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apply index_type on value #204

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Sep 9, 2021
Merged

apply index_type on value #204

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28 changes: 11 additions & 17 deletions src/structarray.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -21,28 +21,23 @@ struct StructArray{T, N, C<:Tup, I} <: AbstractArray{T, N}
axes(c[i]) == ax || error("all field arrays must have same shape")
end
end
new{T, N, C, index_type(C)}(c)
new{T, N, C, index_type(c)}(c)
end
end

# compute optimal type to use for indexing as a function of component types
index_type(::Type{NamedTuple{names, types}}) where {names, types} = index_type(types)
index_type(::Type{Tuple{}}) = Int
function index_type(::Type{T}) where {T<:Tuple}
S, U = tuple_type_head(T), tuple_type_tail(T)
return _index_type(S, U)
# compute optimal type to use for indexing as a function of components
index_type(components::NamedTuple) = index_type(values(components))
index_type(::Tuple{}) = Int
function index_type(components::Tuple)
f, ls = first(components), tail(components)
return IndexStyle(f) isa IndexCartesian ? CartesianIndex{ndims(f)} : index_type(ls)
end
# Julia v1.7.0-beta3 doesn't seem to specialize `index_type` as defined above
# for tuple types with "many" elements (three or four, depending on the concrete
# types). However, we can help the compiler for homogeneous types by defining
# the specialization below.
index_type(::Type{NTuple{N, S}}) where {N, S} = _index_type(S)
# Only check first component if the all the component types match
index_type(components::NTuple) = invoke(index_type, Tuple{Tuple}, (first(components),))
# Return the index type parameter as a function of the StructArray type or instance
index_type(s::StructArray) = index_type(typeof(s))
index_type(::Type{StructArray{T, N, C, I}}) where {T, N, C, I} = I

function _index_type(::Type{S}, ::Type{U}=Tuple{}) where {S, U}
return IndexStyle(S) isa IndexCartesian ? CartesianIndex{ndims(S)} : index_type(U)
end

array_types(::Type{StructArray{T, N, C, I}}) where {T, N, C, I} = array_types(C)
array_types(::Type{NamedTuple{names, types}}) where {names, types} = types
array_types(::Type{TT}) where {TT<:Tuple} = TT
Expand Down Expand Up @@ -168,7 +163,6 @@ function buildfromslices(::Type{T}, unwrap::F, slices) where {T,F}
end
end


function Base.IndexStyle(::Type{S}) where {S<:StructArray}
index_type(S) === Int ? IndexLinear() : IndexCartesian()
end
Expand Down
22 changes: 12 additions & 10 deletions test/runtests.jl
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Expand Up @@ -50,11 +50,10 @@ end
end

@testset "indexstyle" begin
@inferred IndexStyle(StructArray(a=rand(10,10), b=view(rand(100,100), 1:10, 1:10)))
s = StructArray(a=rand(10,10), b=view(rand(100,100), 1:10, 1:10))
T = typeof(s)
@test IndexStyle(T) === IndexCartesian()
@test StructArrays.index_type(T) == CartesianIndex{2}
@test StructArrays.index_type(s) == CartesianIndex{2}
@test s[100] == s[10, 10] == (a=s.a[10,10], b=s.b[10,10])
s[100] = (a=1, b=1)
@test s[100] == s[10, 10] == (a=1, b=1)
Expand All @@ -63,22 +62,25 @@ end
@inferred IndexStyle(StructArray(a=rand(10,10), b=rand(10,10)))
s = StructArray(a=rand(10,10), b=rand(10,10))
T = typeof(s)
@test IndexStyle(T) === IndexLinear()
@test StructArrays.index_type(T) == Int
@test StructArrays.index_type(s) == Int
@inferred IndexStyle(s)
@test s[100] == s[10, 10] == (a=s.a[10,10], b=s.b[10,10])
s[100] = (a=1, b=1)
@test s[100] == s[10, 10] == (a=1, b=1)
s[10, 10] = (a=0, b=0)
@test s[100] == s[10, 10] == (a=0, b=0)

# inference for "many" types, both for linear ad Cartesian indexing
@inferred StructArrays.index_type(NTuple{2, Vector{Float64}})
@inferred StructArrays.index_type(NTuple{3, Matrix{Float64}})
@inferred StructArrays.index_type(NTuple{4, Array{Float64, 3}})
@inferred StructArrays.index_type(ntuple(_ -> rand(5), 2))
@inferred StructArrays.index_type(ntuple(_ -> rand(5, 5), 3))
@inferred StructArrays.index_type(ntuple(_ -> rand(5, 5, 5), 4))

@inferred StructArrays.index_type(ntuple(_ -> view(rand(5), 1:3), 2))
@inferred StructArrays.index_type(ntuple(_ -> view(rand(5, 5), 1:3, 1:2), 3))
@inferred StructArrays.index_type(ntuple(_ -> view(rand(5, 5, 5), 1:3, 1:2, 1:4), 4))

@inferred StructArrays.index_type(NTuple{2, SubArray{Float64, 1, Array{Float64, 2}, Tuple{Base.Slice{Base.OneTo{Int64}}, Int64}, true}})
@inferred StructArrays.index_type(NTuple{3, SubArray{Float64, 1, Array{Float64, 2}, Tuple{Base.Slice{Base.OneTo{Int64}}, Int64}, true}})
@inferred StructArrays.index_type(NTuple{4, SubArray{Float64, 1, Array{Float64, 2}, Tuple{Base.Slice{Base.OneTo{Int64}}, Int64}, true}})
@inferred StructArrays.index_type(ntuple(n -> n == 1 ? rand(5, 5) : view(rand(5, 5), 1:2, 1:3), 5))
@inferred IndexStyle(StructArray(a=rand(10,10), b=view(rand(100,100), 1:10, 1:10)))
end

@testset "replace_storage" begin
Expand Down