Format .jl files (#73)

Co-authored-by: sshin23 <sshin23@users.noreply.github.com>

Author: github-actions[bot]

ext/ExaModelsMOI.jl

@@ -334,13 +334,14 @@ end
 function _exafy(e::MOI.ScalarAffineFunction{T}, p = ()) where {T}
     ec = if !isempty(e.terms)
         sum(begin
-                c1, p = _exafy(term, p)
-                c1
-            end for term in e.terms) + ExaModels.ParIndexed(ExaModels.ParSource(), length(p) + 1)
+            c1, p = _exafy(term, p)
+            c1
+        end for term in e.terms) +
+        ExaModels.ParIndexed(ExaModels.ParSource(), length(p) + 1)
     else
         ExaModels.ParIndexed(ExaModels.ParSource(), length(p) + 1)
     end
-    
+
     return ec, (p..., e.constant)
 end
 

src/nlp.jl

@@ -256,35 +256,35 @@ end
     Var(v.offset + idxx(is .- (_start.(v.size) .- 1), _length.(v.size)))
 end
 
-function _bound_check(sizes, i::I) where I <: Integer
+function _bound_check(sizes, i::I) where {I<:Integer}
     __bound_check(sizes[1], i)
 end
-function _bound_check(sizes, is::NTuple{N,I}) where {I <: Integer, N}
+function _bound_check(sizes, is::NTuple{N,I}) where {I<:Integer,N}
     __bound_check(sizes[1], is[1])
     _bound_check(sizes[2:end], is[2:end])
 end
 _bound_check(sizes, is) = nothing
 _bound_check(sizes, is::Tuple{}) = nothing
 
-function __bound_check(a::I,b::I) where I <: Integer
-    @assert(1<= b <= a, "Variable index bound error")
+function __bound_check(a::I, b::I) where {I<:Integer}
+    @assert(1 <= b <= a, "Variable index bound error")
 end
-function __bound_check(a::UnitRange{Int},b::I) where I <: Integer
+function __bound_check(a::UnitRange{Int}, b::I) where {I<:Integer}
     @assert(b in a, "Variable index bound error")
 end
 
 
 function append!(backend, a, b::Base.Generator, lb)
     b = _adapt_gen(b)
-    
+
     la = length(a)
     resize!(a, la + lb)
     map!(b.f, view(a, (la+1):(la+lb)), convert_array(b.iter, backend))
     return a
 end
 
 function append!(backend, a, b::Base.Generator{UnitRange{I}}, lb) where {I}
-    
+
     la = length(a)
     resize!(a, la + lb)
     map!(b.f, view(a, (la+1):(la+lb)), b.iter)
@@ -450,8 +450,8 @@ function constraint(
     start = zero(T),
     lcon = zero(T),
     ucon = zero(T),
-    ) where {T,C<:ExaCore{T}}
-    
+) where {T,C<:ExaCore{T}}
+
     gen = _adapt_gen(gen)
     f = SIMDFunction(gen, c.ncon, c.nnzj, c.nnzh)
     pars = gen.iter
@@ -512,7 +512,7 @@ function _constraint(c, f, pars, start, lcon, ucon)
 end
 
 function constraint!(c::C, c1, gen::Base.Generator) where {C<:ExaCore}
-    
+
     gen = _adapt_gen(gen)
     f = SIMDFunction(gen, offset0(c1, 0), c.nnzj, c.nnzh)
     pars = gen.iter
@@ -648,7 +648,7 @@ function hess_coord!(
     x::AbstractVector,
     y::AbstractVector,
     hess::AbstractVector;
-   obj_weight = one(eltype(x)),
+    obj_weight = one(eltype(x)),
 )
 
     fill!(hess, zero(eltype(hess)))
@@ -707,21 +707,23 @@ end
 @inbounds @inline offset0(a::C, i) where {C<:ConstraintAug} = offset0(a.f, a.itr, i)
 @inbounds @inline offset0(f::F, itr, i) where {P<:Pair,F<:SIMDFunction{P}} =
     f.o0 + f.f.first(itr[i], nothing)
-@inbounds @inline offset0(f::F, itr, i) where {T<:Tuple,P<:Pair{T},F<:SIMDFunction{P}} = f.o0 + idxx(coord(itr, i, f.f.first), Base.size(itr))
+@inbounds @inline offset0(f::F, itr, i) where {T<:Tuple,P<:Pair{T},F<:SIMDFunction{P}} =
+    f.o0 + idxx(coord(itr, i, f.f.first), Base.size(itr))
 
 @inline idx(itr, I) = @inbounds itr[I]
-@inline idx(itr::Base.Iterators.ProductIterator{V}, I) where V =  _idx(I-1, itr.iterators, Base.size(itr))
+@inline idx(itr::Base.Iterators.ProductIterator{V}, I) where {V} =
+    _idx(I - 1, itr.iterators, Base.size(itr))
 @inline function _idx(n, (vec1, vec...), (si1, si...))
     d, r = divrem(n, si1)
-    return (vec1[r + 1], _idx(d, vec, si)...)
+    return (vec1[r+1], _idx(d, vec, si)...)
 end
-@inline _idx(n, (vec,), ::Tuple{Int}) = @inbounds vec[n + 1]
+@inline _idx(n, (vec,), ::Tuple{Int}) = @inbounds vec[n+1]
 
