init new project for optimal control tests

Author: vyudu

src/systems/optimal_control_interface.jl

@@ -33,7 +33,7 @@ end
 Generate the control function f(x, u, p, t) from the ODESystem. 
 Input variables are automatically inferred but can be manually specified.
 """
-function SciMLBase.ControlFunction{iip, specialize}(sys::ODESystem,
+function SciMLBase.ODEInputFunction{iip, specialize}(sys::ODESystem,
         dvs = unknowns(sys),
         ps = parameters(sys), u0 = nothing,
         inputs = unbound_inputs(sys),
@@ -114,7 +114,7 @@ function SciMLBase.ControlFunction{iip, specialize}(sys::ODESystem,
         controljac_prototype = nothing
     end
 
-    ControlFunction{iip, specialize}(f;
+    ODEInputFunction{iip, specialize}(f;
         sys = sys,
         jac = _jac === nothing ? nothing : _jac,
         controljac = _cjac === nothing ? nothing : _cjac,
@@ -128,18 +128,18 @@ function SciMLBase.ControlFunction{iip, specialize}(sys::ODESystem,
         initialization_data)
 end
 
-function SciMLBase.ControlFunction(sys::AbstractODESystem, args...; kwargs...)
-    ControlFunction{true}(sys, args...; kwargs...)
+function SciMLBase.ODEInputFunction(sys::AbstractODESystem, args...; kwargs...)
+    ODEInputFunction{true}(sys, args...; kwargs...)
 end
 
-function SciMLBase.ControlFunction{true}(sys::AbstractODESystem, args...;
+function SciMLBase.ODEInputFunction{true}(sys::AbstractODESystem, args...;
         kwargs...)
-    ControlFunction{true, SciMLBase.AutoSpecialize}(sys, args...; kwargs...)
+    ODEInputFunction{true, SciMLBase.AutoSpecialize}(sys, args...; kwargs...)
 end
 
-function SciMLBase.ControlFunction{false}(sys::AbstractODESystem, args...;
+function SciMLBase.ODEInputFunction{false}(sys::AbstractODESystem, args...;
         kwargs...)
-    ControlFunction{false, SciMLBase.FullSpecialize}(sys, args...; kwargs...)
+    ODEInputFunction{false, SciMLBase.FullSpecialize}(sys, args...; kwargs...)
 end
 
 """

test/dynamic_optimization/Project.toml

@@ -0,0 +1,5 @@
+[deps]
+DiffEqDevTools = "f3b72e0c-5b89-59e1-b016-84e28bfd966d"
+InfiniteOpt = "20393b10-9daf-11e9-18c9-8db751c92c57"
+Ipopt = "b6b21f68-93f8-5de0-b562-5493be1d77c9"
+Multibody = "e1cad5d1-98ef-44f9-a79a-9ca4547f95b9"

test/extensions/jump_control.jl renamed to test/dynamic_optimization/jump_control.jl

@@ -3,12 +3,9 @@ BifurcationKit = "0f109fa4-8a5d-4b75-95aa-f515264e7665"
 ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
 ChainRulesTestUtils = "cdddcdb0-9152-4a09-a978-84456f9df70a"
 DiffEqBase = "2b5f629d-d688-5b77-993f-72d75c75574e"
-DiffEqDevTools = "f3b72e0c-5b89-59e1-b016-84e28bfd966d"
 ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
 HomotopyContinuation = "f213a82b-91d6-5c5d-acf7-10f1c761b327"
 InfiniteOpt = "20393b10-9daf-11e9-18c9-8db751c92c57"
-Ipopt = "b6b21f68-93f8-5de0-b562-5493be1d77c9"
-JuMP = "4076af6c-e467-56ae-b986-b466b2749572"
 LabelledArrays = "2ee39098-c373-598a-b85f-a56591580800"
 ModelingToolkit = "961ee093-0014-501f-94e3-6117800e7a78"
 Nemo = "2edaba10-b0f1-5616-af89-8c11ac63239a"