Update JuliaFormatter to v2

.github/workflows/format_check.yml

@@ -18,7 +18,7 @@ jobs:
         shell: julia --color=yes {0}
         run: |
           using Pkg
-          Pkg.add(PackageSpec(name="JuliaFormatter", version="1"))
+          Pkg.add(PackageSpec(name="JuliaFormatter", version="2"))
           using JuliaFormatter
           format(".", verbose=true)
           out = String(read(Cmd(`git diff`)))

src/Bridges/Constraint/bridges/BinPackingToMILPBridge.jl

@@ -227,7 +227,7 @@ function MOI.Bridges.final_touch(
         end
         unit_f = MOI.ScalarAffineFunction(MOI.ScalarAffineTerm{T}[], zero(T))
         convex_f = MOI.ScalarAffineFunction(MOI.ScalarAffineTerm{T}[], zero(T))
-        for xi in ret[1]::T:ret[2]::T
+        for xi in (ret[1]::T):(ret[2]::T)
             new_var, _ = MOI.add_constrained_variable(model, MOI.ZeroOne())
             push!(bridge.variables, new_var)
             if !haskey(S, xi)

src/Bridges/Constraint/bridges/CircuitToMILPBridge.jl

@@ -56,7 +56,7 @@ function bridge_constraint(
     s::MOI.Circuit,
 ) where {T,F<:Union{MOI.VectorOfVariables,MOI.VectorAffineFunction{T}}}
     n = MOI.dimension(s)
-    z = [MOI.add_constrained_variable(model, MOI.ZeroOne())[1] for _ in 1:n^2]
+    z = [MOI.add_constrained_variable(model, MOI.ZeroOne())[1] for _ in 1:(n^2)]
     Z = reshape(z, n, n)
     equal_to = MOI.ConstraintIndex{MOI.ScalarAffineFunction{T},MOI.EqualTo{T}}[]
     for (i, x) in enumerate(MOI.Utilities.eachscalar(f))

src/Bridges/Constraint/bridges/CountDistinctToMILPBridge.jl

@@ -375,7 +375,7 @@ function _final_touch_general_case(
         end
         unit_f = MOI.ScalarAffineFunction(MOI.ScalarAffineTerm{T}[], zero(T))
         convex_f = MOI.ScalarAffineFunction(MOI.ScalarAffineTerm{T}[], zero(T))
-        for xi in ret[1]::T:ret[2]::T
+        for xi in (ret[1]::T):(ret[2]::T)
             new_var, _ = MOI.add_constrained_variable(model, MOI.ZeroOne())
             push!(bridge.variables, new_var)
             if !haskey(S, xi)

src/Bridges/Constraint/bridges/CountGreaterThanToMILPBridge.jl

@@ -214,7 +214,7 @@ function _add_unit_expansion(
     end
     unit_f = MOI.ScalarAffineFunction(MOI.ScalarAffineTerm{T}[], zero(T))
     convex_f = MOI.ScalarAffineFunction(MOI.ScalarAffineTerm{T}[], zero(T))
-    for xi in ret[1]::T:ret[2]::T
+    for xi in (ret[1]::T):(ret[2]::T)
         new_var, _ = MOI.add_constrained_variable(model, MOI.ZeroOne())
         push!(bridge.variables, new_var)
         if !haskey(S, xi)

src/Bridges/Constraint/bridges/LogDetBridge.jl

@@ -31,15 +31,15 @@ function _extract_eigenvalues(
     f_scalars = MOI.Utilities.eachscalar(f)
     tu = [f_scalars[i] for i in 1:offset]
     n = MOI.Utilities.trimap(d, d)
-    X = f_scalars[offset.+(1:n)]
+    X = f_scalars[offset .+ (1:n)]
     N = MOI.Utilities.trimap(2d, 2d)
     Δ = MOI.add_variables(model, n)
     Z = [zero(MOI.ScalarAffineFunction{T}) for i in 1:(N-n)]
     for j in 1:d
         for i in j:d
-            Z[MOI.Utilities.trimap(i, d + j)-n] = Δ[MOI.Utilities.trimap(i, j)]
+            Z[MOI.Utilities.trimap(i, d+j)-n] = Δ[MOI.Utilities.trimap(i, j)]
         end
-        Z[MOI.Utilities.trimap(d + j, d + j)-n] = Δ[MOI.Utilities.trimap(j, j)]
+        Z[MOI.Utilities.trimap(d+j, d+j)-n] = Δ[MOI.Utilities.trimap(j, j)]
     end
     Y = MOI.Utilities.operate(vcat, T, X, MOI.Utilities.vectorize(Z))
     set = MOI.PositiveSemidefiniteConeTriangle(2d)

src/Bridges/Constraint/bridges/ReifiedCountDistinctToMILPBridge.jl

@@ -212,7 +212,7 @@ function MOI.get(
 )
     return MOI.ConstraintIndex{MOI.VariableIndex,MOI.ZeroOne}[
         MOI.ConstraintIndex{MOI.VariableIndex,MOI.ZeroOne}(x.value) for
-        x in bridge.variables[1:end-2]
+        x in bridge.variables[1:(end-2)]
     ]
 end
 
