Deprecate vectorized two-argument complex methods in favor of compact…

… broadcast syntax.

base/complex.jl

@@ -867,49 +867,3 @@ end
 ## promotion to complex ##
 
 _default_type(T::Type{Complex}) = Complex{Int}
-
-function complex{S<:Real,T<:Real}(A::AbstractArray{S}, B::AbstractArray{T})
-    if size(A) != size(B); throw(DimensionMismatch()); end
-    F = similar(A, typeof(complex(zero(S),zero(T))))
-    RF, RA, RB = eachindex(F), eachindex(A), eachindex(B)
-    if RF == RA == RB
-        for i in RA
-            @inbounds F[i] = complex(A[i], B[i])
-        end
-    else
-        for (iF, iA, iB) in zip(RF, RA, RB)
-            @inbounds F[iF] = complex(A[iA], B[iB])
-        end
-    end
-    return F
-end
-
-function complex{T<:Real}(A::Real, B::AbstractArray{T})
-    F = similar(B, typeof(complex(A,zero(T))))
-    RF, RB = eachindex(F), eachindex(B)
-    if RF == RB
-        for i in RB
-            @inbounds F[i] = complex(A, B[i])
-        end
-    else
-        for (iF, iB) in zip(RF, RB)
-            @inbounds F[iF] = complex(A, B[iB])
-        end
-    end
-    return F
-end
-
-function complex{T<:Real}(A::AbstractArray{T}, B::Real)
-    F = similar(A, typeof(complex(zero(T),B)))
-    RF, RA = eachindex(F), eachindex(A)
-    if RF == RA
-        for i in RA
-            @inbounds F[i] = complex(A[i], B)
-        end
-    else
-        for (iF, iA) in zip(RF, RA)
-            @inbounds F[iF] = complex(A[iA], B)
-        end
-    end
-    return F
-end

base/deprecated.jl

@@ -1380,6 +1380,11 @@ for f in (:sec, :sech, :secd, :asec, :asech,
     @eval @deprecate $f{T<:Number}(A::AbstractArray{T}) $f.(A)
 end
 
+# Deprecate vectorized two-argument complex in favor of compact broadcast syntax
+@deprecate complex(A::AbstractArray, b::Real)           complex.(A, b)
+@deprecate complex(a::Real, B::AbstractArray)           complex.(a, B)
+@deprecate complex(A::AbstractArray, B::AbstractArray)  complex.(A, B)
+
 # Deprecate manually vectorized clamp methods in favor of compact broadcast syntax
 @deprecate clamp(A::AbstractArray, lo, hi) clamp.(A, lo, hi)
 

base/linalg/arpack.jl

@@ -171,7 +171,7 @@ function eupd_wrapper(T, n::Integer, sym::Bool, cmplx::Bool, bmat::String,
         if info[1] != 0
             throw(ARPACKException(info[1]))
         end
-        evec = complex(Array{T}(n, nev+1), Array{T}(n, nev+1))
+        evec = complex.(Array{T}(n, nev+1), Array{T}(n, nev+1))
 
         j = 1
         while j <= nev
@@ -193,7 +193,7 @@ function eupd_wrapper(T, n::Integer, sym::Bool, cmplx::Bool, bmat::String,
             end
         end
 
-        d = complex(dr,di)
+        d = complex.(dr, di)
 
         if j == nev+1
             p = sortperm(dmap(d[1:nev]), rev=true)

base/linalg/blas.jl

@@ -235,7 +235,7 @@ conjugating the first vector.
 
 # Example:
 ```jldoctest
-julia> Base.BLAS.dotc(10, im*ones(10), 1, complex(ones(20), ones(20)), 2)
+julia> Base.BLAS.dotc(10, im*ones(10), 1, complex.(ones(20), ones(20)), 2)
 10.0 - 10.0im
 ```
 """
@@ -249,7 +249,7 @@ with stride `incx` and `n` elements of array `Y` with stride `incy`.
 
