Sparse matrix indexing with ranges is slow and memory hungry

This fixes the case when a whole column is indexed.  However, indexing
parts of columns still has that problem and needs a bigger rewrite.

base/sparse/sparsematrix.jl

@@ -703,7 +703,7 @@ end
 # TODO: See if growing arrays is faster than pre-computing structure
 # and then populating nonzeros
 # TODO: Use binary search in cases where nI >> nfilled(A[:,j]) or nI << nfilled(A[:,j])
-function getindex_I_sorted{Tv,Ti}(A::SparseMatrixCSC{Tv,Ti}, I::Vector, J::AbstractVector)
+function getindex_I_sorted{Tv,Ti}(A::SparseMatrixCSC{Tv,Ti}, I::AbstractVector, J::AbstractVector)
 
  (m, n) = size(A)
  nI = length(I)
@@ -929,17 +929,26 @@ end
 # S = A[I, J]
 function getindex{Tv,Ti}(A::SparseMatrixCSC{Tv,Ti}, I::AbstractVector, J::AbstractVector)
  m = size(A, 1)
-
- if isa(I, Range) || isa(I, Range1); I = [I]; end
-
- if I == 1:m
- return getindex_cols(A, J)
- elseif issorted(I)
- return getindex_I_sorted(A, I, J)
- else
- return getindex_general(A, I, J)
+ if isa(I, Ranges) 
+ if I == 1:m # whole columns
+ return getindex_cols(A, J)
+ else # ranges are always sorted, but maybe in reverse
+ if step(I)>0
+ return getindex_I_sorted(A, I, J)
+ else 
+ I = [I]
+ return getindex_general(A, I, J)
+ # todo:
+ # return reverse(getindex_I_sorted(A, reverse(I), J))
+ end
+ end
+ else 
+ if issorted(I)
+ return getindex_I_sorted(A, I, J)
+ else
+ return getindex_general(A, I, J)
+ end
  end
-
 end
 
 # logical getindex