This package introduces the type StructArray which is an AbstractArray whose elements are struct (for example NamedTuples, or ComplexF64, or a custom user defined struct). While a StructArray iterates structs, the layout uses separate arrays for each field of the struct. This is often called Structure-Of-Arrays (SOA); the concepts will be explained in greater detail below. struct entries of a StructArray are constructed on-the-fly. This contrasts with the "Array-Of-Structs" (AOS) layout where individual array elements are explicitly stored as structs.
Base.getproperty or the dot syntax can be used to access struct fields of element of a StructArray, whereas elements can be accessed with getindex ([]).
The package was largely inspired by the Columns type in IndexedTables which it now replaces.
One can create a StructArray by providing the struct type and a Tuple or NamedTuple of field arrays:
using StructArrays
struct Foo{T}
a::T
b::T
end
adata = [1 2; 3 4]; bdata = [10 20; 30 40];
x = StructArray{Foo}((adata, bdata))
You can also initialize a StructArray by passing in a NamedTuple, in which case the name (rather than the order) specifies how the input arrays are assigned to fields:
x = StructArray{Foo}((b = adata, a = bdata)) # initialize a with bdata and vice versa
If a struct is not specified, a StructArray with Tuple or NamedTuple elements will be created:
x = StructArray((adata, bdata))
x = StructArray((a = adata, b = bdata))
It's also possible to create a StructArray by choosing a particular dimension to interpret as the components of a struct:
x = StructArray{Complex{Int}}(adata; dims=1) # along dimension 1, the first item `re` and the second is `im`
x = StructArray{Complex{Int}}(adata; dims=2) # along dimension 2, the first item `re` and the second is `im`
One can also create a StructArray from an iterable of structs without creating an intermediate Array:
StructArray(log(j+2.0*im) for j in 1:10)
Another option is to create an uninitialized StructArray and then fill it with data. Just like in normal arrays, this is done with the undef syntax:
julia> s = StructArray{ComplexF64}(undef, 2, 2)
2×2 StructArray(::Matrix{Float64}, ::Matrix{Float64}) with eltype Complex{Float64}:
6.91646e-310+6.91646e-310im 6.91646e-310+6.91646e-310im
6.91646e-310+6.91646e-310im 6.91646e-310+6.91646e-310im
julia> rand!(s)
2×2 StructArray(::Matrix{Float64}, ::Matrix{Float64}) with eltype Complex{Float64}:
0.680079+0.874437im 0.625239+0.737254im
0.92407+0.929336im 0.267358+0.804478imFinally, it is possible to create a StructArray from an array-of-structs:
julia> aos = [1+2im, 3+4im]
2-element Vector{Complex{Int64}}:
1 + 2im
3 + 4im
julia> aos.re # Vectors do not have fields, so this is an error
ERROR: type Array has no field re
[...]
julia> soa = StructArray(aos)
2-element StructArray(::Vector{Int64}, ::Vector{Int64}) with eltype Complex{Int64}:
1 + 2im
3 + 4im
julia> soa.re
2-element Vector{Int64}:
1
3
!!! warning
Unlike the other cases above, soa contains a copy of the data in aos. For more discussion, see Some counterintuitive behaviors.
StructArrays supports using custom array types. It is always possible to pass field arrays of a custom type. The "custom array of structs to struct of custom arrays" transformation will use the similar method of the custom array type. This can be useful when working on the GPU for example:
julia> using StructArrays, CuArrays
julia> a = CuArray(rand(Float32, 10));
julia> b = CuArray(rand(Float32, 10));
julia> StructArray{ComplexF32}((a, b))
10-element StructArray(::CuArray{Float32,1}, ::CuArray{Float32,1}) with eltype Complex{Float32}:
0.19555175f0 + 0.9604322f0im
0.68348145f0 + 0.5778245f0im
0.69664395f0 + 0.79825306f0im
0.118531585f0 + 0.3031248f0im
0.80057466f0 + 0.8964418f0im
0.63772964f0 + 0.2923274f0im
0.65374136f0 + 0.7932533f0im
0.6043732f0 + 0.65964353f0im
0.1106627f0 + 0.090207934f0im
0.707458f0 + 0.1700114f0im
julia> c = CuArray(rand(ComplexF32, 10));
julia> StructArray(c)
10-element StructArray(::Vector{Float32}, ::Vector{Float32}) with eltype Complex{Float32}:
0.7176411f0 + 0.864058f0im
0.252609f0 + 0.14824867f0im
0.26842773f0 + 0.9084332f0im
0.33128333f0 + 0.5106474f0im
0.6509278f0 + 0.87059164f0im
0.9522146f0 + 0.053706646f0im
0.899577f0 + 0.63242567f0im
0.325814f0 + 0.59225655f0im
0.56267905f0 + 0.21927536f0im
0.49719965f0 + 0.754143f0imIf you already have your data in a StructArray with field arrays of a given format (say plain Array) you can change them with replace_storage:
julia> s = StructArray([1.0+im, 2.0-im])
2-element StructArray(::Vector{Float64}, ::Vector{Float64}) with eltype Complex{Float64}:
1.0 + 1.0im
2.0 - 1.0im
julia> replace_storage(CuArray, s)
2-element StructArray(::CuArray{Float64,1}, ::CuArray{Float64,1}) with eltype Complex{Float64}:
1.0 + 1.0im
2.0 - 1.0imStructArrays also provides a LazyRow wrapper for lazy row iteration. LazyRow(t, i) does not materialize the i-th row but returns a lazy wrapper around it on which getproperty does the correct thing. This is useful when the row has many fields only some of which are necessary. It also allows changing columns in place.
julia> t = StructArray((a = [1, 2], b = ["x", "y"]));
julia> LazyRow(t, 2).a
2
julia> LazyRow(t, 2).a = 123
123
julia> t
2-element StructArray(::Vector{Int64}, ::Vector{String}) with eltype NamedTuple{(:a, :b),Tuple{Int64,String}}:
(a = 1, b = "x")
(a = 123, b = "y")To iterate in a lazy way one can simply iterate LazyRows:
julia> map(t -> t.b ^ t.a, LazyRows(t))
2-element Vector{String}:
"x"
"yy"julia> struct Foo
a::Int
b::String
end
julia> s = StructArray([Foo(11, "a"), Foo(22, "b"), Foo(33, "c"), Foo(44, "d"), Foo(55, "e")]);
julia> s
5-element StructArray(::Vector{Int64}, ::Vector{String}) with eltype Foo:
Foo(11, "a")
Foo(22, "b")
Foo(33, "c")
Foo(44, "d")
Foo(55, "e")
julia> StructArrays.foreachfield(v -> deleteat!(v, 3), s)
julia> s
4-element StructArray(::Vector{Int64}, ::Vector{String}) with eltype Foo:
Foo(11, "a")
Foo(22, "b")
Foo(44, "d")
Foo(55, "e")