 # Example:
 ```jldoctest
-julia> Base.BLAS.dotu(10, im*ones(10), 1, complex(ones(20), ones(20)), 2)
+julia> Base.BLAS.dotu(10, im*ones(10), 1, complex.(ones(20), ones(20)), 2)
 -10.0 + 10.0im
 ```
 """

base/linalg/eigen.jl

@@ -45,7 +45,7 @@ function eigfact!{T<:BlasReal}(A::StridedMatrix{T}; permute::Bool=true, scale::B
         end
         j += 1
     end
-    return Eigen(complex(WR, WI), evec)
+    return Eigen(complex.(WR, WI), evec)
 end
 
 function eigfact!{T<:BlasComplex}(A::StridedMatrix{T}; permute::Bool=true, scale::Bool=true)
@@ -162,7 +162,7 @@ make rows and columns more equal in norm.
 function eigvals!{T<:BlasReal}(A::StridedMatrix{T}; permute::Bool=true, scale::Bool=true)
     issymmetric(A) && return eigvals!(Symmetric(A))
     _, valsre, valsim, _ = LAPACK.geevx!(permute ? (scale ? 'B' : 'P') : (scale ? 'S' : 'N'), 'N', 'N', 'N', A)
-    return iszero(valsim) ? valsre : complex(valsre, valsim)
+    return iszero(valsim) ? valsre : complex.(valsre, valsim)
 end
 function eigvals!{T<:BlasComplex}(A::StridedMatrix{T}; permute::Bool=true, scale::Bool=true)
     ishermitian(A) && return eigvals(Hermitian(A))
@@ -297,7 +297,7 @@ function eigfact!{T<:BlasReal}(A::StridedMatrix{T}, B::StridedMatrix{T})
         end
         j += 1
     end
-    return GeneralizedEigen(complex(alphar, alphai)./beta, vecs)
+    return GeneralizedEigen(complex.(alphar, alphai)./beta, vecs)
 end
 
 function eigfact!{T<:BlasComplex}(A::StridedMatrix{T}, B::StridedMatrix{T})
@@ -364,7 +364,7 @@ Same as [`eigvals`](@ref), but saves space by overwriting the input `A` (and `B`
 function eigvals!{T<:BlasReal}(A::StridedMatrix{T}, B::StridedMatrix{T})
     issymmetric(A) && isposdef(B) && return eigvals!(Symmetric(A), Symmetric(B))
     alphar, alphai, beta, vl, vr = LAPACK.ggev!('N', 'N', A, B)
-    return (iszero(alphai) ? alphar : complex(alphar, alphai))./beta
+    return (iszero(alphai) ? alphar : complex.(alphar, alphai))./beta
 end
 function eigvals!{T<:BlasComplex}(A::StridedMatrix{T}, B::StridedMatrix{T})
     ishermitian(A) && isposdef(B) && return eigvals!(Hermitian(A), Hermitian(B))

base/linalg/lapack.jl

@@ -5504,7 +5504,7 @@ for (gees, gges, elty) in
                     work = Array{$elty}(lwork)
                 end
             end
-            A, vs, iszero(wi) ? wr : complex(wr, wi)
+            A, vs, iszero(wi) ? wr : complex.(wr, wi)
         end
 
         # *     .. Scalar Arguments ..
@@ -5553,7 +5553,7 @@ for (gees, gges, elty) in
                     work = Array{$elty}(lwork)
                 end
             end
-            A, B, complex(alphar, alphai), beta, vsl[1:(jobvsl == 'V' ? n : 0),:], vsr[1:(jobvsr == 'V' ? n : 0),:]
+            A, B, complex.(alphar, alphai), beta, vsl[1:(jobvsl == 'V' ? n : 0),:], vsr[1:(jobvsr == 'V' ? n : 0),:]
         end
     end
 end
@@ -5753,7 +5753,7 @@ for (trexc, trsen, tgsen, elty) in
                     iwork  = Array{BlasInt}(liwork)
                 end
             end
-            T, Q, iszero(wi) ? wr : complex(wr, wi)
+            T, Q, iszero(wi) ? wr : complex.(wr, wi)
         end
         trsen!(select::StridedVector{BlasInt}, T::StridedMatrix{$elty}, Q::StridedMatrix{$elty}) =
             trsen!('N', 'V', select, T, Q)
@@ -5822,7 +5822,7 @@ for (trexc, trsen, tgsen, elty) in
                     iwork = Array{BlasInt}(liwork)
                 end
             end
-            S, T, complex(alphar, alphai), beta, Q, Z
+            S, T, complex.(alphar, alphai), beta, Q, Z
         end
     end
 end

base/sharedarray.jl

@@ -537,8 +537,6 @@ function copy!(S::SharedArray, R::SharedArray)
     return S
 end
 
