added default args tol and max_iter; commented tutorials moved to Opt… (

#148)
control-toolbox · Jul 4, 2024 · be1e9b0 · be1e9b0
1 parent cae404f
commit be1e9b0
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Showing 3 changed files with 12 additions and 6 deletions.
diff --git a/docs/make.jl b/docs/make.jl
@@ -18,8 +18,8 @@ makedocs(
             size_threshold_ignore = ["api-ctbase.md"]),
     pages = [
         "Introduction"  => "index.md",
-        "Tutorial"      => "tutorial.md",
-        "Continuation"  => "continuation.md",
+        #"Tutorial"      => "tutorial.md",
+        #"Continuation"  => "continuation.md",
         "API"           => "api.md",
         "Developers"    => "dev-api.md",
     ]

diff --git a/ext/CTSolveExt.jl b/ext/CTSolveExt.jl
@@ -18,6 +18,8 @@ function CommonSolve.solve(docp::DOCP;
     display::Bool=CTDirect.__display(),
     print_level::Integer=CTDirect.__print_level_ipopt(),
     mu_strategy::String=CTDirect.__mu_strategy_ipopt(),
+    max_iter::Integer=CTDirect.__max_iter(),
+    tol::Real=CTDirect.__tol(),
     linear_solver::String=CTDirect.__linear_solver(),
     kwargs...)
 
@@ -38,13 +40,13 @@ function CommonSolve.solve(docp::DOCP;
     nlp = getNLP(docp)
     if isnothing(init)
         # use initial guess embedded in the DOCP
-        docp_solution = ipopt(nlp, print_level=print_level, mu_strategy=mu_strategy, sb="yes", linear_solver=linear_solver; kwargs...)
+        docp_solution = ipopt(nlp, print_level=print_level, mu_strategy=mu_strategy, tol=tol, max_iter=max_iter, sb="yes", linear_solver=linear_solver; kwargs...)
     else
         # use given initial guess
         ocp = docp.ocp
         x0 = CTDirect.DOCP_initial_guess(docp, OptimalControlInit(init, state_dim=ocp.state_dimension, control_dim=ocp.control_dimension, variable_dim=ocp.variable_dimension))
 
-        docp_solution = ipopt(nlp, x0=x0, print_level=print_level, mu_strategy=mu_strategy, sb="yes", linear_solver=linear_solver; kwargs...)
+        docp_solution = ipopt(nlp, x0=x0, print_level=print_level, mu_strategy=mu_strategy, tol=tol, max_iter=max_iter, sb="yes", linear_solver=linear_solver; kwargs...)
     end
 
     # return DOCP solution
@@ -65,14 +67,16 @@ function CommonSolve.solve(ocp::OptimalControlModel,
     display::Bool=CTDirect.__display(),
     print_level::Integer=CTDirect.__print_level_ipopt(),
     mu_strategy::String=CTDirect.__mu_strategy_ipopt(),
+    max_iter::Integer=CTDirect.__max_iter(),
+    tol::Real=CTDirect.__tol(),
     linear_solver::String=CTDirect.__linear_solver(),
     kwargs...)
 
     # build discretized OCP
     docp = directTranscription(ocp, description, init=init, grid_size=grid_size, time_grid=time_grid)
 
     # solve DOCP (NB. init is already embedded in docp)
-    docp_solution = solve(docp, display=display, print_level=print_level, mu_strategy=mu_strategy, linear_solver=linear_solver; kwargs...)
+    docp_solution = solve(docp, display=display, print_level=print_level, mu_strategy=mu_strategy, tol=tol, max_iter=max_iter, linear_solver=linear_solver; kwargs...)
 
     # build and return OCP solution
     return OCPSolutionFromDOCP(docp, docp_solution)

diff --git a/src/CTDirect.jl b/src/CTDirect.jl
@@ -6,10 +6,12 @@ using ADNLPModels               # docp model with AD
 using LinearAlgebra             # norm
 using CommonSolve: solve
 
-# Other declarations
+# Other declarations (+++ sort among modules)
 const __grid_size_direct() = 100
 const __print_level_ipopt = CTBase.__print_level_ipopt
 const __mu_strategy_ipopt = CTBase.__mu_strategy_ipopt
+const __tol() = 1e-8
+const __max_iter() = 1000
 const __display = CTBase.__display
 const nlp_constraints! = CTBase.nlp_constraints!
 const matrix2vec = CTBase.matrix2vec