Ensure indexing is consistent between...

one-column sparse matrices and sparse vectors, with special attention to stored zeros.

base/sparse/sparsevector.jl

@@ -411,7 +411,8 @@ function _logical_index{Tv}(A::SparseMatrixCSC{Tv}, I::AbstractArray{Bool})
     SparseVector(n, rowvalB, nzvalB)
 end
 
-# TODO: further optimizations are available for I::Range
+# TODO: huge optimizations are available for I::Range and ::Colon
+getindex(A::SparseMatrixCSC, ::Colon) = A[1:end]
 function getindex{Tv}(A::SparseMatrixCSC{Tv}, I::AbstractVector)
     szA = size(A)
     nA = szA[1]*szA[2]
@@ -499,8 +500,13 @@ getindex{Tv,Ti}(x::AbstractSparseVector{Tv,Ti}, I::AbstractArray{Bool}) = x[find
     S[I, 1]
 end
 
-# TODO: do this without reshaping
-getindex{Tv,Ti}(x::AbstractSparseVector{Tv,Ti}, I::AbstractArray) = reshape(x[vec(I)], size(I))
+function getindex{Tv,Ti}(x::AbstractSparseVector{Tv,Ti}, I::AbstractArray)
+    # punt to SparseMatrixCSC
+    S = SparseMatrixCSC(x.n, 1, [1,length(x.nzind)+1], x.nzind, x.nzval)
+    S[I]
+end
+
+getindex(x::AbstractSparseVector, ::Colon) = copy(x)
 
 ### show and friends
 

test/sparsedir/sparsevector.jl

@@ -668,3 +668,18 @@ sv[1] = 0
 
 # Ensure that sparsevec with all-zero values returns an array of zeros
 @test sparsevec([1,2,3],[0,0,0]) == [0,0,0]
+
+# Compare stored zero semantics between SparseVector and SparseMatrixCSC
+let S = SparseMatrixCSC(10,1,[1,6],[1,3,5,6,7],[0,1,2,0,3]), x = SparseVector(10,[1,3,5,6,7],[0,1,2,0,3])
+    @test nnz(S) == nnz(x) == 5
+    for I = (:, 1:10, collect(1:10))
+        @test S[I,1] == S[I] == x[I] == x
+        @test nnz(S[I,1]) == nnz(S[I]) == nnz(x[I]) == nnz(x)
+    end
+    for I = (2:9, 1:2, 9:10, [3,6,1], [10,9,8], [])
+        @test S[I,1] == S[I] == x[I]
+        @test nnz(S[I,1]) == nnz(S[I]) == nnz(x[I])
+    end
+    @test S[[1 3 5; 2 4 6]] == x[[1 3 5; 2 4 6]]
+    @test nnz(S[[1 3 5; 2 4 6]]) == nnz(x[[1 3 5; 2 4 6]])
+end