https://github.com/JuliaLang/julia
Tip revision: 2ac304dfba75fad148d4070ef4f8a2e400c305bb authored by Tony Kelman on 18 March 2016, 00:58:17 UTC
Tag v0.4.5
Tag v0.4.5
Tip revision: 2ac304d
abstractarray.jl
# This file is a part of Julia. License is MIT: http://julialang.org/license
# token type on which to dispatch testing methods in order to avoid potential
# name conflicts elsewhere in the base test suite
type TestAbstractArray end
## Tests for the abstract array interfaces with minimally defined array types
# A custom linear fast array type with 24 elements that doesn't rely upon Array storage
type T24Linear{T,N,dims} <: AbstractArray{T,N}
v1::T; v2::T; v3::T; v4::T; v5::T; v6::T; v7::T; v8::T
v9::T; v10::T; v11::T; v12::T; v13::T; v14::T; v15::T; v16::T
v17::T; v18::T; v19::T; v20::T; v21::T; v22::T; v23::T; v24::T
T24Linear() = (prod(dims) == 24 || throw(DimensionMismatch("T24Linear must have 24 elements")); new())
function T24Linear(v1,v2,v3,v4,v5,v6,v7,v8,v9,v10,v11,v12,v13,v14,v15,v16,v17,v18,v19,v20,v21,v22,v23,v24)
prod(dims) == 24 || throw(DimensionMismatch("T24Linear must have 24 elements"))
new(v1,v2,v3,v4,v5,v6,v7,v8,v9,v10,v11,v12,v13,v14,v15,v16,v17,v18,v19,v20,v21,v22,v23,v24)
end
end
T24Linear{T}(::Type{T}, dims::Int...) = T24Linear(T, dims)
T24Linear{T,N}(::Type{T}, dims::NTuple{N,Int}) = T24Linear{T,N,dims}()
Base.convert{T,N }(::Type{T24Linear }, X::AbstractArray{T,N}) = convert(T24Linear{T,N}, X)
Base.convert{T,N,_}(::Type{T24Linear{T }}, X::AbstractArray{_,N}) = convert(T24Linear{T,N}, X)
Base.convert{T,N }(::Type{T24Linear{T,N}}, X::AbstractArray ) = T24Linear{T,N,size(X)}(X...)
Base.size{T,N,dims}(::T24Linear{T,N,dims}) = dims
import Base: LinearFast
Base.linearindexing{A<:T24Linear}(::Type{A}) = LinearFast()
Base.getindex(A::T24Linear, i::Int) = getfield(A, i)
Base.setindex!{T}(A::T24Linear{T}, v, i::Int) = setfield!(A, i, convert(T, v))
# A custom linear slow sparse-like array that relies upon Dict for its storage
immutable TSlow{T,N} <: AbstractArray{T,N}
data::Dict{NTuple{N,Int}, T}
dims::NTuple{N,Int}
end
TSlow{T}(::Type{T}, dims::Int...) = TSlow(T, dims)
TSlow{T,N}(::Type{T}, dims::NTuple{N,Int}) = TSlow{T,N}(Dict{NTuple{N,Int}, T}(), dims)
Base.convert{T,N }(::Type{TSlow }, X::AbstractArray{T,N}) = convert(TSlow{T,N}, X)
Base.convert{T,N,_}(::Type{TSlow{T }}, X::AbstractArray{_,N}) = convert(TSlow{T,N}, X)
Base.convert{T,N }(::Type{TSlow{T,N}}, X::AbstractArray ) = begin
A = TSlow(T, size(X))
for I in CartesianRange(size(X))
A[I.I...] = X[I.I...]