-complex(S1::SharedArray,S2::SharedArray) = convert(SharedArray, complex(S1.s, S2.s))
-
 function print_shmem_limits(slen)
     try
         if is_linux()

base/sparse/cholmod.jl

@@ -1572,7 +1572,7 @@ end
 Ac_ldiv_B(L::FactorComponent, B) = ctranspose(L)\B
 
 (\){T<:VTypes}(L::Factor{T}, B::Dense{T}) = solve(CHOLMOD_A, L, B)
-(\)(L::Factor{Float64}, B::VecOrMat{Complex{Float64}}) = complex(L\real(B), L\imag(B))
+(\)(L::Factor{Float64}, B::VecOrMat{Complex{Float64}}) = complex.(L\real(B), L\imag(B))
 # First explicit TypeVars are necessary to avoid ambiguity errors with definition in
 # linalg/factorizations.jl
 (\){T<:VTypes}(L::Factor{T}, b::StridedVector) = Vector(L\convert(Dense{T}, b))

base/sparse/sparsematrix.jl

@@ -354,8 +354,6 @@ float(S::SparseMatrixCSC) = SparseMatrixCSC(S.m, S.n, copy(S.colptr), copy(S.row
 
 complex(S::SparseMatrixCSC) = SparseMatrixCSC(S.m, S.n, copy(S.colptr), copy(S.rowval), complex(copy(S.nzval)))
 
-complex(A::SparseMatrixCSC, B::SparseMatrixCSC) = A + im*B
-
 # Construct a sparse vector
 
 # Note that unlike `vec` for arrays, this does not share data

base/sparse/umfpack.jl

@@ -370,8 +370,8 @@ for itype in UmfpackIndexTypes
                         Up,Ui,Ux,Uz,
                         P, Q, C_NULL, C_NULL,
                         &0, Rs, lu.numeric)
-            (transpose(SparseMatrixCSC(min(n_row, n_col), n_row, increment!(Lp), increment!(Lj), complex(Lx, Lz))),
-             SparseMatrixCSC(min(n_row, n_col), n_col, increment!(Up), increment!(Ui), complex(Ux, Uz)),
+            (transpose(SparseMatrixCSC(min(n_row, n_col), n_row, increment!(Lp), increment!(Lj), complex.(Lx, Lz))),
+             SparseMatrixCSC(min(n_row, n_col), n_col, increment!(Up), increment!(Ui), complex.(Ux, Uz)),
              increment!(P), increment!(Q), Rs)
         end
     end

test/arrayops.jl

@@ -1183,7 +1183,7 @@ end
 # Handle block matrices
 A = [randn(2,2) for i = 1:2, j = 1:2]
 @test issymmetric(A.'A)
-A = [complex(randn(2,2), randn(2,2)) for i = 1:2, j = 1:2]
+A = [complex.(randn(2,2), randn(2,2)) for i = 1:2, j = 1:2]
 @test ishermitian(A'A)
 
 # issue #7197

test/blas.jl

@@ -8,8 +8,8 @@ for elty in (Float32, Float64, Complex64, Complex128)
     U = randn(5,2)
     V = randn(5,2)
     if elty == Complex64 || elty == Complex128
-        U = complex(U, U)
-        V = complex(V, V)
+        U = complex.(U, U)
+        V = complex.(V, V)
     end
     U = convert(Array{elty, 2}, U)
     V = convert(Array{elty, 2}, V)
@@ -23,8 +23,8 @@ for elty in (Complex64, Complex128)
     U = randn(5,2)
     V = randn(5,2)
     if elty == Complex64 || elty == Complex128
-        U = complex(U, U)
-        V = complex(V, V)
+        U = complex.(U, U)
+        V = complex.(V, V)
     end
     U = convert(Array{elty, 2}, U)
     V = convert(Array{elty, 2}, V)
@@ -58,8 +58,8 @@ for elty in [Float32, Float64, Complex64, Complex128]
             @test BLAS.dot(x1,x2) ≈ sum(x1.*x2)
             @test_throws DimensionMismatch BLAS.dot(x1,rand(elty, n + 1))
         else
-            z1 = convert(Vector{elty}, complex(randn(n),randn(n)))
-            z2 = convert(Vector{elty}, complex(randn(n),randn(n)))
+            z1 = convert(Vector{elty}, complex.(randn(n),randn(n)))
+            z2 = convert(Vector{elty}, complex.(randn(n),randn(n)))
             @test BLAS.dotc(z1,z2) ≈ sum(conj(z1).*z2)
             @test BLAS.dotu(z1,z2) ≈ sum(z1.*z2)
             @test_throws DimensionMismatch BLAS.dotc(z1,rand(elty, n + 1))
@@ -71,7 +71,7 @@ for elty in [Float32, Float64, Complex64, Complex128]
             x = convert(Vector{elty}, randn(n))
             @test BLAS.iamax(x) == indmax(abs.(x))
         else
-            z = convert(Vector{elty}, complex(randn(n),randn(n)))
+            z = convert(Vector{elty}, complex.(randn(n),randn(n)))
             @test BLAS.iamax(z) == indmax(map(x -> abs(real(x)) + abs(imag(x)), z))
         end
 
