Use axes instead of length (#276)

src/Test/array.jl

@@ -307,21 +307,21 @@ function sum_test(matrix)
  @test_rewrite sum(matrix)
  if matrix isa AbstractMatrix
  @test_rewrite sum([
- 2matrix[i, j] for i in 1:size(matrix, 1), j in 1:size(matrix, 2)
+ 2matrix[i, j] for i in axes(matrix, 1), j in axes(matrix, 2)
  ])
  @test_rewrite sum(
- 2matrix[i, j] for i in 1:size(matrix, 1), j in 1:size(matrix, 2)
+ 2matrix[i, j] for i in axes(matrix, 1), j in axes(matrix, 2)
  )
  end
 end
 
 function sum_multiplication_test(matrix)
  if matrix isa AbstractMatrix
  @test_rewrite sum([
- 2matrix[i, j]^2 for i in 1:size(matrix, 1), j in 1:size(matrix, 2)
+ 2matrix[i, j]^2 for i in axes(matrix, 1), j in axes(matrix, 2)
  ])
  @test_rewrite sum(
- 2matrix[i, j]^2 for i in 1:size(matrix, 1), j in 1:size(matrix, 2)
+ 2matrix[i, j]^2 for i in axes(matrix, 1), j in axes(matrix, 2)
  )
  end
 end
@@ -344,7 +344,7 @@ function transpose_test(x)
  # If the element type does not support multiplication, e.g.
  # JuMP or MOI quadratic functions, then we should skip these tests.
  if x isa AbstractMatrix && _is_supported(*, eltype(x), eltype(x))
- y = [x[i, j] for j in 1:size(x, 2), i in 1:size(x, 1)]
+ y = [x[i, j] for j in axes(x, 2), i in axes(x, 1)]
  @test MA.isequal_canonical(x', y)
  @test MA.isequal_canonical(copy(transpose(x)), y)
  if size(x, 1) == size(x, 2)

src/dispatch.jl

@@ -548,7 +548,7 @@ end
 # `eltype` of `B` might be different form the `eltype` of `A`.
 function Matrix(A::LinearAlgebra.Symmetric{<:AbstractMutable})
  B = LinearAlgebra.copytri!(convert(Matrix, copy(A.data)), A.uplo)
- for i in 1:size(A, 1)
+ for i in axes(A, 1)
  # `B[i, i]` is used instead of `A[i, i]` on Julia v1.1 hence the need
  # to overwrite it for `AbstractMutable`.
  B[i, i] = LinearAlgebra.symmetric(
@@ -561,7 +561,7 @@ end
 
 function Matrix(A::LinearAlgebra.Hermitian{<:AbstractMutable})
  B = LinearAlgebra.copytri!(convert(Matrix, copy(A.data)), A.uplo, true)
- for i in 1:size(A, 1)
+ for i in axes(A, 1)
  # `B[i, i]` is used instead of `A[i, i]` on Julia v1.1 hence the need
  # to overwrite it for `AbstractMutable`.
  B[i, i] = LinearAlgebra.hermitian(

src/implementations/SparseArrays.jl

@@ -85,7 +85,7 @@ function operate!(
  A = parent(adjA)
  A_nonzeros = SparseArrays.nonzeros(A)
  A_rowvals = SparseArrays.rowvals(A)
- for k in 1:size(ret, 2)
+ for k in axes(ret, 2)
  for col in 1:A.n
  cur = ret[col, k]
  for j in SparseArrays.nzrange(A, col)
@@ -108,8 +108,8 @@ function operate!(
  _dim_check(ret, A, B)
  A_nonzeros = SparseArrays.nonzeros(A)
  A_rowvals = SparseArrays.rowvals(A)
- for col in 1:size(A, 2)
- for k in 1:size(ret, 2)
+ for col in axes(A, 2)
+ for k in axes(ret, 2)
  αxj = *(B[col, k], α...)
  for j in SparseArrays.nzrange(A, col)
  ret[A_rowvals[j], k] =
@@ -130,8 +130,8 @@ function operate!(
  _dim_check(ret, A, B)
  rowval = SparseArrays.rowvals(B)
  B_nonzeros = SparseArrays.nonzeros(B)
- for multivec_row in 1:size(A, 1)
- for col in 1:size(B, 2)
+ for multivec_row in axes(A, 1)
+ for col in axes(B, 2)
  cur = ret[multivec_row, col]
  for k in SparseArrays.nzrange(B, col)
  cur = operate!!(
@@ -159,11 +159,11 @@ function operate!(
  B = parent(adjB)
  B_rowvals = SparseArrays.rowvals(B)
  B_nonzeros = SparseArrays.nonzeros(B)
- for B_col in 1:size(B, 2), k in SparseArrays.nzrange(B, B_col)
+ for B_col in axes(B, 2), k in SparseArrays.nzrange(B, B_col)
  B_row = B_rowvals[k]
  B_val = _mirror_transpose_or_adjoint(B_nonzeros[k], adjB)
  αB_val = *(B_val, α...)
- for A_row in 1:size(A, 1)
+ for A_row in axes(A, 1)
  ret[A_row, B_row] =
  operate!!(add_mul, ret[A_row, B_row], A[A_row, B_col], αB_val)
  end