end
A
end
Base.size(A::TSlow) = A.dims
Base.similar{T}(A::TSlow, ::Type{T}, dims::Dims) = TSlow(T, dims)
import Base: LinearSlow
Base.linearindexing{A<:TSlow}(::Type{A}) = LinearSlow()
# Until #11242 is merged, we need to define each dimension independently
Base.getindex{T}(A::TSlow{T,0}) = get(A.data, (), zero(T))
Base.getindex{T}(A::TSlow{T,1}, i1::Int) = get(A.data, (i1,), zero(T))
Base.getindex{T}(A::TSlow{T,2}, i1::Int, i2::Int) = get(A.data, (i1,i2), zero(T))
Base.getindex{T}(A::TSlow{T,3}, i1::Int, i2::Int, i3::Int) =
get(A.data, (i1,i2,i3), zero(T))
Base.getindex{T}(A::TSlow{T,4}, i1::Int, i2::Int, i3::Int, i4::Int) =
get(A.data, (i1,i2,i3,i4), zero(T))
Base.getindex{T}(A::TSlow{T,5}, i1::Int, i2::Int, i3::Int, i4::Int, i5::Int) =
get(A.data, (i1,i2,i3,i4,i5), zero(T))
Base.setindex!{T}(A::TSlow{T,0}, v) = (A.data[()] = v)
Base.setindex!{T}(A::TSlow{T,1}, v, i1::Int) = (A.data[(i1,)] = v)
Base.setindex!{T}(A::TSlow{T,2}, v, i1::Int, i2::Int) = (A.data[(i1,i2)] = v)
Base.setindex!{T}(A::TSlow{T,3}, v, i1::Int, i2::Int, i3::Int) =
(A.data[(i1,i2,i3)] = v)
Base.setindex!{T}(A::TSlow{T,4}, v, i1::Int, i2::Int, i3::Int, i4::Int) =
(A.data[(i1,i2,i3,i4)] = v)
Base.setindex!{T}(A::TSlow{T,5}, v, i1::Int, i2::Int, i3::Int, i4::Int, i5::Int) =
(A.data[(i1,i2,i3,i4,i5)] = v)
import Base: trailingsize
const can_inline = Base.JLOptions().can_inline != 0
function test_scalar_indexing{T}(::Type{T}, shape, ::Type{TestAbstractArray})
N = prod(shape)
A = reshape(1:N, shape)
B = T(A)
@test A == B
# Test indexing up to 5 dimensions
i=0
for i5 = 1:trailingsize(B, 5)
for i4 = 1:size(B, 4)
for i3 = 1:size(B, 3)
for i2 = 1:size(B, 2)
for i1 = 1:size(B, 1)
i += 1
@test A[i1,i2,i3,i4,i5] == B[i1,i2,i3,i4,i5] == i
@test A[i1,i2,i3,i4,i5] ==
Base.unsafe_getindex(B, i1, i2, i3, i4, i5) == i
end
end
end
end
end
# Test linear indexing and partial linear indexing
i=0
for i1 = 1:length(B)
i += 1
@test A[i1] == B[i1] == i
end
i=0
for i2 = 1:trailingsize(B, 2)
for i1 = 1:size(B, 1)
i += 1
@test A[i1,i2] == B[i1,i2] == i
end
end
@test A == B
i=0
for i3 = 1:trailingsize(B, 3)
for i2 = 1:size(B, 2)
for i1 = 1:size(B, 1)
i += 1
@test A[i1,i2,i3] == B[i1,i2,i3] == i
end
end
end
# Test zero-dimensional accesses
@test A[] == B[] == A[1] == B[1] == 1
# Test multidimensional scalar indexed assignment
C = T(Int, shape)
D1 = T(Int, shape)
D2 = T(Int, shape)
D3 = T(Int, shape)
i=0
for i5 = 1:trailingsize(B, 5)
for i4 = 1:size(B, 4)
for i3 = 1:size(B, 3)
for i2 = 1:size(B, 2)
for i1 = 1:size(B, 1)
