Merge pull request #382 from SciML/mtk-v10

BREAKING: v10 release

Author: AayushSabharwal

Project.toml

@@ -13,17 +13,17 @@ PreallocationTools = "d236fae5-4411-538c-8e31-a6e3d9e00b46"
 Symbolics = "0c5d862f-8b57-4792-8d23-62f2024744c7"
 
 [compat]
+ADTypes = "1"
 Aqua = "0.8"
 ChainRulesCore = "1.24"
 ControlSystemsBase = "1.4"
 DataFrames = "1.7"
 DataInterpolations = "6"
-ForwardDiff = "0.10"
 DiffEqBase = "6.152"
+ForwardDiff = "0.10"
 IfElse = "0.1"
 LinearAlgebra = "1.10"
-Optimization = "4"
-ModelingToolkit = "9.47"
+ModelingToolkit = "10"
 OrdinaryDiffEq = "6.87"
 OrdinaryDiffEqDefault = "1.1"
 PreallocationTools = "0.4.23"
@@ -35,13 +35,13 @@ Test = "1"
 julia = "1.10"
 
 [extras]
+ADTypes = "47edcb42-4c32-4615-8424-f2b9edc5f35b"
 Aqua = "4c88cf16-eb10-579e-8560-4a9242c79595"
 ControlSystemsBase = "aaaaaaaa-a6ca-5380-bf3e-84a91bcd477e"
 DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
 DataInterpolations = "82cc6244-b520-54b8-b5a6-8a565e85f1d0"
 ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
-Optimization = "7f7a1694-90dd-40f0-9382-eb1efda571ba"
 OrdinaryDiffEq = "1dea7af3-3e70-54e6-95c3-0bf5283fa5ed"
 OrdinaryDiffEqDefault = "50262376-6c5a-4cf5-baba-aaf4f84d72d7"
 SafeTestsets = "1bc83da4-3b8d-516f-aca4-4fe02f6d838f"
@@ -50,4 +50,4 @@ SymbolicIndexingInterface = "2efcf032-c050-4f8e-a9bb-153293bab1f5"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [targets]
-test = ["Aqua", "LinearAlgebra", "OrdinaryDiffEqDefault", "OrdinaryDiffEq", "Optimization", "SafeTestsets", "Test", "ControlSystemsBase", "DataFrames", "DataInterpolations", "SciMLStructures", "SymbolicIndexingInterface", "ForwardDiff"]
+test = ["ADTypes", "Aqua", "LinearAlgebra", "OrdinaryDiffEqDefault", "OrdinaryDiffEq", "SafeTestsets", "Test", "ControlSystemsBase", "DataFrames", "DataInterpolations", "SciMLStructures", "SymbolicIndexingInterface", "ForwardDiff"]

README.md

@@ -71,7 +71,7 @@ using ModelingToolkit: t_nounits as t
     end
 end
 
-@mtkbuild sys = RC()
+@mtkcompile sys = RC()
 prob = ODEProblem(sys, Pair[], (0, 10.0))
 sol = solve(prob)
 

docs/Project.toml

@@ -15,6 +15,6 @@ DataFrames = "1.7"
 DataInterpolations = "6.4, 7, 8"
 Documenter = "1"
 IfElse = "0.1"
-ModelingToolkit = "9"
+ModelingToolkit = "10"
 OrdinaryDiffEq = "6.31"
 Plots = "1.36"

docs/src/API/linear_analysis.md

@@ -61,7 +61,7 @@ using ModelingToolkitStandardLibrary.Blocks, ModelingToolkit
 t = ModelingToolkit.get_iv(P)
 eqs = [connect(P.output, :plant_output, C.input)  # Connect with an automatically created analysis point called :plant_output
        connect(C.output, :plant_input, P.input)]
-sys = ODESystem(eqs, t, systems = [P, C], name = :feedback_system)
+sys = System(eqs, t, systems = [P, C], name = :feedback_system)
 
 matrices_S = get_sensitivity(sys, :plant_input)[1] # Compute the matrices of a state-space representation of the (input)sensitivity function.
 matrices_T = get_comp_sensitivity(sys, :plant_input)[1]

docs/src/connectors/connections.md

@@ -102,9 +102,9 @@ end
 eqs = [connect(capacitor.p, resistor.p)
        connect(resistor.n, ground.g, capacitor.n)]
 
-@named model = ODESystem(eqs, t; systems)
+@named model = System(eqs, t; systems)
 
