u, x, p, t) = ComponentArray(α = -0.313*u[1] +  56.7*u[2] +  0.232*x[1],
                              q = -0.013*u[1] - 0.426*u[2] + 0.0203*x[1],
                              θ =  56.7*u[2]              )
 
@@ -81,17 +81,18 @@ end
 # Lastly, we compute and plot the solution.
 
 ## initial values
-xₒ = LVector( e = 0.01,  # [e, d] -> [θ offset, 𝛿 control input]
+
+x₀ = ComponentArray( e = 0.01,  # [e, d] -> [θ offset, 𝛿 control input]
               d = 0.05);
 
-uₒ = [0.0, 0, 0, 0, 0]
+u₀ = [0.0, 0, 0, 0, 0]
 tspan = (0, 20.0) 
 
 params = (𝓐l = 100,  # decay constant of sensor
           𝓐c = 100,  # decay constant of controller
           𝓑c = 0)    # ratio of velocity to reference velocity
 
-prob = ODEProblem(𝑢ᵤₐᵥ, uₒ, xₒ, tspan, params)
+prob = ODEProblem(𝑢ᵤₐᵥ, u₀, x₀, tspan, params)
 sol = solve(prob, alg_hints=[:stiff]);
 
 #- 

examples/Ecosystem.jl

@@ -5,7 +5,7 @@
 using AlgebraicDynamics
 using Catlab
 
-using LabelledArrays
+using ComponentArrays
 using OrdinaryDiffEq
 using Plots, Plots.PlotMeasures
 
@@ -16,7 +16,8 @@ using Plots, Plots.PlotMeasures
 # - parameters $\gamma$ represent the rate at which a population of predators grows in a predation interaction
 # - parameters $\delta$ represent the rate at with a species population declines
 
-params = LVector(αr=0.3, βrf=0.015, γrf=0.015, δf=0.7,                     
+
+params = ComponentArray(αr=0.3, βrf=0.015, γrf=0.015, δf=0.7,                     
                  βrh=0.01, γrh=0.01, δh=0.5, 
                  γfishh=0.001, βfishh=0.003, 
                  αfish=0.35, βfishF=0.015, γfishF=0.015, 

examples/Lotka-Volterra.jl

@@ -24,7 +24,7 @@
 using AlgebraicDynamics
 using Catlab.WiringDiagrams, Catlab.Programs
 
-using LabelledArrays
+using ComponentArrays
 using OrdinaryDiffEq, Plots, Plots.PlotMeasures
 
 const UWD = UndirectedWiringDiagram
@@ -47,10 +47,11 @@ end
 
 ## Compose
 rabbitfox_system = oapply(rf, [rabbit_growth, rabbitfox_predation, fox_decline])
+
 
 ## Solve and plot
 u0 = [10.0, 100.0]                              
-params = LVector(α=.3, β=0.015, γ=0.015, δ=0.7)
+params = ComponentArray(α=.3, β=0.015, γ=0.015, δ=0.7)
 tspan = (0.0, 100.0)    
 
 prob = ODEProblem(rabbitfox_system, u0, tspan, params)
@@ -100,7 +101,7 @@ rabbitfox_system = oapply(rabbitfox_pattern, [rabbit, fox])
 
 ## Solve and plot
 u0 = [10.0, 100.0]
-params = LVector(α=.3, β=0.015, γ=0.015, δ=0.7)
+params = ComponentArray(α=.3, β=0.015, γ=0.015, δ=0.7)
 tspan = (0.0, 100.0)
 
 prob = ODEProblem(rabbitfox_system, u0, tspan, params)
@@ -123,9 +124,8 @@ rabbitfox_pattern = barbell(1)
 ## Compose
 rabbitfox_system = oapply(rabbitfox_pattern, [rabbit, fox])
 
-## Solve and plot
 u0 = [10.0, 100.0]
-params = LVector(α=.3, β=0.015, γ=0.015, δ=0.7)
+params = ComponentArray(α=.3, β=0.015, γ=0.015, δ=0.7)
 tspan = (0.0, 100.0)
 
 prob = ODEProblem(rabbitfox_system, u0, tspan, params)

examples/Ross-Macdonald.jl

@@ -7,8 +7,7 @@
 using AlgebraicDynamics
 using Catlab.WiringDiagrams, Catlab.Graphics
 
-using LabelledArrays
-
+using ComponentArrays
 using DelayDiffEq, DifferentialEquations
 using Plots
 
@@ -106,9 +105,10 @@ malaria_model = oapply(rm,
 )
 
 #- 
-params = LVector(a = 0.3, b = 0.55, c = 0.15, 
+params = ComponentArray(a = 0.3, b = 0.55, c = 0.15, 
     g = 0.1, n = 10, r = 1.0/200, m = 0.5)
 