@@ -279,7 +279,7 @@ function MOI.Bridges.final_touch(
         end
         unit_f = MOI.ScalarAffineFunction(MOI.ScalarAffineTerm{T}[], zero(T))
         convex_f = MOI.ScalarAffineFunction(MOI.ScalarAffineTerm{T}[], zero(T))
-        for xi in ret[1]::T:ret[2]::T
+        for xi in (ret[1]::T):(ret[2]::T)
             new_var, _ = MOI.add_constrained_variable(model, MOI.ZeroOne())
             push!(bridge.variables, new_var)
             if !haskey(S, xi)

src/Bridges/Constraint/map.jl

@@ -239,7 +239,7 @@ function vector_of_variables_constraints(map::Map)
         Base.Iterators.Filter(
             i ->
                 map.bridges[i] !== nothing &&
-                    map.constraint_types[i][1] == MOI.VectorOfVariables,
+                map.constraint_types[i][1] == MOI.VectorOfVariables,
             eachindex(map.bridges),
         ),
     )

src/Bridges/Variable/bridges/FreeBridge.jl

@@ -105,7 +105,7 @@ function MOI.get(
 ) where {T}
     n = div(length(bridge.variables), 2)
     primal = MOI.get(model, attr, bridge.constraint)
-    return primal[1:n] - primal[n.+(1:n)]
+    return primal[1:n] - primal[n .+ (1:n)]
 end
 
 # The transformation is x_free = [I -I] * x

src/Bridges/Variable/map.jl

@@ -553,7 +553,7 @@ variables corresponding to `ci`.
 function function_for(map::Map, ci::MOI.ConstraintIndex{MOI.VectorOfVariables})
     index = map.vector_of_variables_map[-ci.value]
     variables = MOI.VariableIndex[]
-    for i in index:-1:-length(map.bridges)
+    for i in index:-1:(-length(map.bridges))
         vi = MOI.VariableIndex(i)
         if map.index_in_vector[-vi.value] == -1
             continue

src/Bridges/bridge_optimizer.jl

@@ -735,7 +735,7 @@ function _get_all_including_bridged(
             # function, so we may need to report multiple variables.
             push!(user_only_variables, user_variable)
             n = Variable.length_of_vector_of_variables(map, user_variable)
-            for i in 1:n-1
+            for i in 1:(n-1)
                 push!(
                     user_only_variables,
                     MOI.VariableIndex(user_variable.value - i),
@@ -780,7 +780,7 @@ function _get_all_including_bridged(
             # `outer_variable` might represent the start of a VectorOfVariables
             # if multiple user-variables were bridged. Add them all.
             n = Variable.length_of_vector_of_variables(map, outer_variable)
-            for i in 1:n-1
+            for i in 1:(n-1)
                 push!(ret, MOI.VariableIndex(outer_variable.value - i))
             end
         end

src/FileFormats/CBF/read.jl

@@ -360,15 +360,15 @@ function Base.read!(io::IO, model::Model)
                     MOI.VectorAffineTerm{Float64}(4 - l, t) for
                     l in 1:cone_dim for t in data.row_terms[row_idx+l]
                 ],
-                data.row_constants[row_idx.+(3:-1:1)],
+                data.row_constants[row_idx .+ (3:-1:1)],
             )
         else
             MOI.VectorAffineFunction(
                 [
                     MOI.VectorAffineTerm{Float64}(l, t) for l in 1:cone_dim
                     for t in data.row_terms[row_idx+l]
                 ],
-                data.row_constants[row_idx.+(1:cone_dim)],
+                data.row_constants[row_idx .+ (1:cone_dim)],
             )
         end
         con_set = _cbf_to_moi_cone(data, cone_str, cone_dim)
@@ -386,7 +386,7 @@ function Base.read!(io::IO, model::Model)
                 MOI.VectorAffineTerm{Float64}(l, t) for l in 1:cone_dim for
                 t in data.psd_row_terms[row_start+l]
             ],
-            data.psd_row_constants[row_start.+(1:cone_dim)],
+            data.psd_row_constants[row_start .+ (1:cone_dim)],
         )
         MOI.add_constraint(
             model,

src/FileFormats/MPS/MPS.jl

@@ -221,7 +221,7 @@ function Base.write(io::IO, model::Model)
         FileFormats.create_unique_names(
             model;
             warn = options.warn,
-            replacements = Function[s->replace(s, ' ' => '_')],
+            replacements = Function[s->replace(s, ' '=>'_')],
         )
     end
     variables = MOI.get(model, MOI.ListOfVariableIndices())