-sys = structural_simplify(model)
+sys = mtkcompile(model)
 
 println.(equations(sys))
 nothing # hide
@@ -113,7 +113,7 @@ nothing # hide
 The solution shows what we would expect, a non-linear dissipation of voltage and related decrease in current flow…
 
 ```@example connections
-prob = ODEProblem(sys, [1.0], (0, 10.0), [])
+prob = ODEProblem(sys, [1.0], (0, 10.0))
 sol = solve(prob)
 
 p1 = plot(sol, idxs = [capacitor.v])
@@ -144,9 +144,9 @@ end
 eqs = [connect(damping.flange_a, body.flange)
        connect(ground.flange, damping.flange_b)]
 
-@named model = ODESystem(eqs, t; systems)
+@named model = System(eqs, t; systems)
 
-sys = structural_simplify(model)
+sys = mtkcompile(model)
 
 println.(full_equations(sys))
 nothing # hide
@@ -156,7 +156,7 @@ As expected, we have a similar solution…
 
 ```@example connections
 prob = ODEProblem(
-    sys, [], (0, 10.0), []; initialization_eqs = [sys.body.s ~ 0, sys.body.v ~ 1])
+    sys, [], (0, 10.0); initialization_eqs = [sys.body.s ~ 0, sys.body.v ~ 1])
 sol_v = solve(prob)
 
 p1 = plot(sol_v, idxs = [body.v])
@@ -180,9 +180,9 @@ end
 eqs = [connect(damping.flange_a, body.flange)
        connect(ground.flange, damping.flange_b)]
 
-@named model = ODESystem(eqs, t; systems)
+@named model = System(eqs, t; systems)
 
-sys = structural_simplify(model)
+sys = mtkcompile(model)
 
 println.(full_equations(sys))
 nothing # hide
@@ -191,7 +191,7 @@ nothing # hide
 As can be seen, we get exactly the same result.  The only difference here is that we are solving an extra equation, which allows us to plot the body position as well.
 
 ```@example connections
-prob = ODEProblem(sys, [], (0, 10.0), [], fully_determined=true)
+prob = ODEProblem(sys, [], (0, 10.0), fully_determined=true)
 sol_p = solve(prob)
 
 p1 = plot(sol_p, idxs = [body.v])
@@ -275,13 +275,13 @@ function simplify_and_solve(damping, spring, body, ground; initialization_eqs =
     eqs = [connect(spring.flange_a, body.flange, damping.flange_a)
            connect(spring.flange_b, damping.flange_b, ground.flange)]
 
-    @named model = ODESystem(eqs, t; systems = [ground, body, spring, damping])
+    @named model = System(eqs, t; systems = [ground, body, spring, damping])
 
-    sys = structural_simplify(model)
+    sys = mtkcompile(model)
 
     println.(full_equations(sys))
 
-    prob = ODEProblem(sys, [], (0, 10.0), []; initialization_eqs, fully_determined=true)
+    prob = ODEProblem(sys, [], (0, 10.0); initialization_eqs, fully_determined=true)
     sol = solve(prob; abstol = 1e-9, reltol = 1e-9)
 
     return sol

docs/src/connectors/sign_convention.md

@@ -88,7 +88,7 @@ Here we can see that a positive input force results in an increasing velocity.
         connect(mass.flange, force.flange)
     end
 end
-@mtkbuild sys = Model()
+@mtkcompile sys = Model()
 full_equations(sys)
 ```
 
@@ -128,7 +128,7 @@ Here we can see that a positive input current results in an increasing voltage.
         connect(capacitor.n, current.p, ground.g)
     end
 end
-@mtkbuild sys = Model()
+@mtkcompile sys = Model()
 full_equations(sys)
 ```
 
@@ -146,7 +146,7 @@ Reversing the pins gives the same result
         connect(capacitor.p, current.n, ground.g)
     end
 end
-@mtkbuild sys = Model()
+@mtkcompile sys = Model()
 full_equations(sys)
 ```
 
@@ -184,6 +184,6 @@ A positive input mass flow leads to an increasing pressure (in this case we get
         connect(fluid, flow.port)
     end
 end
-@mtkbuild sys = Model()
+@mtkcompile sys = Model()
 full_equations(sys) |> first
 ```

docs/src/tutorials/custom_component.md

@@ -109,11 +109,11 @@ nothing # hide
 
 ## Simulating the Model
 
-`@mtkbuild` builds a structurally simplified `ChaoticAttractor` model.
+`@mtkcompile` builds a structurally simplified `ChaoticAttractor` model.
 Since the initial voltage of the capacitors was already specified via `v` and the initial current of inductor via `i`, no initial condition is given and an empty pair is supplied.
 
