Merge pull request #467 from control-toolbox/auto-juliaformatter-pr

[AUTO] JuliaFormatter.jl run

Author: ocots

ext/CTDirectExtExa.jl

@@ -36,16 +36,26 @@ function CTDirect.build_nlp!(
     # set initial guess (NB. do not broadcast, apparently fails on GPU arrays)
     # NB unused final control in examodel / euler, hence the different x0 sizes
     build_exa = CTModels.get_build_examodel(docp.ocp)
-    
-    ocp = docp.ocp 
+
+    ocp = docp.ocp
     n = CTModels.state_dimension(ocp)
     m = CTModels.control_dimension(ocp)
     q = CTModels.variable_dimension(ocp)
     state = hcat([x0[(1 + i * (n + m)):(1 + i * (n + m) + n - 1)] for i in 0:grid_size]...) # grid_size + 1 states
-    control = hcat([x0[(n + 1 + i * (n + m)):(n + 1 + i * (n + m) + m - 1)] for i in 0:(grid_size - 1)]...) # grid_size controls...
+    control = hcat(
+        [
+            x0[(n + 1 + i * (n + m)):(n + 1 + i * (n + m) + m - 1)] for
+            i in 0:(grid_size - 1)
+        ]...,
+    ) # grid_size controls...
     control = [control control[:, end]] # ... todo: pass indeed to grid_size only for euler(_b), trapeze and midpoint
-    variable = x0[end - q + 1:end]
-    docp.nlp, docp.exa_getter = build_exa(; grid_size=grid_size, backend=exa_backend, scheme=disc_method, init=(variable, state, control)) 
+    variable = x0[(end - q + 1):end]
+    docp.nlp, docp.exa_getter = build_exa(;
+        grid_size=grid_size,
+        backend=exa_backend,
+        scheme=disc_method,
+        init=(variable, state, control),
+    )
     # remark: docp.nlp.meta.x0[1:docp.dim_NLP_variables] = -vcat(state..., control..., variable) # also work, and supersedes previous init via ExaModels start (itself overridden by init in solve)
     return nothing
 end

src/disc/common.jl

@@ -1,4 +1,3 @@
-
 #= Common parts for the discretization =#
 
 """

test/problems/beam.jl

@@ -32,4 +32,4 @@ function beam2()
     end
 
     return ((ocp=beam2, obj=8.898598, name="beam2", init=nothing))
-end
+end

test/problems/double_integrator.jl

@@ -36,7 +36,6 @@ function double_integrator_mintf2()
     return ((ocp=ocp, obj=2.0, name="double_integrator_tf2", init=nothing))
 end
 
-
 # min energy with fixed tf
 function double_integrator_minenergy(T=2)
     @def ocp begin

test/suite/test_exa.jl

@@ -12,7 +12,6 @@ if !isdefined(Main, :goddard2)
     include("../problems/goddard.jl")
 end
 
-
 # test_exa for all backends (CPU + GPU)
 function test_exa(exa_backend, display)
 
@@ -52,7 +51,7 @@ function test_exa(exa_backend, display)
             disc_method=:trapeze,
             exa_backend=exa_backend,
             display=display,
-            grid_size=1000
+            grid_size=1000,
         )
         @test sol.objective ≈ prob.obj rtol = 1e-2
     end
@@ -70,7 +69,7 @@ function test_exa(exa_backend, display)
             exa_backend=exa_backend,
             grid_size=4,
             display=display,
-            init=(state=[xi1, xi2], control=ui,),
+            init=(state=[xi1, xi2], control=ui),
             max_iter=0,
         )
         @test control(sol)(0.5) == ui
@@ -96,7 +95,6 @@ function test_exa(exa_backend, display)
         docp = direct_transcription(prob.ocp, :madnlp, :exa; display=display, grid_size=100)
         @test docp.dim_NLP_variables == 303
     end
-
 end
 
 # CPU tests
@@ -111,4 +109,4 @@ if CUDA.functional()
     test_exa(CUDABackend(), display) # GPU tests
 else
     println("********** CUDA not available, skipping GPU tests")
-end
+end

test/suite/test_initial_guess.jl

@@ -71,7 +71,9 @@ end
     @test isapprox(control(sol).(T), (t -> u_const).(T), rtol=1e-2)
 end
 @testset verbose = true showtiming = true ":constant_xu" begin
-    sol = solve(prob2.ocp, display=false, init=(state=x_const, control=u_const), max_iter=maxiter)
+    sol = solve(
+        prob2.ocp, display=false, init=(state=x_const, control=u_const), max_iter=maxiter
+    )
     T = time_grid(sol)
     @test isapprox(state(sol).(T), (t -> x_const).(T), rtol=1e-2)
     @test isapprox(control(sol).(T), (t -> u_const).(T), rtol=1e-2)
@@ -123,7 +125,9 @@ end
     @test isapprox(control(sol).(T), u_func.(T), rtol=1e-2)
 end
 @testset verbose = true showtiming = true ":functional_xu" begin
-    sol = solve(prob2.ocp, display=false, init=(state=x_func, control=u_func), max_iter=maxiter)
+    sol = solve(
+        prob2.ocp, display=false, init=(state=x_func, control=u_func), max_iter=maxiter
+    )
     T = time_grid(sol)
     @test isapprox(state(sol).(T), x_func.(T), rtol=1e-2)
     @test isapprox(control(sol).(T), u_func.(T), rtol=1e-2)