fix sparse getindex regression.

also replaced binarysearch with methods from sort.jl
ref JuliaLang#7131, JuliaLang#7047

base/sparse/sparsematrix.jl

@@ -712,33 +712,21 @@ prod{T}(A::SparseMatrixCSC{T}, region) = reducedim(*,A,region,one(T))
 #sum(A::SparseMatrixCSC{Bool}) = countnz(A)
 
 ## getindex
-function binarysearch(haystack::AbstractVector, needle, lo::Int, hi::Int)
- # Finds the first occurrence of needle in haystack[lo:hi]
- lo = lo-1
- hi2 = hi
- hi = hi+1
- @inbounds while lo < hi-1
- m = (lo+hi)>>>1
- if haystack[m] < needle
- lo = m
- else
- hi = m
- end
- end
- (hi==hi2+1 || haystack[hi]!=needle) ? -1 : hi
-end
 function rangesearch(haystack::Range, needle)
  (i,rem) = divrem(needle - first(haystack), step(haystack))
- (rem==0 && 1<=i+1<=length(haystack)) ? i+1 : -1
+ (rem==0 && 1<=i+1<=length(haystack)) ? i+1 : 0
 end
 
 getindex(A::SparseMatrixCSC, i::Integer) = getindex(A, ind2sub(size(A),i))
 getindex(A::SparseMatrixCSC, I::(Integer,Integer)) = getindex(A, I[1], I[2])
 
 function getindex{T}(A::SparseMatrixCSC{T}, i0::Integer, i1::Integer)
  if !(1 <= i0 <= A.m && 1 <= i1 <= A.n); throw(BoundsError()); end
- ind = binarysearch(A.rowval, i0, A.colptr[i1], A.colptr[i1+1]-1)
- ind > -1 ? A.nzval[ind] : zero(T)
+ r1 = int(A.colptr[i1])
+ r2 = int(A.colptr[i1+1]-1)
+ (r1 > r2) && return zero(T)
+ r1 = searchsortedfirst(A.rowval, i0, r1, r2, Forward)
+ ((r1 > r2) || (A.rowval[r1] != i0)) ? zero(T) : A.nzval[r1]
 end
 
 getindex{T<:Integer}(A::SparseMatrixCSC, I::AbstractVector{T}, j::Integer) = getindex(A,I,[j])
@@ -810,7 +798,7 @@ function getindex{Tv,Ti<:Integer}(A::SparseMatrixCSC{Tv,Ti}, I::Range, J::Abstra
  for k = colptrA[col]:colptrA[col+1]-1
  rowA = rowvalA[k]
  i = rangesearch(I, rowA)
- if i > -1
+ if i > 0
  rowvalS[ptrS] = i
  nzvalS[ptrS] = nzvalA[k]
  ptrS += 1
@@ -1073,15 +1061,17 @@ function setindex!{T,Ti}(A::SparseMatrixCSC{T,Ti}, v, i0::Integer, i1::Integer)
  i1 = convert(Ti, i1)
  if !(1 <= i0 <= A.m && 1 <= i1 <= A.n); throw(BoundsError()); end
  v = convert(T, v)
- r1 = A.colptr[i1]
- r2 = A.colptr[i1+1]-1
+ r1 = int(A.colptr[i1])
+ r2 = int(A.colptr[i1+1]-1)
  if v == 0 #either do nothing or delete entry if it exists
- loc = binarysearch(A.rowval, i0, r1, r2)
- if loc != -1
- deleteat!(A.rowval, loc)
- deleteat!(A.nzval, loc)
- for j = (i1+1):(A.n+1)
- A.colptr[j] -= 1
+ if r1 <= r2
+ r1 = searchsortedfirst(A.rowval, i0, r1, r2, Forward)
+ if (r1 <= r2) && (A.rowval[r1] == i0)
+ deleteat!(A.rowval, r1)
+ deleteat!(A.nzval, r1)
+ for j = (i1+1):(A.n+1)
+ A.colptr[j] -= 1
+ end
  end
  end
  return A
@@ -1851,8 +1841,11 @@ done(d::SpDiagIterator, j) = j > d.n
 
 function next{Tv}(d::SpDiagIterator{Tv}, j)
  A = d.A
- idx = binarysearch(A.rowval, j, A.colptr[j], A.colptr[j+1]-1)
- ((idx == -1) ? zero(Tv) : A.nzval[idx], j+1)
+ r1 = int(A.colptr[j])
+ r2 = int(A.colptr[j+1]-1)
+ (r1 > r2) && (return (zero(Tv), j+1))
+ r1 = searchsortedfirst(A.rowval, j, r1, r2, Forward)
+ (((r1 > r2) || (A.rowval[r1] != j)) ? zero(Tv) : A.nzval[r1], j+1)
 end
 
 function trace{Tv}(A::SparseMatrixCSC{Tv})

test/sparse.jl

@@ -289,6 +289,14 @@ for (aa116, ss116) in [(a116, s116), (ad116, sd116)]
  @test full(ss116[li,lj]) == aa116[li,lj]
 end
 
+let S = SparseMatrixCSC(3, 3, Uint8[1,1,1,1], Uint8[], Int64[])
+ S[1,1] = 1
+ S[5] = 2
+ S[end] = 3
+ @test S[end] == (S[1] + S[2,2])
+ @test 6 == sum(diag(S))
+end
+
 
 # setindex tests
 let a = spzeros(Int, 10, 10)