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Project.toml

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name = "PackedArrays"
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name = "SymmetricFormats"
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uuid = "a91e544d-b3d6-4431-ae28-0549b1291c16"
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authors = ["Ben Arthur <[email protected]>"]
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version = "0.1.0"

README.md

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PackedArrays.jl defines the `SymmetricPacked` type which concatenates the
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SymmetricFormats.jl defines the `SymmetricPacked` type which concatenates the
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columns of either the upper or lower triangle into a vector thereby using
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only a little more than half the memory.
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```
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julia> using PackedArrays
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julia> using SymmetricFormats
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julia> A = rand(5,5)
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5×5 Matrix{Float64}:

src/PackedArrays.jl renamed to src/SymmetricFormats.jl

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module PackedArrays
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module SymmetricFormats
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import Base: require_one_based_indexing, size, convert, unsafe_convert
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import Base: getindex, setindex!, copy

test/blas.jl

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using PackedArrays, Test, LinearAlgebra
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using SymmetricFormats, Test, LinearAlgebra
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n=10
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for elty in (Float32, Float64)
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AU = Symmetric(M, :U)
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x = rand(elty, n)
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ALP_result_julia_lower = PackedArrays.pack*x*x' + AL, :L)
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ALP_result_blas_lower = PackedArrays.pack(AL, :L)
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PackedArrays.spr!('L', α, x, ALP_result_blas_lower)
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ALP_result_julia_lower = SymmetricFormats.pack*x*x' + AL, :L)
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ALP_result_blas_lower = SymmetricFormats.pack(AL, :L)
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SymmetricFormats.spr!('L', α, x, ALP_result_blas_lower)
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@test ALP_result_julia_lower ALP_result_blas_lower
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AUP_result_julia_upper = PackedArrays.pack*x*x' + AU, :U)
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AUP_result_blas_upper = PackedArrays.pack(AU, :U)
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PackedArrays.spr!('U', α, x, AUP_result_blas_upper)
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AUP_result_julia_upper = SymmetricFormats.pack*x*x' + AU, :U)
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AUP_result_blas_upper = SymmetricFormats.pack(AU, :U)
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SymmetricFormats.spr!('U', α, x, AUP_result_blas_upper)
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@test AUP_result_julia_upper AUP_result_blas_upper
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end
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end

test/runtests.jl

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using PackedArrays, Test, LinearAlgebra
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using SymmetricFormats, Test, LinearAlgebra
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A = collect(reshape(1:9.0,3,3))
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