🤖 Format .jl files (#387)

Co-authored-by: PierreMartinon <17044253+PierreMartinon@users.noreply.github.com>

Author: github-actions[bot]

docs/make.jl

@@ -4,22 +4,22 @@ using DocumenterMermaid
 using CTDirect
 
 # to add docstrings from external packages
-DocMeta.setdocmeta!(CTDirect, :DocTestSetup, :(using CTDirect); recursive = true)
+DocMeta.setdocmeta!(CTDirect, :DocTestSetup, :(using CTDirect); recursive=true)
 
 repo_url = "github.com/control-toolbox/CTDirect.jl"
 
 makedocs(;
-    warnonly = [:cross_references, :autodocs_block],
-    sitename = "CTDirect.jl",
-    format = Documenter.HTML(
-        repolink = "https://"*repo_url,
-        prettyurls = false,
-        assets = [
+    warnonly=[:cross_references, :autodocs_block],
+    sitename="CTDirect.jl",
+    format=Documenter.HTML(
+        repolink="https://"*repo_url,
+        prettyurls=false,
+        assets=[
             asset("https://control-toolbox.org/assets/css/documentation.css"),
             asset("https://control-toolbox.org/assets/js/documentation.js"),
         ],
     ),
-    pages = ["Introduction" => "index.md", "API" => "api.md", "Developers" => "dev-api.md"],
+    pages=["Introduction" => "index.md", "API" => "api.md", "Developers" => "dev-api.md"],
 )
 
 deploydocs(;

ext/CTSolveExtIpopt.jl

@@ -17,12 +17,12 @@ function CTDirect.solve_docp(
     solver_backend::CTDirect.IpoptBackend,
     docp::CTDirect.DOCP,
     nlp;
-    display::Bool = CTDirect.__display(),
-    max_iter::Integer = CTDirect.__max_iterations(),
-    tol::Real = CTDirect.__tolerance(),
-    print_level::Integer = CTDirect.__ipopt_print_level(),
-    mu_strategy::String = CTDirect.__ipopt_mu_strategy(),
-    linear_solver::String = CTDirect.__ipopt_linear_solver(),
+    display::Bool=CTDirect.__display(),
+    max_iter::Integer=CTDirect.__max_iterations(),
+    tol::Real=CTDirect.__tolerance(),
+    print_level::Integer=CTDirect.__ipopt_print_level(),
+    mu_strategy::String=CTDirect.__ipopt_mu_strategy(),
+    linear_solver::String=CTDirect.__ipopt_linear_solver(),
     kwargs...,
 )
 
@@ -55,13 +55,13 @@ function CTDirect.solve_docp(
     docp_solution = solve!(
         solver,
         nlp,
-        print_level = print_level,
-        mu_strategy = mu_strategy,
-        tol = tol,
-        max_iter = max_iter,
-        sb = "yes",
+        print_level=print_level,
+        mu_strategy=mu_strategy,
+        tol=tol,
+        max_iter=max_iter,
+        sb="yes",
         #check_derivatives_for_naninf = "yes",
-        linear_solver = linear_solver;
+        linear_solver=linear_solver;
         kwargs...,
     )
 

ext/CTSolveExtKnitro.jl

@@ -17,10 +17,10 @@ function CTDirect.solve_docp(
     solver_backend::CTDirect.KnitroBackend,
     docp::CTDirect.DOCP,
     nlp;
-    display::Bool = CTDirect.__display(),
-    max_iter::Integer = CTDirect.__max_iterations(),
-    tol::Real = CTDirect.__tolerance(),
-    print_level::Integer = CTDirect.__knitro_print_level(),
+    display::Bool=CTDirect.__display(),
+    max_iter::Integer=CTDirect.__max_iterations(),
+    tol::Real=CTDirect.__tolerance(),
+    print_level::Integer=CTDirect.__knitro_print_level(),
     kwargs...,
 )
 

