Format code with JuliaFormatter

.JuliaFormatter.toml

@@ -0,0 +1,8 @@
+# Configuration file for JuliaFormatter.jl
+# For more information, see: https://domluna.github.io/JuliaFormatter.jl/stable/config/
+
+always_for_in = true
+always_use_return = true
+margin = 92
+remove_extra_newlines = true
+short_to_long_function_def = true

src/MPCCModels.jl

@@ -8,7 +8,7 @@ using NLPModels, LinearAlgebra, SparseArrays
     s.t. lbc ≤ c(w) ≤ ubc
          lbG ≤ G(w) ⟂ H(w) ≥ lbH
 """
-abstract type AbstractMPCCModel{T, VT} end
+abstract type AbstractMPCCModel{T,VT} end
 
 include("utils.jl")
 include("lifted_model.jl")
@@ -25,8 +25,10 @@ export comp_left, comp_left!, comp_right, comp_right!
 export lcomp_left, lcomp_left!, lcomp_right, lcomp_right!
 export comp_res_left, comp_res_left!, comp_res_right, comp_res_right!
 export comp_res_prod!
-export jac_comp_left_structure, jac_comp_left_structure!, jac_comp_right_structure, jac_comp_right_structure!
-export jac_comp_left_coord, jac_comp_left_coord!, jac_comp_right_coord, jac_comp_right_coord!
+export jac_comp_left_structure,
+    jac_comp_left_structure!, jac_comp_right_structure, jac_comp_right_structure!
+export jac_comp_left_coord,
+    jac_comp_left_coord!, jac_comp_right_coord, jac_comp_right_coord!
 export jac_comp_left, jac_comp_right
 export comp_residual, comp_residual_product, comp_residual_sum
 end

src/lifted_model.jl

@@ -4,8 +4,7 @@
   The lifting variables then take on the bounds of the original
 """
 ######################### Metadata Definition #########################
-struct LiftedNLPModelMeta{T, VT, MT <: AbstractNLPModelMeta{T, VT}} <:
-       AbstractNLPModelMeta{T, VT}
+struct LiftedNLPModelMeta{T,VT,MT<:AbstractNLPModelMeta{T,VT}} <: AbstractNLPModelMeta{T,VT}
     parent::MT
 
     ind_lift::IndexSet
@@ -20,10 +19,10 @@ struct LiftedNLPModelMeta{T, VT, MT <: AbstractNLPModelMeta{T, VT}} <:
 end
 
 ######################### LiftedNLPModel Definition #########################
-struct LiftedNLPModel{T, VT, NLP <: AbstractNLPModel{T, VT}, NMT} <: AbstractNLPModel{T, VT}
+struct LiftedNLPModel{T,VT,NLP<:AbstractNLPModel{T,VT},NMT} <: AbstractNLPModel{T,VT}
     nlp::NLP
 
-    meta::LiftedNLPModelMeta{T, VT, NMT}
+    meta::LiftedNLPModelMeta{T,VT,NMT}
     counters::NLPModels.Counters
 end
 
@@ -64,15 +63,15 @@ function LiftedNLPModel(nlp::AbstractNLPModel, ind_lift::IndexSet)
 
     parent_meta = NLPModels.NLPModelMeta(
         nlp.meta,
-        nvar=nvar,
-        lcon=lcon,
-        ucon=ucon,
-        lvar=lvar,
-        uvar=uvar,
-        x0=x0,
-        nnzj=nnzj,
-        nln_nnzj=nln_nnzj,
-        lin_nnzj=lin_nnzj,
+        nvar = nvar,
+        lcon = lcon,
+        ucon = ucon,
+        lvar = lvar,
+        uvar = uvar,
+        x0 = x0,
+        nnzj = nnzj,
+        nln_nnzj = nln_nnzj,
+        lin_nnzj = lin_nnzj,
     )
 
     meta = LiftedNLPModelMeta(
@@ -273,36 +272,36 @@ function NLPModels.hess_structure!(
 end
 
 function NLPModels.hess_coord!(
-    lnlp::LiftedNLPModel{T, VT},
+    lnlp::LiftedNLPModel{T,VT},
     x::AbstractVector{T},
     y::AbstractVector{T},
     H::AbstractVector{T};
-    obj_weight::Real=one(T),
-) where {T, VT}
+    obj_weight::Real = one(T),
+) where {T,VT}
     return @views hess_coord!(
         lnlp.nlp,
         x[1:get_nvar(lnlp.nlp)],
         y,
         H;
-        obj_weight=obj_weight,
+        obj_weight = obj_weight,
     )
 end
 
 function NLPModels.hprod!(
-    lnlp::LiftedNLPModel{T, VT},
+    lnlp::LiftedNLPModel{T,VT},
     x::AbstractVector{T},
     y::AbstractVector{T},
     v::AbstractVector{T},
     Hv::AbstractVector;
-    obj_weight::Real=one(T),
-) where {T, VT}
+    obj_weight::Real = one(T),
+) where {T,VT}
     @views hprod!(
         lnlp.nlp,
         x[1:get_nvar(lnlp.nlp)],
         y,
         v[1:get_nvar(lnlp.nlp)],
         Hv[1:get_nvar(lnlp.nlp)];
-        obj_weight=obj_weight,
+        obj_weight = obj_weight,
     )
     Hv[(get_nvar(lnlp.nlp)+1):get_nvar(lnlp)] .= 0
     return Hv