i += 1
C[i1,i2,i3,i4,i5] = i
# test general unsafe_setindex!
Base.unsafe_setindex!(D1, i, i1,i2,i3,i4,i5)
# test for dropping trailing dims
Base.unsafe_setindex!(D2, i, i1,i2,i3,i4,i5, 1, 1, 1)
# test for expanding index argument to appropriate dims
Base.unsafe_setindex!(D3, i, i1,i2,i3,i4)
end
end
end
end
end
@test D1 == D2 == C == B == A
@test D3[:, :, :, :, 1] == D2[:, :, :, :, 1]
# Test linear indexing and partial linear indexing
C = T(Int, shape)
fill!(C, 0)
@test C != B && C != A
i=0
for i1 = 1:length(C)
i += 1
C[i1] = i
end
@test C == B == A
C = T(Int, shape)
i=0
for i2 = 1:trailingsize(C, 2)
for i1 = 1:size(C, 1)
i += 1
C[i1,i2] = i
end
end
@test C == B == A
C = T(Int, shape)
i=0
for i3 = 1:trailingsize(C, 3)
for i2 = 1:size(C, 2)
for i1 = 1:size(C, 1)
i += 1
C[i1,i2,i3] = i
end
end
end
@test C == B == A
# Test zero-dimensional setindex
A[] = 0; B[] = 0
@test A[] == B[] == 0
@test A == B
end
function test_vector_indexing{T}(::Type{T}, shape, ::Type{TestAbstractArray})
N = prod(shape)
A = reshape(1:N, shape)
B = T(A)
idxs = rand(1:N, 3, 3, 3)
@test B[idxs] == A[idxs] == idxs
@test B[vec(idxs)] == A[vec(idxs)] == vec(idxs)
@test B[:] == A[:] == collect(1:N)
@test B[1:end] == A[1:end] == collect(1:N)
@test B[:,:] == A[:,:] == reshape(1:N, shape[1], prod(shape[2:end]))
@test B[1:end,1:end] == A[1:end,1:end] == reshape(1:N, shape[1], prod(shape[2:end]))
# Test with containers that aren't Int[]
@test B[[]] == A[[]] == []
@test B[convert(Array{Any}, idxs)] == A[convert(Array{Any}, idxs)] == idxs
end
function test_primitives{T}(::Type{T}, shape, ::Type{TestAbstractArray})
N = prod(shape)
A = reshape(1:N, shape)
B = T(A)
# last(a)
@test last(B) == B[length(B)]
# strides(a::AbstractArray)
strides_B = strides(B)
for (i, _stride) in enumerate(collect(strides_B))
@test _stride == stride(B, i)
end
# isassigned(a::AbstractArray, i::Int...)
j = rand(1:length(B))
@test isassigned(B, j) == true
if T == T24Linear
@test isassigned(B, length(B) + 1) == false
end
# reshape(a::AbstractArray, dims::Dims)
@test_throws ArgumentError reshape(B, (0, 1))
# copy!(dest::AbstractArray, src::AbstractArray)
@test_throws BoundsError copy!(Array(Int, 10), [1:11...])
# convert{T, N}(::Type{Array}, A::AbstractArray{T, N})
X = [1:10...]
@test convert(Array, X) == X
end
function test_in_bounds(::Type{TestAbstractArray})
n = rand(2:5)
dims = tuple(rand(2:5, n)...)
len = prod(dims)
for i in 1:len
@test checkbounds(Bool, dims, i) == true
end
@test checkbounds(Bool, dims, len + 1) == false
end
type UnimplementedFastArray{T, N} <: AbstractArray{T, N} end
Base.linearindexing(::UnimplementedFastArray) = Base.LinearFast()
type UnimplementedSlowArray{T, N} <: AbstractArray{T, N} end
Base.linearindexing(::UnimplementedSlowArray) = Base.LinearSlow()
type UnimplementedArray{T, N} <: AbstractArray{T, N} end
function test_getindex_internals{T}(::Type{T}, shape, ::Type{TestAbstractArray})
N = prod(shape)
A = reshape(1:N, shape)
B = T(A)
@test getindex(A) == 1
@test getindex(B) == 1
@test Base.unsafe_getindex(A) == 1
@test Base.unsafe_getindex(B) == 1
end
function test_getindex_internals(::Type{TestAbstractArray})
U = UnimplementedFastArray{Int, 2}()
V = UnimplementedSlowArray{Int, 2}()
@test_throws ErrorException getindex(U, 1)
@test_throws ErrorException Base.unsafe_getindex(U, 1)
@test_throws ErrorException getindex(V, 1, 1)
@test_throws ErrorException Base.unsafe_getindex(V, 1, 1)
end
function test_setindex!_internals{T}(::Type{T}, shape, ::Type{TestAbstractArray})
N = prod(shape)
A = reshape(1:N, shape)
B = T(A)
Base.unsafe_setindex!(B, 1)
@test B[1] == 1
end
function test_setindex!_internals(::Type{TestAbstractArray})
U = UnimplementedFastArray{Int, 2}()
V = UnimplementedSlowArray{Int, 2}()
@test_throws ErrorException setindex!(U, 1)
@test_throws ErrorException Base.unsafe_setindex!(U, 1)
@test_throws ErrorException Base.unsafe_setindex!(U, 1, 1)
end
function test_get(::Type{TestAbstractArray})
A = T24Linear([1:24...])
