improve code coverage

src/CTDirect.jl

@@ -16,17 +16,15 @@ const nlp_constraints = CTBase.nlp_constraints
 const matrix2vec = CTBase.matrix2vec
 
 # includes
-#include("init.jl")
 include("utils.jl")
 include("problem.jl")
 include("solution.jl")
 include("solve.jl")
 
 # export functions only for user
+export solve
 export available_methods
 export is_solvable
-export solve
-#export OptimalControlInit
 export directTranscription
 export getNLP
 export setDOCPInit

src/utils.jl

@@ -22,10 +22,6 @@ $(TYPEDSIGNATURES)
 Retrieve state variables at given time step from the NLP variables
 """
 function get_state_at_time_step(xu, docp, i::Int64)
-    """
-        return
-        x(t_i)
-    """
     nx = docp.dim_NLP_state
     n = docp.ocp.state_dimension
     N = docp.dim_NLP_steps
@@ -65,10 +61,6 @@ $(TYPEDSIGNATURES)
 Retrieve control variables at given time step from the NLP variables
 """
 function get_control_at_time_step(xu, docp, i)
-    """
-        return
-        u(t_i)
-    """
     nx = docp.dim_NLP_state
     m = docp.ocp.control_dimension
     N = docp.dim_NLP_steps

test/suite/misc.jl

@@ -0,0 +1,21 @@
+using CTDirect
+
+println("Test: misc")
+
+# simple integrator (control split as positive/negative parts)
+ocp = Model()
+state!(ocp, 1)
+control!(ocp, 2)
+time!(ocp, [0, 1])
+constraint!(ocp, :initial, -1, :initial_constraint)
+constraint!(ocp, :final, 0, :final_constraint)
+constraint!(ocp, :control, 1:2, [0,0], [Inf, Inf], :positive_controls)
+dynamics!(ocp, (x, u) -> -x - u[1] + u[2])
+objective!(ocp, :lagrange, (x, u) -> (u[1]+u[2])^2)
+
+@testset verbose = true showtiming = true ":control_dim_2" begin
+    @test (:adnlp,:ipopt) in available_methods()
+    @test is_solvable(ocp)
+    sol = solve(ocp, print_level=5)
+    @test sol.objective ≈ 0.313 rtol=1e-2
+end

test/test_misc.jl

@@ -0,0 +1,20 @@
+using CTDirect
+
+println("Test: misc")
+
+# simple integrator (control split as positive/negative parts)
+ocp = Model()
+state!(ocp, 1)
+control!(ocp, 2)
+time!(ocp, [0, 1])
+constraint!(ocp, :initial, -1, :initial_constraint)
+constraint!(ocp, :final, 0, :final_constraint)
+constraint!(ocp, :control, 1:2, [0,0], [Inf, Inf], :positive_controls)
+dynamics!(ocp, (x, u) -> -x - u[1] + u[2])
+objective!(ocp, :lagrange, (x, u) -> (u[1]+u[2])^2)
+
+println(available_methods())
+println(is_solvable(ocp))
+
+sol = solve(ocp, print_level=5)
+println("Expected Objective 0.313, found ", sol.objective)