Deprecate a few remaining vectorized methods over SparseVectors. (And…

… associated cleanup.)

base/sparse/higherorderfns.jl

@@ -141,7 +141,6 @@ end
     return SparseMatrixCSC(shape..., pointers, storedinds, storedvals)
 end
 # Ambiguity killers, TODO: nix conflicting specializations
-broadcast(::typeof(abs), x::SparseVector) = _noshapecheck_map(abs, x) # base/sparse/sparevectors.jl: 921
 ambiguityfunnel{Tf}(f::Tf, x, y) = _aresameshape(x, y) ? _noshapecheck_map(f, x, y) : _diffshape_broadcast(f, x, y)
 broadcast(::typeof(+), x::SparseVector, y::SparseVector) = ambiguityfunnel(+, x, y) # base/sparse/sparsevectors.jl:1266
 broadcast(::typeof(-), x::SparseVector, y::SparseVector) = ambiguityfunnel(-, x, y) # base/sparse/sparsevectors.jl:1266

base/sparse/sparsevector.jl

@@ -918,14 +918,8 @@ hvcat{T}(rows::Tuple{Vararg{Int}}, xs::_TypedDenseConcatGroup{T}...) = Base.type
 ### Unary Map
 
 # zero-preserving functions (z->z, nz->nz)
-broadcast(::typeof(abs), x::AbstractSparseVector) = SparseVector(length(x), copy(nonzeroinds(x)), abs.(nonzeros(x)))
-for op in [:conj]
-    @eval begin
-        $(op)(x::AbstractSparseVector) =
-            SparseVector(length(x), copy(nonzeroinds(x)), $(op).(nonzeros(x)))
-    end
-end
--(x::AbstractSparseVector) = SparseVector(length(x), copy(nonzeroinds(x)), -(nonzeros(x)))
+conj(x::SparseVector) = SparseVector(length(x), copy(nonzeroinds(x)), conj(nonzeros(x)))
+-(x::SparseVector) = SparseVector(length(x), copy(nonzeroinds(x)), -(nonzeros(x)))
 
 # functions f, such that
 #   f(x) can be zero or non-zero when x != 0
@@ -1271,18 +1265,17 @@ end
 
 # definition of other binary functions
 
-for (op, TF, mode) in [(:max, :Real, 2),
-                       (:min, :Real, 2),
-                       (:complex, :Real, 1)]
-    @eval begin
-        $(op){Tx<:$(TF),Ty<:$(TF)}(x::AbstractSparseVector{Tx}, y::AbstractSparseVector{Ty}) =
-            _binarymap($(op), x, y, $mode)
-        $(op){Tx<:$(TF),Ty<:$(TF)}(x::StridedVector{Tx}, y::AbstractSparseVector{Ty}) =
-            _binarymap($(op), x, y, $mode)
-        $(op){Tx<:$(TF),Ty<:$(TF)}(x::AbstractSparseVector{Tx}, y::StridedVector{Ty}) =
-            _binarymap($(op), x, y, $mode)
-    end
-end
+broadcast{Tx<:Real,Ty<:Real}(::typeof(min), x::SparseVector{Tx}, y::SparseVector{Ty}) = _binarymap(min, x, y, 2)
+broadcast{Tx<:Real,Ty<:Real}(::typeof(min), x::StridedVector{Tx}, y::SparseVector{Ty}) = _binarymap(min, x, y, 2)
+broadcast{Tx<:Real,Ty<:Real}(::typeof(min), x::SparseVector{Tx}, y::SparseVector{Ty}) = _binarymap(min, x, y, 2)
+
+broadcast{Tx<:Real,Ty<:Real}(::typeof(max), x::SparseVector{Tx}, y::SparseVector{Ty}) = _binarymap(max, x, y, 2)
+broadcast{Tx<:Real,Ty<:Real}(::typeof(max), x::StridedVector{Tx}, y::SparseVector{Ty}) = _binarymap(max, x, y, 2)
+broadcast{Tx<:Real,Ty<:Real}(::typeof(max), x::SparseVector{Tx}, y::SparseVector{Ty}) = _binarymap(max, x, y, 2)
+
+complex{Tx<:Real,Ty<:Real}(x::StridedVector{Tx}, y::AbstractSparseVector{Ty}) = _binarymap(complex, x, y, 1)
+complex{Tx<:Real,Ty<:Real}(x::AbstractSparseVector{Tx}, y::StridedVector{Ty}) = _binarymap(complex, x, y, 1)
+complex{Tx<:Real,Ty<:Real}(x::AbstractSparseVector{Tx}, y::AbstractSparseVector{Ty}) = _binarymap(complex, x, y, 1)
 
 ### Reduction
 

test/sparse/sparsevector.jl

@@ -617,11 +617,11 @@ let x = spv_x1, x2 = spv_x2
     @test x .* Array(x2) == Array(xm)
 
     # max & min
-    @test exact_equal(max(x, x), x)
-    @test exact_equal(min(x, x), x)
-    @test exact_equal(max(x, x2),
+    @test exact_equal(max.(x, x), x)
+    @test exact_equal(min.(x, x), x)
+    @test exact_equal(max.(x, x2),
         SparseVector(8, Int[1, 2, 6], Float64[3.25, 4.0, 3.5]))
-    @test exact_equal(min(x, x2),
+    @test exact_equal(min.(x, x2),
         SparseVector(8, Int[2, 5, 6, 7], Float64[1.25, -0.75, -5.5, -6.0]))
 end