@@ -87,8 +87,8 @@ for elty in [Float32, Float64, Complex64, Complex128]
             @test_throws ArgumentError BLAS.axpy!(α, copy(x1), 1:div(n,2), copy(x2), 0:(div(n, 2) - 1))
             @test BLAS.axpy!(α,copy(x1),1:n,copy(x2),1:n) ≈ x2 + α*x1
         else
-            z1 = convert(Vector{elty}, complex(randn(n), randn(n)))
-            z2 = convert(Vector{elty}, complex(randn(n), randn(n)))
+            z1 = convert(Vector{elty}, complex.(randn(n), randn(n)))
+            z2 = convert(Vector{elty}, complex.(randn(n), randn(n)))
             α  = rand(elty)
             @test BLAS.axpy!(α, copy(z1), copy(z2)) ≈ z2 + α * z1
             @test_throws DimensionMismatch BLAS.axpy!(α, copy(z1), rand(elty, n + 1))

test/complex.jl

@@ -813,8 +813,8 @@ end
 @test_throws DomainError complex(2,2)^(-2)
 @test complex(2.0,2.0)^(-2) === complex(0.0, -0.125)
 
-@test complex(1.0,[1.0,1.0]) == [complex(1.0,1.0), complex(1.0,1.0)]
-@test complex([1.0,1.0],1.0) == [complex(1.0,1.0), complex(1.0,1.0)]
+@test complex.(1.0, [1.0, 1.0]) == [complex(1.0, 1.0), complex(1.0, 1.0)]
+@test complex.([1.0, 1.0], 1.0) == [complex(1.0, 1.0), complex(1.0, 1.0)]
 # robust division of Float64
 # hard complex divisions from Fig 6 of arxiv.1210.4539
 z7 = Complex{Float64}(3.898125604559113300e289, 8.174961907852353577e295)

test/dsp.jl

@@ -37,7 +37,7 @@ si = [0.9967207836936347,-1.4940914728163142,1.2841226760316475,-0.4524417279474
 a = [1., 2., 1., 2.]
 b = [1., 2., 3.]
 @test conv(a, b) ≈ [1., 4., 8., 10., 7., 6.]
-@test conv(complex(a, ones(4)), complex(b)) ≈ complex([1., 4., 8., 10., 7., 6.], [1., 3., 6., 6., 5., 3.])
+@test conv(complex.(a, ones(4)), complex(b)) ≈ complex.([1., 4., 8., 10., 7., 6.], [1., 3., 6., 6., 5., 3.])
 
 # Discrete cosine transform (DCT) tests
 

test/linalg/arnoldi.jl

@@ -9,8 +9,8 @@ using Base.Test
         n = 10
         areal  = sprandn(n,n,0.4)
         breal  = sprandn(n,n,0.4)
-        acmplx = complex(sprandn(n,n,0.4), sprandn(n,n,0.4))
-        bcmplx = complex(sprandn(n,n,0.4), sprandn(n,n,0.4))
+        acmplx = complex.(sprandn(n,n,0.4), sprandn(n,n,0.4))
+        bcmplx = complex.(sprandn(n,n,0.4), sprandn(n,n,0.4))
 
