type-stable

Author: mcabbott

base/abstractarray.jl

@@ -2788,19 +2788,20 @@ function mapslices(f, A::AbstractArray; dims)
     Aslice = A[idx1...]
     r1 = f(Aslice)
 
-    if r1 isa AbstractArray && ndims(r1) > 0
+    res1 = if r1 isa AbstractArray && ndims(r1) > 0
         n = sum(dim_mask)
         if ndims(r1) > n && any(ntuple(d -> size(r1,d+n)>1, ndims(r1)-n))
             s = size(r1)[1:n]
             throw(DimensionMismatch("cannot assign slice f(x) of size $(size(r1)) into output of size $s"))
         end
-        res1 = r1
+        r1
     else
         # If the result of f on a single slice is a scalar then we add singleton
         # dimensions. When adding the dimensions, we have to respect the
         # index type of the input array (e.g. in the case of OffsetArrays)
-        res1 = similar(Aslice, typeof(r1), reduced_indices(Aslice, 1:ndims(Aslice)))
-        res1[begin] = r1
+        _res1 = similar(Aslice, typeof(r1), reduced_indices(Aslice, 1:ndims(Aslice)))
+        _res1[begin] = r1
+        _res1
     end
 
     # Determine result size and allocate. We always pad ndims(res1) out to length(dims):

test/arrayops.jl

@@ -1201,7 +1201,7 @@ end
     @test mapslices(nnz, sparse(1.0I, 3, 3), dims=1) == [1 1 1]
 
     r = rand(Int8, 4,5,2)
-    @test mapslices(transpose, r, dims=(1,3)) == permutedims(r, (3,2,1))
+    @test @inferred(mapslices(transpose, r, dims=(1,3))) == permutedims(r, (3,2,1))
     @test vec(mapslices(repr, r, dims=(2,1))) == map(repr, eachslice(r, dims=3))
     @test mapslices(cumsum, sparse(r[:,:,1]), dims=1) == cumsum(r[:,:,1], dims=1)
     @test mapslices(prod, sparse(r[:,:,1]), dims=1) == prod(r[:,:,1], dims=1)
@@ -1210,8 +1210,8 @@ end
     @test_throws ArgumentError mapslices(identity, rand(2,3), dims=0) # previously BoundsError
     @test_throws ArgumentError mapslices(identity, rand(2,3), dims=(1,3)) # previously BoundsError
     @test_throws DimensionMismatch mapslices(x -> x * x', rand(2,3), dims=1) # explicitly caught
-    @test mapslices(hcat, [1 2; 3 4], dims=1) == [1 2; 3 4] # previously an error, now allowed
-    @test mapslices(identity, [1 2; 3 4], dims=(2,2)) == [1 2; 3 4] # previously an error
+    @test @inferred(mapslices(hcat, [1 2; 3 4], dims=1)) == [1 2; 3 4] # previously an error, now allowed
+    @test @inferred(mapslices(identity, [1 2; 3 4], dims=(2,2))) == [1 2; 3 4] # previously an error
 end
 
 @testset "single multidimensional index" begin