Transition vectorized unary functions over SparseMatrixCSCs to comp…

…act broadcast syntax, accordingly revise and expand the associated tests, and add deprecations for the vectorized syntax.

base/deprecated.jl

@@ -793,6 +793,19 @@ function transpose(x)
     return x
 end
 
+# Deprecate vectorized unary functions over sparse matrices in favor of compact broadcast syntax (#17265).
+for f in (:sin, :sinh, :sind, :asin, :asinh, :asind,
+        :tan, :tanh, :tand, :atan, :atanh, :atand,
+        :sinpi, :cosc, :ceil, :floor, :trunc, :round, :real, :imag,
+        :log1p, :expm1, :abs, :abs2, :conj,
+        :log, :log2, :log10, :exp, :exp2, :exp10, :sinc, :cospi,
+        :cos, :cosh, :cosd, :acos, :acosd,
+        :cot, :coth, :cotd, :acot, :acotd,
+        :sec, :sech, :secd, :asech,
+        :csc, :csch, :cscd, :acsch)
+    @eval @deprecate $f(A::SparseMatrixCSC) $f.(A)
+end
+
 # During the 0.5 development cycle, do not add any deprecations below this line
 # To be deprecated in 0.6
 

base/sparse/sparsematrix.jl

@@ -1285,12 +1285,12 @@ end
 """
 Helper macro for the unary broadcast definitions below. Takes parent method `fp` and a set
 of desired child methods `fcs`, and builds an expression defining each of the child methods
-such that `fc(A::SparseMatrixCSC) = fp(fc, A)`.
+such that `broadcast(::typeof(fc), A::SparseMatrixCSC) = fp(fc, A)`.
 """
 macro _enumerate_childmethods(fp, fcs...)
     fcexps = Expr(:block)
     for fc in fcs
-        push!(fcexps.args, :( $(esc(fc))(A::SparseMatrixCSC) = $(esc(fp))($(esc(fc)), A) ) )
+        push!(fcexps.args, :( broadcast(::typeof($(esc(fc))), A::SparseMatrixCSC) = $(esc(fp))($(esc(fc)), A) ) )
     end
     return fcexps
 end
@@ -1329,10 +1329,10 @@ end
     sin, sinh, sind, asin, asinh, asind,
     tan, tanh, tand, atan, atanh, atand,
     sinpi, cosc, ceil, floor, trunc, round)
-real(A::SparseMatrixCSC) = copy(A)
-imag{Tv,Ti}(A::SparseMatrixCSC{Tv,Ti}) = spzeros(Tv, Ti, A.m, A.n)
-real{TTv}(A::SparseMatrixCSC{Complex{TTv}}) = _broadcast_unary_nz2z_z2z_T(real, A, TTv)
-imag{TTv}(A::SparseMatrixCSC{Complex{TTv}}) = _broadcast_unary_nz2z_z2z_T(imag, A, TTv)
+broadcast(::typeof(real), A::SparseMatrixCSC) = copy(A)
+broadcast{Tv,Ti}(::typeof(imag), A::SparseMatrixCSC{Tv,Ti}) = spzeros(Tv, Ti, A.m, A.n)
+broadcast{TTv}(::typeof(real), A::SparseMatrixCSC{Complex{TTv}}) = _broadcast_unary_nz2z_z2z_T(real, A, TTv)
+broadcast{TTv}(::typeof(imag), A::SparseMatrixCSC{Complex{TTv}}) = _broadcast_unary_nz2z_z2z_T(imag, A, TTv)
 ceil{To}(::Type{To}, A::SparseMatrixCSC) = _broadcast_unary_nz2z_z2z_T(ceil, A, To)
 floor{To}(::Type{To}, A::SparseMatrixCSC) = _broadcast_unary_nz2z_z2z_T(floor, A, To)
 trunc{To}(::Type{To}, A::SparseMatrixCSC) = _broadcast_unary_nz2z_z2z_T(trunc, A, To)
@@ -1359,10 +1359,10 @@ function _broadcast_unary_nz2nz_z2z{Tv}(f::Function, A::SparseMatrixCSC{Tv})
 end
 @_enumerate_childmethods(_broadcast_unary_nz2nz_z2z,
     log1p, expm1, abs, abs2, conj)
-abs2{TTv}(A::SparseMatrixCSC{Complex{TTv}}) = _broadcast_unary_nz2nz_z2z_T(abs2, A, TTv)
-abs{TTv}(A::SparseMatrixCSC{Complex{TTv}}) = _broadcast_unary_nz2nz_z2z_T(abs, A, TTv)
-abs{TTv<:Integer}(A::SparseMatrixCSC{Complex{TTv}}) = _broadcast_unary_nz2nz_z2z_T(abs, A, Float64)
-abs{TTv<:BigInt}(A::SparseMatrixCSC{Complex{TTv}}) = _broadcast_unary_nz2nz_z2z_T(abs, A, BigFloat)
+broadcast{TTv}(::typeof(abs2), A::SparseMatrixCSC{Complex{TTv}}) = _broadcast_unary_nz2nz_z2z_T(abs2, A, TTv)
+broadcast{TTv}(::typeof(abs), A::SparseMatrixCSC{Complex{TTv}}) = _broadcast_unary_nz2nz_z2z_T(abs, A, TTv)
+broadcast{TTv<:Integer}(::typeof(abs), A::SparseMatrixCSC{Complex{TTv}}) = _broadcast_unary_nz2nz_z2z_T(abs, A, Float64)
+broadcast{TTv<:BigInt}(::typeof(abs), A::SparseMatrixCSC{Complex{TTv}}) = _broadcast_unary_nz2nz_z2z_T(abs, A, BigFloat)
 function conj!(A::SparseMatrixCSC)
     @inbounds @simd for k in 1:nnz(A)
         A.nzval[k] = conj(A.nzval[k])
@@ -1699,7 +1699,7 @@ end # macro
 (.^)(A::SparseMatrixCSC, B::Number) =
     B==0 ? sparse(ones(typeof(one(eltype(A)).^B), A.m, A.n)) :
            SparseMatrixCSC(A.m, A.n, copy(A.colptr), copy(A.rowval), A.nzval .^ B)
-(.^)(::Irrational{:e}, B::SparseMatrixCSC) = exp(B)
+(.^)(::Irrational{:e}, B::SparseMatrixCSC) = exp.(B)
 (.^)(A::Number, B::SparseMatrixCSC) = (.^)(A, full(B))
 (.^)(A::SparseMatrixCSC, B::Array) = (.^)(full(A), B)
 (.^)(A::Array, B::SparseMatrixCSC) = (.^)(A, full(B))