         testtol = 1e-6
 

test/linalg/bunchkaufman.jl

@@ -20,8 +20,8 @@ breal = randn(n,2)/2
 bimg  = randn(n,2)/2
 
 @testset for eltya in (Float32, Float64, Complex64, Complex128, Int)
-    a = eltya == Int ? rand(1:7, n, n) : convert(Matrix{eltya}, eltya <: Complex ? complex(areal, aimg) : areal)
-    a2 = eltya == Int ? rand(1:7, n, n) : convert(Matrix{eltya}, eltya <: Complex ? complex(a2real, a2img) : a2real)
+    a = eltya == Int ? rand(1:7, n, n) : convert(Matrix{eltya}, eltya <: Complex ? complex.(areal, aimg) : areal)
+    a2 = eltya == Int ? rand(1:7, n, n) : convert(Matrix{eltya}, eltya <: Complex ? complex.(a2real, a2img) : a2real)
     @testset for atype in ("Array", "SubArray")
         asym = a'+a                  # symmetric indefinite
         apd  = a'*a                 # symmetric positive-definite
@@ -37,7 +37,7 @@ bimg  = randn(n,2)/2
         ε = εa = eps(abs(float(one(eltya))))
 
         @testset for eltyb in (Float32, Float64, Complex64, Complex128, Int)
-            b = eltyb == Int ? rand(1:5, n, 2) : convert(Matrix{eltyb}, eltyb <: Complex ? complex(breal, bimg) : breal)
+            b = eltyb == Int ? rand(1:5, n, 2) : convert(Matrix{eltyb}, eltyb <: Complex ? complex.(breal, bimg) : breal)
             @testset for btype in ("Array", "SubArray")
                 if btype == "Array"
                     b = b

test/linalg/cholesky.jl

@@ -22,8 +22,8 @@ breal = randn(n,2)/2
 bimg  = randn(n,2)/2
 
 for eltya in (Float32, Float64, Complex64, Complex128, BigFloat, Int)
-    a = eltya == Int ? rand(1:7, n, n) : convert(Matrix{eltya}, eltya <: Complex ? complex(areal, aimg) : areal)
-    a2 = eltya == Int ? rand(1:7, n, n) : convert(Matrix{eltya}, eltya <: Complex ? complex(a2real, a2img) : a2real)
+    a = eltya == Int ? rand(1:7, n, n) : convert(Matrix{eltya}, eltya <: Complex ? complex.(areal, aimg) : areal)
+    a2 = eltya == Int ? rand(1:7, n, n) : convert(Matrix{eltya}, eltya <: Complex ? complex.(a2real, a2img) : a2real)
     apd  = a'*a                  # symmetric positive-definite
 
     apds  = Symmetric(apd)
@@ -144,7 +144,7 @@ for eltya in (Float32, Float64, Complex64, Complex128, BigFloat, Int)
     end
 
     for eltyb in (Float32, Float64, Complex64, Complex128, Int)
-        b = eltyb == Int ? rand(1:5, n, 2) : convert(Matrix{eltyb}, eltyb <: Complex ? complex(breal, bimg) : breal)
+        b = eltyb == Int ? rand(1:5, n, 2) : convert(Matrix{eltyb}, eltyb <: Complex ? complex.(breal, bimg) : breal)
         εb = eps(abs(float(one(eltyb))))
         ε = max(εa,εb)
 
@@ -200,7 +200,7 @@ end
 # Test generic cholfact!
 for elty in (Float32, Float64, Complex{Float32}, Complex{Float64})
     if elty <: Complex
-        A = complex(randn(5,5), randn(5,5))
+        A = complex.(randn(5,5), randn(5,5))
     else
         A = randn(5,5)
     end
@@ -210,7 +210,7 @@ for elty in (Float32, Float64, Complex{Float32}, Complex{Float64})
 end
 
 # Test up- and downdates
-let A = complex(randn(10,5), randn(10, 5)), v = complex(randn(5), randn(5))
+let A = complex.(randn(10,5), randn(10, 5)), v = complex.(randn(5), randn(5))
     for uplo in (:U, :L)
         AcA = A'A
         BcB = AcA + v*v'
@@ -257,7 +257,7 @@ end
 
 # Fail if non-Hermitian
 @test_throws ArgumentError cholfact(randn(5,5))
-@test_throws ArgumentError cholfact(complex(randn(5,5), randn(5,5)))
+@test_throws ArgumentError cholfact(complex.(randn(5,5), randn(5,5)))
 @test_throws ArgumentError Base.LinAlg.chol!(randn(5,5))
 @test_throws ArgumentError Base.LinAlg.cholfact!(randn(5,5),:U,Val{false})
 @test_throws ArgumentError Base.LinAlg.cholfact!(randn(5,5),:U,Val{true})