size -> axes (#262)

src/Certificate/Symmetry/wedderburn.jl

@@ -135,7 +135,7 @@ function _gram_basis(pattern::Pattern, basis, ::Type{T}) where {T}
             if !all(is_orthogonal, S)
                 R = orthogonalize(R)
                 S = matrix_reps(pattern, R, basis, T, _OrthogonalMatrix())
-                for i in 1:size(R, 1)
+                for i in axes(R, 1)
                     R[i, :] = LinearAlgebra.normalize(R[i, :])
                 end
                 S = matrix_reps(pattern, R, basis, T, _OrthogonalMatrix())

src/sosdec.jl

@@ -44,7 +44,7 @@ function SOSDecomposition(p::GramMatrix, ranktol=0.0,
     # TODO LDL^T factorization for SDP is missing in Julia
     # it would be nice to have though
     nM, cM, Q = MultivariateMoments.lowrankchol(Matrix(getmat(p)), dec, ranktol)
-    ps = [MP.polynomial(Q[i,:], p.basis) for i in 1:size(Q, 1)]
+    ps = [MP.polynomial(Q[i,:], p.basis) for i in axes(Q, 1)]
     return SOSDecomposition(ps)
 end
 # Without LDL^T, we need to do float(T)

test/ceg_test.jl

@@ -127,7 +127,7 @@ end
         @test CEG.add_node!(G, 1) == 1
         @test CEG.add_edge!(G, (1, 2)) == (1, 2)
         @test CEG.add_edge!.(G, [(1, 2), (2, 3)]) isa Vector{Tuple{Int, Int}}
-        @test CEG.add_clique!(G, [1, 2, 3]) == nothing
+        @test CEG.add_clique!(G, [1, 2, 3]) === nothing
     end
 
     @testset "show" begin

test/symmetry.jl

@@ -14,7 +14,7 @@ function test_linsolve()
         b = A' * x
         @test Certificate.Symmetry._linsolve(A, b, Symmetry._RowEchelonMatrix()) ≈ x
         B = float.(A)
-        for i in 1:size(B, 1)
+        for i in axes(B, 1)
             B[i, :] = normalize(B[i, :])
         end
         b = B' * x