Update to JuliaFormatter v2 (#400)

Author: blegat

.github/workflows/format_check.yml

@@ -19,7 +19,7 @@ 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("src", verbose=true)
           format("test", verbose=true)

src/Bridges/Constraint/image.jl

@@ -271,10 +271,9 @@ function MOI.get(
             MOI.get(model, attr, bridge.zero_constraint),
         )
     end
-    funcs =
-        MOI.Utilities.eachscalar.(
-            MOI.get.(model, MOI.ConstraintFunction(), bridge.constraints)
-        )
+    funcs = MOI.Utilities.eachscalar.(
+        MOI.get.(model, MOI.ConstraintFunction(), bridge.constraints),
+    )
     z_idx = 0
     return MOI.Utilities.vectorize(
         map(eachindex(bridge.first)) do i

src/Certificate/Sparsity/xor_space.jl

@@ -60,7 +60,7 @@ end
 function XORSpace(n)
     return XORSpace{appropriate_type(n)}(n)
 end
-b(x) = bitstring(x)[end-5:end]
+b(x) = bitstring(x)[(end-5):end]
 e_i(T, i) = (one(T) << (i - 1))
 has_bit(x, i) = !iszero(x & e_i(typeof(x), i))
 function Base.push!(xs::XORSpace{T}, x::T) where {T}

src/Certificate/Symmetry/block_diag.jl

@@ -277,7 +277,7 @@ function block_diag(As, d)
                     end
                     V *= _V
                 end
-                U[:, offset.+eachindex(v)] = V
+                U[:, offset .+ eachindex(v)] = V
                 offset += length(v)
             end
             if offset == n

src/Certificate/newton_polytope.jl

@@ -301,11 +301,11 @@ function _multiplier_maxdegree(maxdegree, g::SA.AlgebraElement, vars)
 end
 
 function _multiplier_deg_range(range, g::SA.AlgebraElement, vars)
-    return _multiplier_mindegree(minimum(range), g, vars):_multiplier_maxdegree(
-        maximum(range),
+    return _multiplier_mindegree(
+        minimum(range),
         g,
         vars,
-    )
+    ):_multiplier_maxdegree(maximum(range), g, vars)
 end
 
 # Cheap approximation of the convex hull as the approximation of:
@@ -344,7 +344,7 @@ function putinar_degree_bounds(
             p,
             gs,
             minus_degrange,
-            -maxdegree:0,
+            (-maxdegree):0,
         )
         isnothing(d) ? d : -d
     else
@@ -365,7 +365,7 @@ function putinar_degree_bounds(
                 p,
                 gs,
                 minus_degrange,
-                -maxdegree:0,
+                (-maxdegree):0,
             )
         else
             0
@@ -837,8 +837,5 @@ function half_newton_polytope(basis::MB.SubBasis, args...)
 end
 
 function monomials_half_newton_polytope(monos, args...)
-    return half_newton_polytope(
-        MB.SubBasis{MB.Monomial}(monos),
-        args...,
-    ).monomials
+    return half_newton_polytope(MB.SubBasis{MB.Monomial}(monos), args...).monomials
 end

test/Tests/chebyshev.jl

@@ -11,7 +11,7 @@ function chebyshev_test(optimizer, config::MOI.Test.Config)
 
     @polyvar x
 
-    Z = monomials((x,), 0:ndeg-1)
+    Z = monomials((x,), 0:(ndeg-1))
 
     model = _model(optimizer)
 

test/Tests/sosdemo5.jl

@@ -48,7 +48,7 @@ function sosdemo5_test(optimizer, config::MOI.Test.Config, feasible::Bool, γ)
     # -- r's -- : constant sum of squares
     Z = monomials(x, 0)
     #r = Matrix{GramMatrix{JuMP.VariableRef}}(4,4) # FIXME doesn't work with 1x1 SDP matrix :(
-    @variable model r[i = 1:4, j = (i+1):4] >= 0
+    @variable model r[i=1:4, j=(i+1):4] >= 0
 