ext/CTSolveExtMadNLP.jl

@@ -17,10 +17,10 @@ function CTDirect.solve_docp(
     solver_backend::CTDirect.MadNLPBackend,
     docp::CTDirect.DOCP,
     nlp;
-    display::Bool = CTDirect.__display(),
-    max_iter::Integer = CTDirect.__max_iterations(),
-    tol::Real = CTDirect.__tolerance(),
-    linear_solver::String = CTDirect.__madnlp_linear_solver(), # ?
+    display::Bool=CTDirect.__display(),
+    max_iter::Integer=CTDirect.__max_iterations(),
+    tol::Real=CTDirect.__tolerance(),
+    linear_solver::String=CTDirect.__madnlp_linear_solver(), # ?
     kwargs...,
 )
 

src/default.jl

@@ -22,15 +22,15 @@ $(TYPEDSIGNATURES)
 Used to set the default initial guess.
 The default value is `nothing` and will correspond to 0.1 for all variables.
 """
-__ocp_init() = nothing 
+__ocp_init() = nothing
 
 """
 $(TYPEDSIGNATURES)
 
 Used to set the default display toggle.
 The default value is true.
 """
-__display() = true 
+__display() = true
 
 """
 $(TYPEDSIGNATURES)

src/disc/common.jl

@@ -1,6 +1,10 @@
+
+
+
 #= Common parts for the discretization =#
 
 
+
 """
 $(TYPEDSIGNATURES)
 
@@ -9,7 +13,7 @@ Convention: stored at the end, hence not dependent on the discretization method
 Vector output
 """
 function get_OCP_variable(xu, docp::DOCP)
-    return @view xu[(docp.dim_NLP_variables - docp.dims.NLP_v + 1):docp.dim_NLP_variables]
+    return @view xu[(docp.dim_NLP_variables-docp.dims.NLP_v+1):docp.dim_NLP_variables]
 end
 
 
@@ -22,7 +26,7 @@ Vector output
 """
 function get_OCP_state_at_time_step(xu, docp::DOCP, i)
     offset = (i-1) * docp.discretization._step_variables_block
-    return @view xu[(offset + 1):(offset + docp.dims.OCP_x)]
+    return @view xu[(offset+1):(offset+docp.dims.OCP_x)]
 end
 """
 $(TYPEDSIGNATURES)
@@ -32,7 +36,7 @@ Convention: 1 <= i <= dim_NLP_steps+1   (no check for actual lagrange cost prese
 """
 function get_lagrange_state_at_time_step(xu, docp::DOCP, i)
     offset = (i-1) * docp.discretization._step_variables_block
-    return xu[offset + docp.dims.NLP_x]
+    return xu[offset+docp.dims.NLP_x]
 end
 
 """
@@ -48,7 +52,7 @@ function get_OCP_control_at_time_step(xu, docp::DOCP, i)
         i = docp.time.steps
     end
     offset = (i-1) * docp.discretization._step_variables_block + docp.dims.NLP_x
-    return @view xu[(offset + 1):(offset + docp.dims.NLP_u)]
+    return @view xu[(offset+1):(offset+docp.dims.NLP_u)]
 end
 
 
@@ -62,7 +66,7 @@ Note that passing correct indices is up to the caller, no checks are made here.
 """
 function get_stagevars_at_time_step(xu, docp::DOCP, i, j)
     offset = (i-1) * docp.discretization._step_variables_block + docp.dims.NLP_x + docp.dims.NLP_u + (j-1)*docp.dims.NLP_x
-    return @view xu[(offset + 1):(offset + docp.dims.NLP_x)]
+    return @view xu[(offset+1):(offset+docp.dims.NLP_x)]
 end
 
 
@@ -72,7 +76,7 @@ $(TYPEDSIGNATURES)
 Set optimization variables in the NLP variables (for initial guess)
 """
 function set_optim_variable!(xu, v_init, docp)
-    xu[(end - docp.dims.NLP_v + 1):end] .= v_init
+    xu[(end-docp.dims.NLP_v+1):end] .= v_init
 end
 
