v0.9.0 (#142)

* prepare v0.9.0 (todo: comment local init and its export)

* comment local init and its export

* local tests ok, removed _ for OptimalControlInit

* renamed box dim to range

* solve appears in api doc, listed under commonsolve

* v0.9.0

Project.toml

@@ -23,7 +23,7 @@ CTSolveExt = ["NLPModelsIpopt", "HSL"]
 
 [compat]
 ADNLPModels = "0.8"
-CTBase = "0.10"
+CTBase = "0.11"
 DocStringExtensions = "0.9"
 HSL = "0.4"
 julia = "1.10"

docs/Project.toml

@@ -7,6 +7,3 @@ JLD2 = "033835bb-8acc-5ee8-8aae-3f567f8a3819"
 JSON3 = "0f8b85d8-7281-11e9-16c2-39a750bddbf1"
 NLPModelsIpopt = "f4238b75-b362-5c4c-b852-0801c9a21d71"
 Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
-
-[compat]
-julia = "1.9"

docs/make.jl

@@ -6,6 +6,7 @@ using HSL
 using JLD2
 using JSON3
 using Plots
+using CommonSolve
 
 DocMeta.setdocmeta!(CTBase, :DocTestSetup, :(using CTBase); recursive = true)
 DocMeta.setdocmeta!(CTDirect, :DocTestSetup, :(using CTDirect); recursive = true)

docs/src/api.md

@@ -4,17 +4,10 @@
 
 ```@index
 Pages   = ["api.md"]
-Modules = [CTDirect]
+Modules = [CTDirect, CommonSolve]
 Order = [:module, :constant, :type, :function, :macro]
 ```
 
-## Available methods
-
-```@example
-using CTDirect
-available_methods()
-```
-
 ## Documentation
 
 ```@autodocs
@@ -23,8 +16,6 @@ Order = [:module, :constant, :type, :function, :macro]
 Private = false
 ```
 
-<! -- manually add docstrings from package extensions -->
-<! -- does not work for solve which is not in CTDirect -->
 ```@docs
 solve
 save_OCP_solution

ext/CTSolveExt.jl

@@ -42,7 +42,7 @@ function CommonSolve.solve(docp::DOCP;
     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))
+        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...)
     end

src/CTDirect.jl

@@ -22,7 +22,7 @@ include("solution.jl")
 include("solve.jl")
 
 # re exports
-export solve # CommonSolve
+export solve # from CommonSolve, extended in CTSolveExt
 
 # exports
 export available_methods
@@ -39,6 +39,4 @@ export export_OCP_solution
 export read_OCP_solution
 export OCP_Solution_discrete
 
-export _OptimalControlInit #temp, later from CTBase
-
 end

src/problem.jl

@@ -177,9 +177,9 @@ function variables_bounds(docp)
 
     # state box
     offset = 0
-    if dim_state_box(ocp) > 0
+    if dim_state_range(ocp) > 0
         for i in 0:N
-            for j in 1:dim_state_box(ocp)
+            for j in 1:dim_state_range(ocp)
                 indice = docp.state_box[2][j]
                 l_var[offset+indice] = docp.state_box[1][j]
                 u_var[offset+indice] = docp.state_box[3][j]
@@ -190,9 +190,9 @@ function variables_bounds(docp)
 
     # control box
     offset = (N+1) * docp.dim_NLP_x
-    if dim_control_box(ocp) > 0
+    if dim_control_range(ocp) > 0
         for i in 0:N
-            for j in 1:dim_control_box(ocp)
+            for j in 1:dim_control_range(ocp)
                 indice = docp.control_box[2][j]
                 l_var[offset+indice] = docp.control_box[1][j]
                 u_var[offset+indice] = docp.control_box[3][j]
@@ -203,8 +203,8 @@ function variables_bounds(docp)
 
     # variable box
     offset = (N+1) * (docp.dim_NLP_x + docp.dim_NLP_u)
-    if dim_variable_box(ocp) > 0
-        for j in 1:dim_variable_box(ocp)
+    if dim_variable_range(ocp) > 0
+        for j in 1:dim_variable_range(ocp)
             indice = docp.variable_box[2][j]
             l_var[offset+indice] = docp.variable_box[1][j]
             u_var[offset+indice] = docp.variable_box[3][j]

src/solution.jl

@@ -128,20 +128,20 @@ function OCPSolutionFromDOCP_raw(docp, T, X, U, v, P;
     end
 
     # box constraints multipliers
-    if dim_state_box(ocp) > 0
+    if dim_state_range(ocp) > 0
         # remove additional state for lagrange cost
         mbox_x_l = ctinterpolate(T, matrix2vec(mult_state_box_lower[:,1:ocp.state_dimension], 1))
         mbox_x_u = ctinterpolate(T, matrix2vec(mult_state_box_upper[:,1:ocp.state_dimension], 1))
         sol.infos[:mult_state_box_lower] = t -> mbox_x_l(t)
         sol.infos[:mult_state_box_upper] = t -> mbox_x_u(t)    
     end
-    if dim_control_box(ocp) > 0
+    if dim_control_range(ocp) > 0
         mbox_u_l = ctinterpolate(T, matrix2vec(mult_control_box_lower, 1))
         mbox_u_u = ctinterpolate(T, matrix2vec(mult_control_box_upper, 1))
         sol.infos[:mult_control_box_lower] = t -> mbox_u_l(t)
         sol.infos[:mult_control_box_upper] = t -> mbox_u_u(t)
     end
-    if dim_variable_box(ocp) > 0
+    if dim_variable_range(ocp) > 0
         sol.infos[:mult_variable_box_lower] = mult_variable_box_lower
         sol.infos[:mult_variable_box_upper] = mult_variable_box_upper 
     end
@@ -193,7 +193,7 @@ function parse_DOCP_solution(docp, solution, multipliers_constraints, multiplier
         mult_state_box_upper[i,:] = vget_state_at_time_step(mult_U, docp, i-1)
         mult_control_box_upper[i,:] = vget_control_at_time_step(mult_U, docp, i-1)
     end
-    if dim_variable_box(ocp) > 0
+    if dim_variable_range(ocp) > 0
         mult_variable_box_lower = get_variable(mult_L, docp)
         mult_variable_box_upper = get_variable(mult_U, docp)
     end

src/solve.jl

@@ -29,7 +29,7 @@ function directTranscription(ocp::OptimalControlModel,
     docp = DOCP(ocp, grid_size, time_grid)
 
     # set initial guess
-    x0 = DOCP_initial_guess(docp, _OptimalControlInit(init, state_dim=ocp.state_dimension, control_dim=ocp.control_dimension, variable_dim=ocp.variable_dimension))
+    x0 = DOCP_initial_guess(docp, OptimalControlInit(init, state_dim=ocp.state_dimension, control_dim=ocp.control_dimension, variable_dim=ocp.variable_dimension))
 
     # set bounds
     docp.var_l, docp.var_u = variables_bounds(docp)
@@ -67,6 +67,6 @@ function setInitialGuess(docp::DOCP, init)
 
     nlp = getNLP(docp)
     ocp = docp.ocp
-    nlp.meta.x0 .= DOCP_initial_guess(docp, _OptimalControlInit(init, state_dim=ocp.state_dimension, control_dim=ocp.control_dimension, variable_dim=ocp.variable_dimension))
+    nlp.meta.x0 .= DOCP_initial_guess(docp, OptimalControlInit(init, state_dim=ocp.state_dimension, control_dim=ocp.control_dimension, variable_dim=ocp.variable_dimension))
 
 end