src/FileFormats/NL/NL.jl

@@ -749,7 +749,7 @@ function Base.write(io::IO, model::Model)
     if n_con > 0
         println(io, "k", length(model.x) - 1)
         total = 0
-        for i in 1:length(model.order)-1
+        for i in 1:(length(model.order)-1)
             total += model.x[model.order[i]].jacobian_count
             println(io, total)
         end

src/Nonlinear/ReverseAD/forward_over_reverse.jl

@@ -60,7 +60,7 @@ function _eval_hessian_inner(
     num_products = size(ex.seed_matrix, 2) # number of hessian-vector products
     num_chunks = div(num_products, CHUNK)
     @assert size(ex.seed_matrix, 1) == length(local_to_global_idx)
-    for k in 1:CHUNK:CHUNK*num_chunks
+    for k in 1:CHUNK:(CHUNK*num_chunks)
         for r in 1:length(local_to_global_idx)
             # set up directional derivatives
             @inbounds idx = local_to_global_idx[r]

src/Nonlinear/ReverseAD/graph_tools.jl

@@ -258,7 +258,7 @@ function _compute_hessian_sparsity(
                 if !all(
                     i ->
                         input_linearity[children_arr[i]] == CONSTANT ||
-                            children_arr[i] == k,
+                        children_arr[i] == k,
                     sibling_idx,
                 )
                     # at least one sibling isn't constant

src/Nonlinear/SymbolicAD/SymbolicAD.jl

@@ -710,7 +710,7 @@ function derivative(f::MOI.ScalarNonlinearFunction, x::MOI.VariableIndex)
         )
     elseif f.head == :min
         g = derivative(f.args[end], x)
-        for i in length(f.args)-1:-1:1
+        for i in (length(f.args)-1):-1:1
             g = MOI.ScalarNonlinearFunction(
                 :ifelse,
                 Any[
@@ -723,7 +723,7 @@ function derivative(f::MOI.ScalarNonlinearFunction, x::MOI.VariableIndex)
         return g
     elseif f.head == :max
         g = derivative(f.args[end], x)
-        for i in length(f.args)-1:-1:1
+        for i in (length(f.args)-1):-1:1
             g = MOI.ScalarNonlinearFunction(
                 :ifelse,
                 Any[
@@ -896,7 +896,7 @@ function Base.show(io::IO, n::_Node)
         print(io, "# ", reinterpret(Float64, n.data))
     else
         type, op, nargs = _operator_to_type_id_nargs(n.operator)
-        children = n.data .+ (0:nargs-1)
+        children = n.data .+ (0:(nargs-1))
         print(io, "# $type(op = $op, children = $children)")
     end
 end

src/Nonlinear/operators.jl

@@ -17,7 +17,7 @@ function _create_binary_switch(ids, exprs)
         :if,
         Expr(:call, :(<=), :id, ids[mid]),
         _create_binary_switch(ids[1:mid], exprs[1:mid]),
-        _create_binary_switch(ids[mid+1:end], exprs[mid+1:end]),
+        _create_binary_switch(ids[(mid+1):end], exprs[(mid+1):end]),
     )
 end
 

src/Nonlinear/parse.jl

@@ -226,7 +226,7 @@ function _parse_comparison_expression(
     x::Expr,
     parent_index::Int,
 )
-    for k in 2:2:length(x.args)-1
+    for k in 2:2:(length(x.args)-1)
         @assert x.args[k] == x.args[2] # don't handle a <= b >= c
     end
     operator_id = data.operators.comparison_operator_to_id[x.args[2]]

src/Test/test_conic.jl

@@ -2611,7 +2611,7 @@ function test_conic_RotatedSecondOrderCone_INFEASIBLE_2(
             @test ≈(MOI.get(model, MOI.ConstraintDual(), c1), d, config)
             @test ≈(
                 MOI.get(model, MOI.ConstraintDual(), c2),
-                T[√ub/√T(2), 1/√(2 * ub), -1],
+                T[√ub/√T(2), 1/√(2*ub), -1],
                 config,
             )
         end
@@ -2642,7 +2642,7 @@ function setup_test(
                     -√ub / 2,
                     zeros(T, n - 1),
                 ),
-                T[√ub/√T(2), 1/√(2 * ub), -1],
+                T[√ub/√T(2), 1/√(2*ub), -1],
             ],
         ),
     )
@@ -4192,7 +4192,7 @@ function _test_conic_DualPowerCone_helper(
         @test ≈(MOI.get(model, MOI.VariablePrimal(), v), v_sol, config)
         @test ≈(
             MOI.get(model, MOI.VariablePrimal(), x),
-            T[-exponent, -(1 - exponent)],
+            T[-exponent, -(1-exponent)],
             config,
         )
         @test ≈(MOI.get(model, MOI.ConstraintPrimal(), vc), v_sol, config)
@@ -4343,7 +4343,7 @@ function test_conic_RelativeEntropyCone(
         if _supports(config, MOI.ConstraintDual)
             @test ≈(
                 MOI.get(model, MOI.ConstraintDual(), relentr),
-                T[1, 2, 3//5, log(T(1 // 2))-1, log(T(5 // 3))-1],
+                T[1, 2, 3//5, log(T(1//2))-1, log(T(5//3))-1],
                 config,
             )
         end
@@ -4362,7 +4362,7 @@ function setup_test(
             mock,
             [2 * log(T(2 // 1)) + 3 * log(T(3 // 5))],
             (MOI.VectorAffineFunction{T}, MOI.RelativeEntropyCone) =>
-                [T[1, 2, 3//5, log(T(1 // 2))-1, log(T(5 // 3))-1]],
+                [T[1, 2, 3//5, log(T(1//2))-1, log(T(5//3))-1]],
         ),
     )
     return