+
 u0 = [0.1, 0.3]
 tspan = (0.0, 365.0*2)
 
@@ -254,7 +254,7 @@ malaria_delay_model = oapply(rm,
     Dict(:humans => human_delay_model, :mosquitos => mosquito_delay_model)
 )
 #- 
-params = LVector(a = 0.3, b = 0.55, c = 0.15, 
+params = ComponentArray(a = 0.3, b = 0.55, c = 0.15, 
     g = 0.1, n = 10, r = 1.0/200, m = 0.5)
 
 u0_delay = [0.09, .01, 0.3]

ext/AlgebraicDynamicsAlgebraicPetriExt.jl

@@ -3,7 +3,7 @@ module AlgebraicDynamicsAlgebraicPetriExt
 using AlgebraicPetri
 using AlgebraicDynamics
 using Catlab
-using LabelledArrays
+using ComponentArrays
 import AlgebraicDynamics.UWDDynam: ContinuousResourceSharer
 
 export OpenNet
@@ -21,16 +21,17 @@ function dynamics(pn::OpenPetriNet,T::Type,ns::Int64)
   vf(u, p, t) = begin f!(storage, u, p, t); return storage end
 end
 
+
 function dynamics(pn::OpenLabelledPetriNet,T::Type,ns::Int64)
   f! = vectorfield(apex(pn))
-  storage = LVector(NamedTuple{tuple(snames(apex(pn))...)}(zeros(T,ns)))
+  storage = ComponentArray(NamedTuple{tuple(snames(apex(pn))...)}(zeros(T,ns)))
   vf(u, p, t) = begin f!(storage, u, p, t); return storage end
   return vf
 end
 
 function dynamics(pn::OpenLabelledReactionNet,T::Type,ns::Int64)
   f! = vectorfield(apex(pn))
-  storage = LVector(NamedTuple{tuple(snames(apex(pn))...)}(zeros(T,ns)))
+  storage = ComponentArray(NamedTuple{tuple(snames(apex(pn))...)}(zeros(T,ns)))
   rt = rates(apex(pn))
   vf(u, p, t) = begin f!(storage, u, rt, t); return storage end
   return vf

notebooks/Project.toml

@@ -4,7 +4,6 @@ Animations = "27a7e980-b3e6-11e9-2bcd-0b925532e340"
 Catlab = "134e5e36-593f-5add-ad60-77f754baafbe"
 Javis = "78b212ba-a7f9-42d4-b726-60726080707e"
 JavisNB = "92afb270-2599-44f6-96a1-44c6efb1daf1"
-LabelledArrays = "2ee39098-c373-598a-b85f-a56591580800"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 OrdinaryDiffEq = "1dea7af3-3e70-54e6-95c3-0bf5283fa5ed"
 Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"

notebooks/multi-city SIR.ipynb

@@ -23,7 +23,7 @@
     "\n",
     "using AlgebraicDynamics, AlgebraicDynamics.DWDDynam\n",
     "\n",
-    "using LabelledArrays\n",
+    "using ComponentArrays\n",
     "\n",
     "using OrdinaryDiffEq\n",
     "using Plots"

test/Project.toml

@@ -1,9 +1,9 @@
 [deps]
 AlgebraicDynamics = "5fd6ff03-a254-427e-8840-ba658f502e32"
+AlgebraicPetri = "4f99eebe-17bf-4e98-b6a1-2c4f205a959b"
 Catlab = "134e5e36-593f-5add-ad60-77f754baafbe"
+ComponentArrays = "b0b7db55-cfe3-40fc-9ded-d10e2dbeff66"
 DelayDiffEq = "bcd4f6db-9728-5f36-b5f7-82caef46ccdb"
-LabelledArrays = "2ee39098-c373-598a-b85f-a56591580800"
 OrdinaryDiffEq = "1dea7af3-3e70-54e6-95c3-0bf5283fa5ed"
 PrettyTables = "08abe8d2-0d0c-5749-adfa-8a2ac140af0d"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
-AlgebraicPetri = "4f99eebe-17bf-4e98-b6a1-2c4f205a959b"

test/cpg_dynam.jl

@@ -3,7 +3,7 @@ using AlgebraicDynamics.DWDDynam
 using AlgebraicDynamics.CPortGraphDynam: draw, barbell, gridpath, grid, meshpath
 using Catlab
 
-using LabelledArrays
+using ComponentArrays
 
 using Test
 using PrettyTables

test/dwd_dynam.jl

@@ -1,7 +1,7 @@
 using AlgebraicDynamics.DWDDynam
 using Catlab
 
-using LabelledArrays
+using ComponentArrays
 using DelayDiffEq
 using Test
 

test/ext/AlgebraicPetri.jl

@@ -3,7 +3,7 @@ using AlgebraicPetri
 using Catlab
 using Test
 using AlgebraicDynamics.UWDDynam
-using LabelledArrays
+using ComponentArrays
 