 
@@ -86,7 +90,7 @@ function set_state_at_time_step!(xu, x_init, docp::DOCP, i)
     # initialize only actual state variables from OCP (not lagrange state)
     if !isnothing(x_init)
         offset = (i-1) * docp.discretization._step_variables_block
-        xu[(offset + 1):(offset + docp.dims.OCP_x)] .= x_init
+        xu[(offset+1):(offset+docp.dims.OCP_x)] .= x_init
     end
 end
 
@@ -101,7 +105,7 @@ function set_control_at_time_step!(xu, u_init, docp::DOCP, i)
     if !isnothing(u_init)
         if i <= docp.time.steps || (docp.discretization._final_control && i <= docp.time.steps + 1)
             offset = (i-1) * docp.discretization._step_variables_block + docp.dims.NLP_x
-            xu[(offset + 1):(offset + docp.dims.NLP_u)] .= u_init
+            xu[(offset+1):(offset+docp.dims.NLP_u)] .= u_init
         end
     end
 end
@@ -122,9 +126,9 @@ $(TYPEDSIGNATURES)
 
 Build sparsity pattern for Jacobian of constraints
 """
-function DOCP_Jacobian_pattern(docp::DOCP{D}) where (D <: Discretization)
+function DOCP_Jacobian_pattern(docp::DOCP{D}) where (D<:Discretization)
     error("DOCP_Jacobian_pattern not implemented for discretization ", D,
-    " Use option solve(...; adnlp_backend=:optimized)")
+        " Use option solve(...; adnlp_backend=:optimized)")
 end
 
 
@@ -133,9 +137,9 @@ $(TYPEDSIGNATURES)
 
 Build sparsity pattern for Hessian of Lagrangian
 """
-function DOCP_Hessian_pattern(docp::DOCP{D}) where (D <: Discretization)
+function DOCP_Hessian_pattern(docp::DOCP{D}) where (D<:Discretization)
     error("DOCP_Hessian_pattern not implemented for discretization ", D,
-    " Use option solve(...; adnlp_backend=:optimized)")
+        " Use option solve(...; adnlp_backend=:optimized)")
 end
 
 
@@ -154,8 +158,8 @@ function add_nonzero_block!(M, i_start, i_end, j_start, j_end; sym=false)
     return
 end
 function add_nonzero_block!(M, i, j; sym=false)
-    M[i,j] = true
-    sym && (M[j,i] = true)
+    M[i, j] = true
+    sym && (M[j, i] = true)
     return
 end
 function add_nonzero_block!(Is, Js, i_start, i_end, j_start, j_end; sym=false)

src/disc/euler.jl

@@ -26,11 +26,11 @@ struct Euler <: Discretization
 
         # NLP variables size ([state, control]_1..N, final state, variable)
         dim_NLP_variables = dim_NLP_steps * step_variables_block + dim_NLP_x + dim_NLP_v
-        
+
         # NLP constraints size ([dynamics, path]_1..N, final path, boundary, variable)
         dim_NLP_constraints = dim_NLP_steps * (state_stage_eqs_block + step_pathcons_block) + step_pathcons_block + dim_boundary_cons
 
-        if explicit 
+        if explicit
             info = "Euler (explicit), 1st order"
         else
             info = "Euler (implicit), 1st order"
@@ -54,12 +54,12 @@ function get_OCP_control_at_time_step(xu, docp::DOCP{Euler}, i)
         # final time case
         (i == docp.time.steps + 1) && (i = docp.time.steps)
         offset = (i-1) * docp.discretization._step_variables_block + docp.dims.NLP_x
-    else 
+    else
         # initial time case
         (i == 1) && (i = 2)
         offset = (i-2) * docp.discretization._step_variables_block + docp.dims.NLP_x
     end
-    return @view xu[(offset + 1):(offset + docp.dims.NLP_u)]
+    return @view xu[(offset+1):(offset+docp.dims.NLP_u)]
 end
 
 
@@ -87,11 +87,11 @@ function setWorkArray(docp::DOCP{Euler}, xu, time_grid, v)
         u = get_OCP_control_at_time_step(xu, docp, index)
 