B = TSlow([1:24...])
@test get(A, (), 0) == Int[]
@test get(B, (), 0) == TSlow(Int, 0)
end
function test_cat(::Type{TestAbstractArray})
A = T24Linear([1:24...])
b_int = reshape([1:27...], 3, 3, 3)
b_float = reshape(Float64[1:27...], 3, 3, 3)
b2hcat = Array(Float64, 3, 6, 3)
b1 = reshape([1:9...], 3, 3)
b2 = reshape([10:18...], 3, 3)
b3 = reshape([19:27...], 3, 3)
b2hcat[:, :, 1] = hcat(b1, b1)
b2hcat[:, :, 2] = hcat(b2, b2)
b2hcat[:, :, 3] = hcat(b3, b3)
b3hcat = Array(Float64, 3, 9, 3)
b3hcat[:, :, 1] = hcat(b1, b1, b1)
b3hcat[:, :, 2] = hcat(b2, b2, b2)
b3hcat[:, :, 3] = hcat(b3, b3, b3)
B = TSlow(b_int)
B1 = TSlow([1:24...])
B2 = TSlow([1:25...])
C1 = TSlow([1 2; 3 4])
C2 = TSlow([1 2 3; 4 5 6])
C3 = TSlow([1 2; 3 4; 5 6])
D = [1:24...]
i = rand(1:10)
@test cat(i) == Any[]
@test vcat() == Any[]
@test hcat() == Any[]
@test hcat(1, 1.0, 3, 3.0) == [1.0 1.0 3.0 3.0]
@test_throws ArgumentError hcat(B1, B2)
@test_throws ArgumentError vcat(C1, C2)
@test vcat(B) == B
@test hcat(B) == B
@test Base.typed_hcat(Float64, B) == TSlow(b_float)
@test Base.typed_hcat(Float64, B, B) == TSlow(b2hcat)
@test Base.typed_hcat(Float64, B, B, B) == TSlow(b3hcat)
@test vcat(B1, B2) == TSlow(vcat([1:24...], [1:25...]))
@test hcat(C1, C2) == TSlow([1 2 1 2 3; 3 4 4 5 6])
@test hcat(C1, C2, C1) == TSlow([1 2 1 2 3 1 2; 3 4 4 5 6 3 4])
# hvcat
for nbc in (1, 2, 3, 4, 5, 6)
@test hvcat(nbc, 1:120...) ==
transpose(reshape([1:120...], nbc, round(Int, 120 / nbc)))
end
@test_throws ArgumentError hvcat(7, 1:20...)
@test_throws ArgumentError hvcat((2), C1, C3)
@test_throws ArgumentError hvcat((1), C1, C2)
@test_throws ArgumentError hvcat((1), C2, C3)
tup = tuple(rand(1:10, i)...)
@test hvcat(tup) == []
# check for shape mismatch
@test_throws ArgumentError hvcat((2, 2), 1, 2, 3, 4, 5)
@test_throws ArgumentError Base.typed_hvcat(Int, (2, 2), 1, 2, 3, 4, 5)
# check for # of columns mismatch b/w rows
@test_throws ArgumentError hvcat((3, 2), 1, 2, 3, 4, 5, 6)
@test_throws ArgumentError Base.typed_hvcat(Int, (3, 2), 1, 2, 3, 4, 5, 6)
end
function test_ind2sub(::Type{TestAbstractArray})
n = rand(2:5)
dims = tuple(rand(1:5, n)...)
len = prod(dims)
A = reshape(1:len, dims...)