 
 @testset "AlgebraicPetri" begin
@@ -21,18 +21,19 @@ using LabelledArrays
   @test nstates(rs) == 1
   @test nports(rs) == 1
   @test portmap(rs) == [1]
-  u = LVector(foo=1.0)
-  p = LVector(bar=2.0)
-  @test eval_dynamics(rs, u, p, 0) == [2.0]
+  u = ComponentArray(foo=1.0)
+  p = ComponentArray(bar=2.0)
+  @test eval_dynamics(rs, u, p, 0) == ComponentArray(foo=2.0)
+
 
   labelled_birth_react = Open(LabelledReactionNet{Float64}{Float64}([:foo => 1.0], ((:bar => 2.0), (:foo => (:foo, :foo)))))
   rs = ContinuousResourceSharer{Float64}(labelled_birth_react)
   @test nstates(rs) == 1
   @test nports(rs) == 1
   @test portmap(rs) == [1]
-  u = LVector(NamedTuple(zip(snames(apex(labelled_birth_react)), Vector(subpart(apex(labelled_birth_react), :concentration)))))
-  p = LVector(bar=2.0)
-  @test eval_dynamics(rs, u, p, 0) == [2.0]
+  u = ComponentArray(NamedTuple(zip(snames(apex(labelled_birth_react)), Vector(subpart(apex(labelled_birth_react), :concentration)))))
+  p = ComponentArray(bar=2.0)
+  @test eval_dynamics(rs, u, p, 0) == ComponentArray(foo=2.0)
 
   Brusselator = LabelledPetriNet([:A, :B, :D, :E, :X, :Y],
     :t1 => (:A => (:X, :A)),

test/ext/DelayDiffEq.jl

@@ -2,7 +2,7 @@ using AlgebraicDynamics
 using Catlab
 using DelayDiffEq
 using Test
-
+using ComponentArrays
 # DWDDynam Integration
 ######################
 
@@ -56,8 +56,8 @@ add_wires!(d_big, Pair[
       u0 = [2.7]
       x0 = [10.0]
       τ = 10.0
-      p = LVector(τ = τ)
-
+      p = ComponentArray(τ = τ)
+    
       @test eval_dynamics(delay, u0, x0, hist, p) == [0.0]
       @test eval_dynamics(delay_copy, u0, x0, hist, p) == [0.0]
 
@@ -109,14 +109,14 @@ add_wires!(d_big, Pair[
         mult_delay = DelayMachine{Float64}(1,1,1, df, delay ? delay_rf : rf)
         add_delay = DelayMachine{Float64}(1,1,1, ef, delay ? delay_rf : rf)
 
-        prob = DDEProblem(oapply(d, [mult_delay, add_delay]), u0, x0, hist, (0, 4.0), LVector(τ = 2.0))
+        prob = DDEProblem(oapply(d, [mult_delay, add_delay]), u0, x0, hist, (0, 4.0), ComponentArray(τ = 2.0)) 
         sol1 = solve(prob, alg; dtmax = 0.1)
         if delay
           f = (u,h,p,t) -> [ (h(p,t - p.τ)[2] + x0[1]) * h(p,t - p.τ)[1], h(p, t - p.τ)[1] + h(p,t - p.τ)[2] ]
         else
           f = (u,h,p,t) -> [ (u[2] + x0[1]) * h(p,t - p.τ)[1], u[1] + h(p,t - p.τ)[2] ]
         end
-        prob = DDEProblem(f, u0, hist, (0, 4.0), LVector(τ = 2.0))
+        prob = DDEProblem(f, u0, hist, (0, 4.0), ComponentArray(τ = 2.0))
         sol2 = solve(prob, alg; dtmax = 0.1)
         @test last(sol1) == last(sol2)
       end
@@ -324,8 +324,8 @@ const UWD = UndirectedWiringDiagram
         1, 1, 1, dxdt_delay, (u,h,p,t) -> [[u[1], h(p, t - p.n)[1]]])
     rm_model = oapply(c, [mosquito_delay_model, human_delay_model])
 
-    params = LVector(a = 0.3, b = 0.55, c = 0.15,
-        g = 0.1, n = 10, r = 1.0/200, m = 0.5)
+    params = ComponentArray(a = 0.3, b = 0.55, c = 0.15,
+    g = 0.1, n = 10, r = 1.0/200, m = 0.5)
 
     u0_delay = [0.09, .01, 0.3]
     tspan = (0.0, 365.0*5)