add OptimizationProblem building

Author: ChrisRackauckas

Project.toml

@@ -22,7 +22,7 @@ TreeViews = "a2a6695c-b41b-5b7d-aed9-dbfdeacea5d7"
 Unitful = "1986cc42-f94f-5a68-af5c-568840ba703d"
 
 [compat]
-DiffEqBase = "6"
+DiffEqBase = "6.28"
 DiffRules = "0.1, 1.0"
 DocStringExtensions = "0.7, 0.8"
 GeneralizedGenerated = "0.1.4, 0.2"

src/ModelingToolkit.jl

@@ -122,6 +122,7 @@ export simplify_constants
 export Operation, Expression, Variable
 export calculate_jacobian, generate_jacobian, generate_function
 export calculate_tgrad, generate_tgrad
+export calculate_gradient, generate_gradient
 export calculate_hessian, generate_hessian
 export calculate_massmatrix, generate_diffusion_function
 export independent_variable, states, parameters, equations

src/systems/nonlinear/nonlinearsystem.jl

@@ -74,8 +74,7 @@ end
 
 function DiffEqBase.NonlinearProblem{iip}(sys::NonlinearSystem,u0map,tspan,
                                           parammap=DiffEqBase.NullParameters();
-                                          version = nothing, jac = false,
-                                          kwargs...) where iip
+                                          jac = false,kwargs...) where iip
     dvs = states(sys)
     ps = parameters(sys)
 

src/systems/optimization/optimizationsystem.jl

@@ -39,13 +39,22 @@ function OptimizationSystem(op, states, ps;
     OptimizationSystem(op, convert.(Variable,states), convert.(Variable,ps), name, systems)
 end
 
+function calculate_gradient(sys::OptimizationSystem)
+    expand_derivatives.(gradient(equations(sys), [dv() for dv in states(sys)]))
+end
+
+function generate_gradient(sys::OptimizationSystem, vs = states(sys), ps = parameters(sys), expression = Val{true}; kwargs...)
+    grad = calculate_gradient(sys)
+    return build_function(grad, convert.(Variable,vs), convert.(Variable,ps), (), x->convert(Expr, x); kwargs...)
+end
+
 function calculate_hessian(sys::OptimizationSystem)
     expand_derivatives.(hessian(equations(sys), [dv() for dv in states(sys)]))
 end
 
 function generate_hessian(sys::OptimizationSystem, vs = states(sys), ps = parameters(sys), expression = Val{true}; kwargs...)
     hes = calculate_hessian(sys)
-    return build_function(hes, convert.(Variable,vs), convert.(Variable,ps), (), x->convert(Expr, x))
+    return build_function(hes, convert.(Variable,vs), convert.(Variable,ps), (), x->convert(Expr, x); kwargs...)
 end
 
 function generate_function(sys::OptimizationSystem, vs = states(sys), ps = parameters(sys), expression = Val{true}; kwargs...)
@@ -56,3 +65,19 @@ end
 
 equations(sys::OptimizationSystem) = isempty(sys.systems) ? sys.op : sys.op + reduce(+,namespace_operation.(sys.systems))
 namespace_operation(sys::OptimizationSystem) = namespace_operation(sys.op,sys.name,nothing)
+
+function DiffEqBase.OptimizationProblem{iip}(sys::OptimizationSystem,
+                                          parammap=DiffEqBase.NullParameters();
+                                          u0=nothing, lb=nothing, ub=nothing,
+                                          hes = false,
+                                          kwargs...) where iip
+    dvs = states(sys)
+    ps = parameters(sys)
+
+    f = generate_function(sys)
+    u0 = varmap_to_vars(u0,dvs)
+    p = varmap_to_vars(parammap,ps)
+    lb = varmap_to_vars(lb,dvs)
+    ub = varmap_to_vars(ub,dvs)
+    OptimizationProblem(f,p;u0=u0,lb=lb,ub=ub,kwargs...)
+end

src/variables.jl

@@ -192,3 +192,4 @@ function varmap_to_vars(varmap,varlist)
 end
 
 varmap_to_vars(varmap::DiffEqBase.NullParameters,varlist) = varmap
+varmap_to_vars(varmap::Nothing,varlist) = varmap

test/optimizationsystem.jl

@@ -8,12 +8,14 @@ sys2 = OptimizationSystem(loss,[x,y],[a,b],name=:sys2)
 @variables z
 @parameters β
 loss2 = sys1.x - sys2.y + z*β
-combinedsys = OptimizationSystem(loss,[z],[β],systems=[sys1,sys2],name=:combinedsys)
+combinedsys = OptimizationSystem(loss2,[z],[β],systems=[sys1,sys2],name=:combinedsys)
 
 equations(combinedsys)
 states(combinedsys)
 parameters(combinedsys)
 
+calculate_gradient(combinedsys)
 calculate_hessian(combinedsys)
 generate_function(combinedsys)
+generate_gradient(combinedsys)
 generate_hessian(combinedsys)