     # Constraint : -sum(Qi(x)*Ai(x)) - sum(rij*Ai(x)*Aj(x)) + I(x) >= 0
     expr = 0

test/certificate.jl

@@ -318,14 +318,13 @@ function test_putinar_ijk(i, j, k, default::Bool, post_filter::Bool = default)
     poly = x^(2i) + y^(2j + 1)
     domain = @set y^(2k + 1) >= 0
     if default
-        certificate =
-            JuMP.moi_set(
-                SOSCone(),
-                MB.SubBasis{MB.Monomial}(monomials(poly)),
-                MB.FullBasis{MB.Monomial,MP.monomial_type(poly)}(),
-                MB.FullBasis{MB.Monomial,MP.monomial_type(poly)}();
-                domain,
-            ).certificate
+        certificate = JuMP.moi_set(
+            SOSCone(),
+            MB.SubBasis{MB.Monomial}(monomials(poly)),
+            MB.FullBasis{MB.Monomial,MP.monomial_type(poly)}(),
+            MB.FullBasis{MB.Monomial,MP.monomial_type(poly)}();
+            domain,
+        ).certificate
     else
         newton = Certificate.NewtonDegreeBounds(tuple())
         if post_filter
@@ -351,10 +350,8 @@ function test_putinar_ijk(i, j, k, default::Bool, post_filter::Bool = default)
             @test isempty(monos)
         else
             w = post_filter ? v[2:2] : v
-            @test monos == MP.monomials(
-                w,
-                max(0, (post_filter ? j : min(i, j)) - k):(j-k),
-            )
+            @test monos ==
+                  MP.monomials(w, max(0, (post_filter ? j : min(i, j))-k):(j-k))
         end
     end
     icert = Certificate.ideal_certificate(certificate)

test/equalitypolyconstr.jl

@@ -1,5 +1,6 @@
 @testset "Polynomial equality constraint with domain with $(factory.optimizer_constructor)" for factory in
                                                                                                 sdp_factories
+
     @polyvar(x, y)
 
     m = SOSModel(factory)

test/segfault.jl

@@ -43,7 +43,7 @@ for (gam, expected) in [(0.8723, :Infeasible), (0.8724, :Optimal)]
 
     # -- r's -- : constant sum of squares
     Z = monomials(x, 0)
-    @variable m r[i = 1:4, j = (i+1):4] >= 0
+    @variable m r[i=1:4, j=(i+1):4] >= 0
 
     # Constraint : -sum(Qi(x)*Ai(x)) - sum(rij*Ai(x)*Aj(x)) + I(x) >= 0
     expr = 0

test/simplepolysos.jl

@@ -3,6 +3,7 @@
 # Semidefinite optimization and convex algebraic geometry SIAM 2013
 @testset "Example 3.35 with $(factory.optimizer_constructor)" for factory in
                                                                   sdp_factories
+
     @polyvar x
     m = SOSModel(factory)
     @constraint m x^4 + 4x^3 + 6x^2 + 4x + 5 in SOSCone() # equivalent to >= 0

test/sosquartic.jl

@@ -2,6 +2,7 @@
 
 @testset "SOSquartic with $(factory.optimizer_constructor)" for factory in
                                                                 sdp_factories
+
     @polyvar x y
     m = SOSModel(factory)
     p = x^4 - y^4

test/sparsity.jl

@@ -286,9 +286,13 @@ function wml19()
                 certificate,
             ),
         ) == Set(
-            monomial_vector.([
-                [x[1]^2 * x[2]^2, x[1] * x[2]^2, 1, x[1]^2 * x[2], x[1] * x[2]],
-            ]),
+            monomial_vector.([[
+                x[1]^2 * x[2]^2,
+                x[1] * x[2]^2,
+                1,
+                x[1]^2 * x[2],
+                x[1] * x[2],
+            ],]),
         )
     end
 end