         # OCP dynamics
-        CTModels.dynamics(docp.ocp)((@view work[offset+1:offset+docp.dims.OCP_x]), t, x, u, v)
+        CTModels.dynamics(docp.ocp)((@view work[(offset+1):(offset+docp.dims.OCP_x)]), t, x, u, v)
         # lagrange cost
         if docp.flags.lagrange
             work[offset+docp.dims.NLP_x] = CTModels.lagrange(docp.ocp)(t, x, u, v)
-        end   
+        end
     end
     return work
 end
@@ -104,7 +104,7 @@ Set the constraints corresponding to the state equation
 Convention: 1 <= i <= dim_NLP_steps+1
 """
 function setStepConstraints!(docp::DOCP{Euler}, c, xu, v, time_grid, i, work)
-    
+
     # offset for previous steps
     offset = (i-1)*(docp.discretization._state_stage_eqs_block + docp.discretization._step_pathcons_block)
 
@@ -121,20 +121,20 @@ function setStepConstraints!(docp::DOCP{Euler}, c, xu, v, time_grid, i, work)
         offset_dyn_i = (i-1)*docp.dims.NLP_x
 
         # state equation: euler rule
-        @views @. c[offset+1:offset+docp.dims.OCP_x] = xip1 - (xi + hi * work[offset_dyn_i+1:offset_dyn_i+docp.dims.OCP_x])
+        @views @. c[(offset+1):(offset+docp.dims.OCP_x)] = xip1 - (xi + hi * work[(offset_dyn_i+1):(offset_dyn_i+docp.dims.OCP_x)])
         if docp.flags.lagrange
             c[offset+docp.dims.NLP_x] = get_lagrange_state_at_time_step(xu, docp, i+1) - (get_lagrange_state_at_time_step(xu, docp, i) + hi * work[offset_dyn_i+docp.dims.NLP_x])
         end
         offset += docp.dims.NLP_x
 
     end
-   
+
     # 2. path constraints
     if docp.discretization._step_pathcons_block > 0
         ui = get_OCP_control_at_time_step(xu, docp, i)
-        CTModels.path_constraints_nl(docp.ocp)[2]((@view c[offset+1:offset+docp.dims.path_cons]), ti, xi, ui, v)
+        CTModels.path_constraints_nl(docp.ocp)[2]((@view c[(offset+1):(offset+docp.dims.path_cons)]), ti, xi, ui, v)
     end
-    
+
 end
 
 
@@ -213,7 +213,7 @@ function DOCP_Jacobian_pattern(docp::DOCP{Euler})
     uf_start = var_offset-docp.discretization._step_variables_block + docp.dims.NLP_x + 1
     uf_end = var_offset-docp.discretization._step_variables_block + docp.dims.NLP_x + docp.dims.NLP_u
     add_nonzero_block!(Is, Js, c_offset+1, c_offset+c_block, xf_start, xf_end)
-    add_nonzero_block!(Is, Js, c_offset+1,c_offset+c_block, uf_start, uf_end)
+    add_nonzero_block!(Is, Js, c_offset+1, c_offset+c_block, uf_start, uf_end)
     add_nonzero_block!(Is, Js, c_offset+1, c_offset+c_block, v_start, v_end)
 
     # 3. boundary constraints (x0, xf, v)
@@ -258,7 +258,7 @@ function DOCP_Hessian_pattern(docp::DOCP{Euler})
     # -> grouped with term 3. for boundary conditions
     # 0.2 lagrange case (lf)
     # -> 2nd order term is zero
-   
+
     # 1. main loop over steps
     # 1.0 v / v term
     add_nonzero_block!(Is, Js, v_start, v_end, v_start, v_end)
@@ -317,7 +317,7 @@ function DOCP_Hessian_pattern(docp::DOCP{Euler})
 
     # 3.1 null initial condition for lagrangian cost state l0
     # -> 2nd order term is zero
-   
+
     # build and return sparse matrix
     nnzj = length(Is)
     Vs = ones(Bool, nnzj)