src/Utilities/distance_to_set.jl

@@ -484,7 +484,7 @@
 ) where {T<:Real}
     _check_dimension(x, set)
     p = sortperm(set.weights)
-    pairs = collect(zip(p[1:end-1], p[2:end]))
+    pairs = collect(zip(p[1:(end-1)], p[2:end]))
     _, k = findmax([abs(x[i]) + abs(x[j]) for (i, j) in pairs])
     elements = [x[i] for i in eachindex(x) if !(i in pairs[k])]
     return LinearAlgebra.norm(elements, 2)

src/Utilities/functions.jl

@@ -1974,7 +1974,7 @@ function fill_variables(
     ::Int,
     func::MOI.VectorOfVariables,
 )
-    variables[offset.+(1:length(func.variables))] .= func.variables
+    variables[offset .+ (1:length(func.variables))] .= func.variables
     return
 end
 
@@ -2062,11 +2062,10 @@ function fill_terms(
     func::MOI.VectorOfVariables,
 ) where {T}
     n = number_of_affine_terms(T, func)
-    terms[offset.+(1:n)] .=
-        MOI.VectorAffineTerm.(
-            output_offset .+ (1:n),
-            MOI.ScalarAffineTerm.(one(T), func.variables),
-        )
+    terms[offset .+ (1:n)] .= MOI.VectorAffineTerm.(
+        output_offset .+ (1:n),
+        MOI.ScalarAffineTerm.(one(T), func.variables),
+    )
     return
 end
 
@@ -2077,7 +2076,7 @@ function fill_terms(
     func::Union{MOI.ScalarAffineFunction{T},MOI.VectorAffineFunction{T}},
 ) where {T}
     n = number_of_affine_terms(T, func)
-    terms[offset.+(1:n)] .= offset_term.(func.terms, output_offset)
+    terms[offset .+ (1:n)] .= offset_term.(func.terms, output_offset)
     return
 end
 
@@ -2088,7 +2087,7 @@ function fill_terms(
     func::Union{MOI.ScalarQuadraticFunction{T},MOI.VectorQuadraticFunction{T}},
 ) where {T}
     n = number_of_affine_terms(T, func)
-    terms[offset.+(1:n)] .= offset_term.(func.affine_terms, output_offset)
+    terms[offset .+ (1:n)] .= offset_term.(func.affine_terms, output_offset)
     return
 end
 
@@ -2115,7 +2114,7 @@ function fill_terms(
     func::Union{MOI.ScalarQuadraticFunction{T},MOI.VectorQuadraticFunction{T}},
 ) where {T}
     n = number_of_quadratic_terms(T, func)
-    terms[offset.+(1:n)] .= offset_term.(func.quadratic_terms, output_offset)
+    terms[offset .+ (1:n)] .= offset_term.(func.quadratic_terms, output_offset)
     return
 end
 
@@ -2173,7 +2172,7 @@ function fill_constant(
     func::Union{MOI.VectorAffineFunction{T},MOI.VectorQuadraticFunction{T}},
 ) where {T}
     n = MOI.output_dimension(func)
-    constant[offset.+(1:n)] .= func.constants
+    constant[offset .+ (1:n)] .= func.constants
     return
 end
 

test/FileFormats/MOF/MOF.jl

@@ -1419,9 +1419,11 @@ function test_integer_coefficients()
     @test MOF.moi_to_object(f, names) == (
         type = "ScalarQuadraticFunction",
         affine_terms = [(coefficient = 3, variable = "x")],
-        quadratic_terms = [
-            (coefficient = 4, variable_1 = "x", variable_2 = "x"),
-        ],
+        quadratic_terms = [(
+            coefficient = 4,
+            variable_1 = "x",
+            variable_2 = "x",
+        ),],
         constant = 4,
     )
     return