test/sparsedir/sparse.jl

@@ -286,7 +286,7 @@ end
 
 # conj
 cA = sprandn(5,5,0.2) + im*sprandn(5,5,0.2)
-@test full(conj(cA)) == conj(full(cA))
+@test full(conj.(cA)) == conj(full(cA))
 
 # Test SparseMatrixCSC [c]transpose[!] and permute[!] methods
 let smalldim = 5, largedim = 10, nzprob = 0.4
@@ -461,22 +461,47 @@ end
 @test maximum(sparse(-ones(3,3))) == -1
 @test minimum(sparse(ones(3,3))) == 1
 
-# Unary functions
-a = sprand(5,15, 0.5)
-afull = full(a)
-for op in (:sin, :cos, :tan, :ceil, :floor, :abs, :abs2)
-    @eval begin
-        @test ($op)(afull) == full($(op)(a))
-    end
-end
-
-for op in (:ceil, :floor)
-    @eval begin
-        @test ($op)(Int,afull) == full($(op)(Int,a))
+# Test unary functions with specialized broadcast over SparseMatrixCSCs
+let
+    A = sprand(5, 15, 0.5)
+    C = A + im*A
+    Afull = full(A)
+    Cfull = full(C)
+    # Test representatives of [unary functions that map zeros to zeros and may map nonzeros to zeros]
+    @test sin.(Afull) == full(sin.(A))
+    @test tan.(Afull) == full(tan.(A)) # should be redundant with sin test
+    @test ceil.(Afull) == full(ceil.(A))
+    @test floor.(Afull) == full(floor.(A)) # should be redundant with ceil test
+    @test real.(Afull) == full(real.(A))
+    @test imag.(Afull) == full(imag.(A))
+    @test real.(Cfull) == full(real.(C))
+    @test imag.(Cfull) == full(imag.(C))
+    # Test representatives of [unary functions that map zeros to zeros and nonzeros to nonzeros]
+    @test expm1.(Afull) == full(expm1.(A))
+    @test abs.(Afull) == full(abs.(A))
+    @test abs2.(Afull) == full(abs2.(A))
+    @test abs.(Cfull) == full(abs.(C))
+    @test abs2.(Cfull) == full(abs2.(C))
+    # Test representatives of [unary functions that map both zeros and nonzeros to nonzeros]
+    @test cos.(Afull) == full(cos.(A))
+    # Test representatives of remaining vectorized-nonbroadcast unary functions
+    @test ceil(Int, Afull) == full(ceil(Int, A))
+    @test floor(Int, Afull) == full(floor(Int, A))
+    # Tests of real, imag, abs, and abs2 for SparseMatrixCSC{Int,X}s previously elsewhere
+    for T in (Int, Float16, Float32, Float64, BigInt, BigFloat)
+        R = rand(T[1:100;], 2, 2)
+        I = rand(T[1:100;], 2, 2)
+        D = R + I*im
+        S = sparse(D)
+        @test R == real.(S)
+        @test I == imag.(S)
+        @test real.(sparse(R)) == R
+        @test nnz(imag.(sparse(R))) == 0
+        @test abs.(S) == abs(D)
+        @test abs2.(S) == abs2(D)
     end
 end
 
-
 # getindex tests
 ni = 23
 nj = 32
@@ -755,7 +780,7 @@ end
 @test_throws ArgumentError sparsevec(Dict(-1=>1,1=>2))
 
 # issue #8976
-@test conj(sparse([1im])) == sparse(conj([1im]))
+@test conj.(sparse([1im])) == sparse(conj([1im]))
 @test conj!(sparse([1im])) == sparse(conj!([1im]))
 
 # issue #9525
@@ -921,18 +946,6 @@ end
 x = speye(100)
 @test_throws BoundsError x[-10:10]
 
-for T in (Int, Float16, Float32, Float64, BigInt, BigFloat)
-    let R=rand(T[1:100;],2,2), I=rand(T[1:100;],2,2)
-        D = R + I*im
-        S = sparse(D)
-        @test R == real(S)
-        @test I == imag(S)
-        @test real(sparse(R)) == R
-        @test nnz(imag(sparse(R))) == 0
-        @test abs(S) == abs(D)
-        @test abs2(S) == abs2(D)
-    end
-end
 
 # issue #10407
 @test maximum(spzeros(5, 5)) == 0.0