 ```@example components
-@mtkbuild sys = ChaoticAttractor()
+@mtkcompile sys = ChaoticAttractor()
 prob = ODEProblem(sys, Pair[], (0, 5e4))
 sol = solve(prob; saveat = 1.0)
 

docs/src/tutorials/dc_motor_pi.md

@@ -76,7 +76,7 @@ Now the model can be simulated. Typical rotational mechanical systems are descri
 so that it can be represented as a system of `ODEs` (ordinary differential equations).
 
 ```@example dc_motor_pi
-sys = structural_simplify(model)
+sys = mtkcompile(model)
 prob = ODEProblem(sys, [sys.L1.i => 0.0], (0, 6.0))
 sol = solve(prob)
 

docs/src/tutorials/input_component.md

@@ -43,7 +43,7 @@ function MassSpringDamper(; name)
            D(x) ~ dx
            D(dx) ~ ddx]
 
-    ODESystem(eqs, t; name, systems = [input])
+    System(eqs, t; name, systems = [input])
 end
 
 function MassSpringDamperSystem(data, time; name)
@@ -54,7 +54,7 @@ function MassSpringDamperSystem(data, time; name)
     eqs = [connect(clk.output, src.input)
            connect(src.output, model.input)]
 
-    ODESystem(eqs, t, [], []; name, systems = [src, clk, model])
+    System(eqs, t, [], []; name, systems = [src, clk, model])
 end
 
 function generate_data()
@@ -68,7 +68,7 @@ end
 df = generate_data() # example data
 
 @named system = MassSpringDamperSystem(df.data, df.time)
-sys = structural_simplify(system)
+sys = mtkcompile(system)
 prob = ODEProblem(sys, [], (0, df.time[end]))
 sol = solve(prob)
 plot(sol)
@@ -93,7 +93,7 @@ my_interpolation = LinearInterpolation(df.data, df.time)
         connect(src.output, model.input)
     end
 end;
-@mtkbuild sys = MassSpringDamperSystem2()
+@mtkcompile sys = MassSpringDamperSystem2()
 
 prob = ODEProblem(sys, [], (0, df.time[end]))
 sol = solve(prob, Tsit5())
@@ -134,7 +134,7 @@ function MassSpringDamper(; name)
            D(x) ~ dx
            D(dx) ~ ddx]
 
-    ODESystem(eqs, t, vars, pars; name, systems = [input])
+    System(eqs, t, vars, pars; name, systems = [input])
 end
 
 function MassSpringDamperSystem(data, time; name)
@@ -145,7 +145,7 @@ function MassSpringDamperSystem(data, time; name)
     eqs = [connect(model.input, src.output)
            connect(clk.output, src.input)]
 
-    ODESystem(eqs, t; name, systems = [src, clk, model])
+    System(eqs, t; name, systems = [src, clk, model])
 end
 
 function generate_data()
@@ -159,7 +159,7 @@ end
 df = generate_data() # example data
 
 @named system = MassSpringDamperSystem(df.data, df.time)
-sys = structural_simplify(system)
+sys = mtkcompile(system)
 prob = ODEProblem(sys, [], (0, df.time[end]))
 sol = solve(prob)
 plot(sol)
@@ -213,11 +213,11 @@ function System(; name)
            D(x) ~ dx
            D(dx) ~ ddx]
 
-    ODESystem(eqs, t, vars, pars; name)
+    System(eqs, t, vars, pars; name)
 end
 
 @named system = System()
-sys = structural_simplify(system)
+sys = mtkcompile(system)
 prob = ODEProblem(sys, [], (0, time[end]))
 
 rdata[] = data1
@@ -240,7 +240,7 @@ Additional code could be added to resolve this issue, for example by using a `Re
 
 ## `SampledData` Component
 
-To resolve the issues presented above, the `ModelingToolkitStandardLibrary.Blocks.SampledData` component can be used which allows for a resusable `ODESystem` and self contained data which ensures a solution which remains valid for it's lifetime.  Now it's possible to also parallelize the call to `solve()`.
+To resolve the issues presented above, the `ModelingToolkitStandardLibrary.Blocks.SampledData` component can be used which allows for a resusable `System` and self contained data which ensures a solution which remains valid for it's lifetime.  Now it's possible to also parallelize the call to `solve()`.
 
 ```julia
 using ModelingToolkit
@@ -259,11 +259,11 @@ function System(; name)
            D(x) ~ dx
            D(dx) ~ ddx]
 
-    ODESystem(eqs, t, vars, pars; systems = [src], name)
+    System(eqs, t, vars, pars; systems = [src], name)
 end
 
 @named system = System()
-sys = structural_simplify(system, split = false)
+sys = mtkcompile(system, split = false)
 s = complete(system)
 
 dt = 4e-4

docs/src/tutorials/rc_circuit.md

@@ -33,7 +33,7 @@ using ModelingToolkit: t_nounits as t
     end
 end
 
-@mtkbuild sys = RC()
+@mtkcompile sys = RC()
 prob = ODEProblem(sys, Pair[], (0, 10.0))
 sol = solve(prob)