I = ind2sub(dims, [1:len...])
for i in 1:len
idx = [ I[j][i] for j in 1:n ]
@test A[idx...] == A[i]
end
end
# A custom linear slow array that insists upon Cartesian indexing
type TSlowNIndexes{T,N} <: AbstractArray{T,N}
data::Array{T,N}
end
Base.linearindexing{A<:TSlowNIndexes}(::Type{A}) = Base.LinearSlow()
Base.size(A::TSlowNIndexes) = size(A.data)
Base.getindex(A::TSlowNIndexes, index::Int...) = error("Must use $(ndims(A)) indexes")
Base.getindex{T}(A::TSlowNIndexes{T,2}, i::Int, j::Int) = A.data[i,j]
type GenericIterator{N} end
Base.start{N}(::GenericIterator{N}) = 1
Base.next{N}(::GenericIterator{N}, i) = (i, i + 1)
Base.done{N}(::GenericIterator{N}, i) = i > N ? true : false
function test_map(::Type{TestAbstractArray})
for typ in (Float16, Float32, Float64,
Int8, Int16, Int32, Int64, Int128,
UInt8, UInt16, UInt32, UInt64, UInt128
),
arg_typ in (Integer,
Signed,
Unsigned
)
X = typ[1:10...]
_typ = typeof(arg_typ(one(typ)))
@test map(arg_typ, X) == _typ[1:10...]
end
# generic map
f(x) = x + 1
I = GenericIterator{10}()
@test map(f, I) == Any[2:11...]
# AbstractArray map for 2 arg case
f(x, y) = x + y
A = Array(Int, 10)
B = Float64[1:10...]
C = Float64[1:10...]
@test Base.map_to!(f, 1, A, B, C) == Real[ 2 * i for i in 1:10 ]
@test map(f, Int[], Float64[]) == Float64[]
# AbstractArray map for N-arg case
f(x, y, z) = x + y + z
D = Float64[1:10...]
@test map!(f, A, B, C, D) == Int[ 3 * i for i in 1:10 ]
@test Base.map_to_n!(f, 1, A, (B, C, D)) == Real[ 3 * i for i in 1:10 ]
@test map(f, B, C, D) == Float64[ 3 * i for i in 1:10 ]
@test map(f, Int[], Int[], Complex{Int}[]) == Number[]
end
function test_map_promote(::Type{TestAbstractArray})
A = [1:10...]
f(x) = iseven(x) ? 1.0 : 1
@test Base.map_promote(f, A) == fill(1.0, 10)
end
function test_UInt_indexing(::Type{TestAbstractArray})
A = [1:100...]
_A = Expr(:quote, A)
for i in 1:100
_i8 = convert(UInt8, i)
_i16 = convert(UInt16, i)
_i32 = convert(UInt32, i)
for _i in (_i8, _i16, _i32)
@eval begin
@test $_A[$_i] == $i
end
end
end
end
function test_vcat_depwarn(::Type{TestAbstractArray})
if (Base.JLOptions()).depwarn > 1
@test_throws ErrorException [1:10]
@test_throws ErrorException [[1, 2], [3, 4]]
@test_throws ErrorException [[1, 2], [3, 4], [5, 6]]
else
olderr = STDERR
try
rd, wr = redirect_stderr()
@test [1:10] == [1:10...]
@test [[1, 2], [3, 4]] == [1, 2, 3, 4]
@test [[1, 2], [3, 4], [5, 6]] == [1, 2, 3, 4, 5, 6]
finally
redirect_stderr(olderr)
end
end
end
# Issue 13315
function test_13315(::Type{TestAbstractArray})
U = UInt(1):UInt(2)
@test [U;[U;]] == [UInt(1), UInt(2), UInt(1), UInt(2)]
end
#----- run tests -------------------------------------------------------------#
for T in (T24Linear, TSlow), shape in ((24,), (2, 12), (2,3,4), (1,2,3,4), (4,3,2,1))
test_scalar_indexing(T, shape, TestAbstractArray)
test_vector_indexing(T, shape, TestAbstractArray)
test_primitives(T, shape, TestAbstractArray)
test_getindex_internals(T, shape, TestAbstractArray)
test_setindex!_internals(T, shape, TestAbstractArray)
end
test_in_bounds(TestAbstractArray)
test_getindex_internals(TestAbstractArray)
test_setindex!_internals(TestAbstractArray)
test_get(TestAbstractArray)
test_cat(TestAbstractArray)
test_ind2sub(TestAbstractArray)
test_map(TestAbstractArray)
test_map_promote(TestAbstractArray)
test_UInt_indexing(TestAbstractArray)
test_vcat_depwarn(TestAbstractArray)
test_13315(TestAbstractArray)
A = TSlowNIndexes(rand(2,2))
@test_throws ErrorException A[1]
@test A[1,1] == A.data[1]
@test first(A) == A.data[1]