 @inline idxx(coord, si) = _idxx(coord, si, 1) + 1
-@inline _idxx(coord, si, a) = a * (coord[1] - 1) + _idxx(coord[2:end], si[2:end], a*si[1])
+@inline _idxx(coord, si, a) = a * (coord[1] - 1) + _idxx(coord[2:end], si[2:end], a * si[1])
 @inline _idxx(::Tuple{}, ::Tuple{}, a) = 0
 
-@inline coord(itr, i, (f,fs...)) = (f(idx(itr,i), nothing), coord(itr, i, fs)...)
+@inline coord(itr, i, (f, fs...)) = (f(idx(itr, i), nothing), coord(itr, i, fs)...)
 @inline coord(itr, i, ::Tuple{}) = ()
 
 for (thing, val) in [(:solution, 1), (:multipliers_L, 0), (:multipliers_U, 2)]
@@ -801,4 +803,4 @@ end
 
 
 _adapt_gen(gen) = Base.Generator(gen.f, collect(gen.iter))
-_adapt_gen(gen::Base.Generator{P}) where P <: Union{AbstractArray,AbstractRange} = gen
+_adapt_gen(gen::Base.Generator{P}) where {P<:Union{AbstractArray,AbstractRange}} = gen

test/NLPTest/NLPTest.jl

@@ -136,7 +136,7 @@ function runtests()
 
                         m, vars2, cons2 = jump_model(nothing, args)
                         m2 = MathOptNLPModel(m)
-                        
+
                         set_optimizer(m, MadNLP.Optimizer)
                         set_optimizer_attribute(m, "print_level", MadNLP.ERROR)
                         optimize!(m)

test/NLPTest/luksan.jl

@@ -7,7 +7,7 @@ function luksan_vlcek_con1(x, i, j)
 end
 function luksan_vlcek_con2(x, i, j)
     return sin(x[i+1, j] - x[i+2, j])sin(x[i+1, j] + x[i+2, j]) + 4x[i+1, j] -
-        x[i, j]exp(x[i, j] - x[i+1, j]) - 3
+           x[i, j]exp(x[i, j] - x[i+1, j]) - 3
 end
 
 function luksan_vlcek_x0(i)
@@ -17,30 +17,35 @@ end
 function _exa_luksan_vlcek_model(backend, N; M = 1)
 
     c = ExaCore(backend = backend)
-    x = variable(c, N, M; start = [luksan_vlcek_x0(i) for i = 1:N, j=1:M])
-    s = constraint(c, luksan_vlcek_con1(x, i, j) for i = 1:N-2, j=1:M)
-    constraint!(c, s, (i,j) => luksan_vlcek_con2(x, i, j) for i = 1:N-2, j=1:M)
-    objective(c, luksan_vlcek_obj(x, i, j) for i = 2:N, j=1:M)
+    x = variable(c, N, M; start = [luksan_vlcek_x0(i) for i = 1:N, j = 1:M])
+    s = constraint(c, luksan_vlcek_con1(x, i, j) for i = 1:N-2, j = 1:M)
+    constraint!(c, s, (i, j) => luksan_vlcek_con2(x, i, j) for i = 1:N-2, j = 1:M)
+    objective(c, luksan_vlcek_obj(x, i, j) for i = 2:N, j = 1:M)
 
     return ExaModel(c; prod = true), (x,), (s,)
 end
 
 function exa_luksan_vlcek_model(backend, N; M = 1)
-    m, vars, cons = _exa_luksan_vlcek_model(backend, N;M =  M)
+    m, vars, cons = _exa_luksan_vlcek_model(backend, N; M = M)
     return m
 end
 
 function _jump_luksan_vlcek_model(backend, N; M = 1)
     jm = JuMP.Model()
 
-    JuMP.@variable(jm, x[i = 1:N, j=1:M], start = mod(i, 2) == 1 ? -1.2 : 1.0)
+    JuMP.@variable(jm, x[i = 1:N, j = 1:M], start = mod(i, 2) == 1 ? -1.2 : 1.0)
     JuMP.@NLconstraint(
         jm,
-        s[i = 1:N-2, j=1:M],
-        3x[i+1,j]^3 + 2x[i+2,j] - 5 + sin(x[i+1,j] - x[i+2,j])sin(x[i+1,j] + x[i+2,j]) + 4x[i+1,j] -
-        x[i,j]exp(x[i,j] - x[i+1,j]) - 3 == 0.0
+        s[i = 1:N-2, j = 1:M],
+        3x[i+1, j]^3 + 2x[i+2, j] - 5 +
+        sin(x[i+1, j] - x[i+2, j])sin(x[i+1, j] + x[i+2, j]) +
+        4x[i+1, j] - x[i, j]exp(x[i, j] - x[i+1, j]) - 3 == 0.0
+    )
+    JuMP.@NLobjective(
+        jm,
+        Min,
+        sum(100(x[i-1, j]^2 - x[i, j])^2 + (x[i-1, j] - 1)^2 for i = 2:N, j = 1:M)
     )
-    JuMP.@NLobjective(jm, Min, sum(100(x[i-1,j]^2 - x[i,j])^2 + (x[i-1,j] - 1)^2 for i = 2:N, j=1:M))
 
     return jm, (x,), (s,)
 end