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Merge pull request #626 from cfbaptista/FieldMatrix
Add FieldMatrix: a rank-two tensor generalisation of FieldVector
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‎src/FieldArray.jl

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"""
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abstract FieldArray{N, T, D} <: StaticArray{N, T, D}
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Inheriting from this type will make it easy to create your own rank-D tensor types. A `FieldArray`
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will automatically define `getindex` and `setindex!` appropriately. An immutable
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`FieldArray` will be as performant as an `SArray` of similar length and element type,
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while a mutable `FieldArray` will behave similarly to an `MArray`.
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For example:
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struct Stiffness <: FieldArray{Tuple{2,2,2,2}, Float64, 4}
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xxxx::Float64
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yxxx::Float64
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xyxx::Float64
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yyxx::Float64
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xxyx::Float64
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yxyx::Float64
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xyyx::Float64
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yyyx::Float64
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xxxy::Float64
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yxxy::Float64
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xyxy::Float64
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yyxy::Float64
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xxyy::Float64
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yxyy::Float64
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xyyy::Float64
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yyyy::Float64
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end
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Note that you must define the fields of any `FieldArray` subtype in column major order. If you
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want to use an alternative ordering you will need to pay special attention in providing your
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own definitions of `getindex`, `setindex!` and tuple conversion.
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"""
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abstract type FieldArray{N, T, D} <: StaticArray{N, T, D} end
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"""
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abstract FieldMatrix{N1, N2, T} <: FieldArray{Tuple{N1, N2}, 2}
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Inheriting from this type will make it easy to create your own rank-two tensor types. A `FieldMatrix`
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will automatically define `getindex` and `setindex!` appropriately. An immutable
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`FieldMatrix` will be as performant as an `SMatrix` of similar length and element type,
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while a mutable `FieldMatrix` will behave similarly to an `MMatrix`.
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For example:
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struct Stress <: FieldMatrix{3, 3, Float64}
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xx::Float64
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yx::Float64
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zx::Float64
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xy::Float64
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yy::Float64
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zy::Float64
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xz::Float64
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yz::Float64
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zz::Float64
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end
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Note that the fields of any subtype of `FieldMatrix` must be defined in column major order.
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This means that formatting of constructors for literal `FieldMatrix` can be confusing. For example
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sigma = Stress(1.0, 2.0, 3.0,
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4.0, 5.0, 6.0,
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7.0, 8.0, 9.0)
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3×3 Stress:
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1.0 4.0 7.0
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2.0 5.0 8.0
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3.0 6.0 9.0
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will give you the transpose of what the multi-argument formatting suggests. For clarity,
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you may consider using the alternative
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sigma = Stress(@SArray[1.0 2.0 3.0;
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4.0 5.0 6.0;
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7.0 8.0 9.0])
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"""
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abstract type FieldMatrix{N1, N2, T} <: FieldArray{Tuple{N1, N2}, T, 2} end
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"""
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abstract FieldVector{N, T} <: FieldArray{Tuple{N}, 1}
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Inheriting from this type will make it easy to create your own vector types. A `FieldVector`
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will automatically define `getindex` and `setindex!` appropriately. An immutable
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`FieldVector` will be as performant as an `SVector` of similar length and element type,
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while a mutable `FieldVector` will behave similarly to an `MVector`.
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For example:
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struct Point3D <: FieldVector{3, Float64}
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x::Float64
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y::Float64
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z::Float64
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end
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"""
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abstract type FieldVector{N, T} <: FieldArray{Tuple{N}, T, 1} end
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@inline function (::Type{FA})(x::Tuple{Vararg{Any, N}}) where {N, FA <: FieldArray}
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if length(FA) == length(x)
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FA(x...)
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else
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throw(DimensionMismatch("No precise constructor for $FA found. Length of input was $(length(x))."))
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end
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end
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@propagate_inbounds getindex(a::FieldArray, i::Int) = getfield(a, i)
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@propagate_inbounds setindex!(a::FieldArray, x, i::Int) = setfield!(a, i, x)
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Base.cconvert(::Type{<:Ptr}, a::FieldArray) = Base.RefValue(a)
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Base.unsafe_convert(::Type{Ptr{T}}, m::Base.RefValue{FA}) where {N,T,D,FA<:FieldArray{N,T,D}} =
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Ptr{T}(Base.unsafe_convert(Ptr{FA}, m))

‎src/FieldVector.jl

-28
This file was deleted.

‎src/StaticArrays.jl

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@@ -29,7 +29,7 @@ export SOneTo
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export StaticScalar, StaticArray, StaticVector, StaticMatrix
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export Scalar, SArray, SVector, SMatrix
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export MArray, MVector, MMatrix
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export FieldVector
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export FieldVector, FieldMatrix, FieldArray
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export SizedArray, SizedVector, SizedMatrix
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export SDiagonal
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export SHermitianCompact
@@ -71,7 +71,7 @@ For mutable containers you may also need to define the following:
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- In some cases, a zero-parameter constructor, `MyStaticArray{...}()` for unintialized data
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is assumed to exist.
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(see also `SVector`, `SMatrix`, `SArray`, `MVector`, `MMatrix`, `MArray`, `SizedArray` and `FieldVector`)
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(see also `SVector`, `SMatrix`, `SArray`, `MVector`, `MMatrix`, `MArray`, `SizedArray`, `FieldVector`, `FieldMatrix` and `FieldArray`)
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"""
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abstract type StaticArray{S <: Tuple, T, N} <: AbstractArray{T, N} end
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const StaticScalar{T} = StaticArray{Tuple{}, T, 0}
@@ -101,7 +101,7 @@ include("util.jl")
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include("traits.jl")
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include("SUnitRange.jl")
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include("FieldVector.jl")
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include("FieldArray.jl")
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include("SArray.jl")
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include("SMatrix.jl")
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include("SVector.jl")

‎test/FieldMatrix.jl

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@testset "FieldMatrix" begin
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@testset "Immutable Tensor3x3" begin
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eval(quote
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struct Tensor3x3 <: FieldMatrix{3, 3, Float64}
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xx::Float64
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yx::Float64
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zx::Float64
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xy::Float64
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yy::Float64
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zy::Float64
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xz::Float64
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yz::Float64
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zz::Float64
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end
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StaticArrays.similar_type(::Type{Tensor3x3}, ::Type{Float64}, s::Size{(3,3)}) = Tensor3x3
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end)
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p = Tensor3x3(1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0)
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@test_throws Exception p[2] = 4.0
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@test_throws Exception p[2, 3] = 6.0
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@test size(p) === (3,3)
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@test length(p) === 9
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@test eltype(p) === Float64
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@testinf Tuple(p) === (1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0)
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@test @inferred(p + p) === Tensor3x3(2.0, 4.0, 6.0, 8.0, 10.0, 12.0, 14.0, 16.0, 18.0)
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@test (p[1], p[2], p[3], p[4], p[5], p[6], p[7], p[8], p[9]) === (p.xx, p.yx, p.zx, p.xy, p.yy, p.zy, p.xz, p.yz, p.zz)
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m = @SMatrix [2.0 0.0 0.0;
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0.0 2.0 0.0;
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0.0 0.0 2.0]
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@test @inferred(p*m) === Tensor3x3(2.0, 4.0, 6.0, 8.0, 10.0, 12.0, 14.0, 16.0, 18.0)
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@test @inferred(similar_type(Tensor3x3)) == Tensor3x3
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@test @inferred(similar_type(Tensor3x3, Float64)) == Tensor3x3
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@test @inferred(similar_type(Tensor3x3, Float32)) == SMatrix{3,3,Float32,9}
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@test @inferred(similar_type(Tensor3x3, Size(4,4))) == SMatrix{4,4,Float64,16}
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@test @inferred(similar_type(Tensor3x3, Float32, Size(4,4))) == SMatrix{4,4,Float32,16}
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# Issue 146
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@test [[Tensor3x3(1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0)]; [Tensor3x3(2.0, 4.0, 6.0, 8.0, 10.0, 12.0, 14.0, 16.0, 18.0)]]::Vector{Tensor3x3} == [Tensor3x3(1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0), Tensor3x3(2.0, 4.0, 6.0, 8.0, 10.0, 12.0, 14.0, 16.0, 18.0)]
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# Issue 342
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@test_throws DimensionMismatch("No precise constructor for Tensor3x3 found. Length of input was 10.") Tensor3x3(1,2,3,4,5,6,7,8,9,10)
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end
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@testset "Mutable Tensor2x2" begin
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eval(quote
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mutable struct Tensor2x2{T} <: FieldMatrix{2, 2, T}
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xx::T
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yx::T
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xy::T
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yy::T
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end
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StaticArrays.similar_type(::Type{<:Tensor2x2}, ::Type{T}, s::Size{(2,2)}) where {T} = Tensor2x2{T}
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end)
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p = Tensor2x2(0.0, 0.0, 0.0, 0.0)
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p[1,1] = 1.0
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p[2,1] = 2.0
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@test size(p) === (2,2)
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@test length(p) === 4
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@test eltype(p) === Float64
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@testinf Tuple(p) === (1.0, 2.0, 0.0, 0.0)
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@test (p[1], p[2], p[3], p[4]) === (p.xx, p.yx, p.xy, p.yy)
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@test (p[1], p[2], p[3], p[4]) === (1.0, 2.0, 0.0, 0.0)
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m = @SMatrix [2.0 0.0;
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0.0 2.0]
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@test @inferred(p*m)::Tensor2x2 == Tensor2x2(2.0, 4.0, 0.0, 0.0)
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@test @inferred(similar_type(Tensor2x2{Float64})) == Tensor2x2{Float64}
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@test @inferred(similar_type(Tensor2x2{Float64}, Float32)) == Tensor2x2{Float32}
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@test @inferred(similar_type(Tensor2x2{Float64}, Size(3,3))) == SMatrix{3,3,Float64,9}
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@test @inferred(similar_type(Tensor2x2{Float64}, Float32, Size(4,4))) == SMatrix{4,4,Float32,16}
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end
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@testset "FieldMatrix with Tuple fields" begin
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# verify that having a field which is itself a Tuple
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# doesn't break anything
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eval(quote
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struct TupleField2 <: FieldMatrix{1, 1, NTuple{2, Int}}
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x::NTuple{2, Int}
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end
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end)
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x = TupleField2((1,2))
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@test length(x) == 1
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@test length(x[1]) == 2
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@test x.x == (1, 2)
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end
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end

‎test/FieldVector.jl

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y::T
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end
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StaticArrays.similar_type(::Type{P2D}, ::Type{T}, s::Size{(2,)}) where {P2D<:Point2D,T} = Point2D{T}
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StaticArrays.similar_type(::Type{<:Point2D}, ::Type{T}, s::Size{(2,)}) where {T} = Point2D{T}
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end)
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p = Point2D(0.0, 0.0)
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end
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@testset "FieldVector with Tuple fields" begin
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# verify that having a field which is itself a Tuple
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# verify that having a field which is itself a Tuple
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# doesn't break anything
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eval(quote

‎test/runtests.jl

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@@ -19,6 +19,7 @@ include("MMatrix.jl")
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include("SArray.jl")
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include("MArray.jl")
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include("FieldVector.jl")
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include("FieldMatrix.jl")
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include("Scalar.jl")
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include("SUnitRange.jl")
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include("SizedArray.jl")

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