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thomasgudjonwrightthomasgudjonwright
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Adding two MOInput types (#310)
* Initial push for adding two MOInput types * Change supertype name, address field types * Updating Base functions defined * Removing MOInput from documentation * Using boundschecks * Remove iterate def and bump version * Addressing a few small comments: mainly fixing typos in docs * Adding tests for type updates * Fixing docstrings, typos * Fixing compat and format suggestion * Add MOInput alias and change test var names * Add helper methods to create MOInput types * Fixing tests from changed exports * Removing exports, adding MOInput alias, restoring docs * Version edit * Fixing test I missed * Update docs project compat * *Hopefully* fixing CI bug * Addressing a few typos * Bump version, remove helper methods, change out_dim type to Integer * Adding MOInput deprecation note * Removing small change that was accidentally included in last commit * Bumping docs manifest
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‎Project.toml

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Original file line numberDiff line numberDiff line change
@@ -1,6 +1,6 @@
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name = "KernelFunctions"
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uuid = "ec8451be-7e33-11e9-00cf-bbf324bd1392"
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version = "0.10.7"
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version = "0.10.8"
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[deps]
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ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"

‎docs/Manifest.toml

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@@ -119,7 +119,7 @@ version = "0.21.1"
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deps = ["ChainRulesCore", "Compat", "CompositionsBase", "Distances", "FillArrays", "Functors", "LinearAlgebra", "Random", "Requires", "SpecialFunctions", "StatsBase", "StatsFuns", "TensorCore", "Test", "ZygoteRules"]
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path = ".."
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uuid = "ec8451be-7e33-11e9-00cf-bbf324bd1392"
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version = "0.10.6"
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version = "0.10.8"
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[[Kronecker]]
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deps = ["FillArrays", "LinearAlgebra", "NamedDims", "SparseArrays", "StatsBase"]

‎src/mokernels/moinput.jl

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@@ -1,15 +1,44 @@
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"""
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MOInput(x::AbstractVector, out_dim::Integer)
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MOInputIsotopicByFeatures(x::AbstractVector, out_dim::Integer)
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4-
A data type to accomodate modelling multi-dimensional output data.
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`MOInputIsotopicByFeatures(x, out_dim)` has length `out_dim * length(x)`.
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6-
`MOInput(x, out_dim)` has length `length(x) * out_dim`.
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```jldoctest
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julia> x = [1, 2, 3];
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julia> KernelFunctions.MOInputIsotopicByFeatures(x, 2)
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6-element KernelFunctions.MOInputIsotopicByFeatures{Int64, Vector{Int64}}:
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(1, 1)
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(1, 2)
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(2, 1)
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(2, 2)
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(3, 1)
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(3, 2)
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```
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Accommodates modelling multi-dimensional output data where all outputs are always observed.
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As shown above, an `MOInputIsotopicByFeatures` represents a vector of tuples.
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The first `out_dim` elements represent all outputs for the first input, the second
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`out_dim` elements represent the outputs for the second input, etc.
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See [Inputs for Multiple Outputs](@ref) in the docs for more info.
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"""
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struct MOInputIsotopicByFeatures{S,T<:AbstractVector{S}} <: AbstractVector{Tuple{S,Int}}
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x::T
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out_dim::Integer
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end
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"""
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MOInputIsotopicByOutputs(x::AbstractVector, out_dim::Integer)
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`MOInputIsotopicByOutputs(x, out_dim)` has length `length(x) * out_dim`.
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```jldoctest
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julia> x = [1, 2, 3];
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julia> MOInput(x, 2)
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6-element MOInput{Vector{Int64}}:
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julia> KernelFunctions.MOInputIsotopicByOutputs(x, 2)
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6-element KernelFunctions.MOInputIsotopicByOutputs{Int64, Vector{Int64}}:
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(1, 1)
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(2, 1)
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(3, 1)
@@ -18,40 +47,59 @@ julia> MOInput(x, 2)
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(3, 2)
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```
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As shown above, an `MOInput` represents a vector of tuples.
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Accommodates modelling multi-dimensional output data where all outputs are always observed.
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As shown above, an `MOInputIsotopicByOutputs` represents a vector of tuples.
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The first `length(x)` elements represent the inputs for the first output, the second
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`length(x)` elements represent the inputs for the second output, etc.
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See [Inputs for Multiple Outputs](@ref) in the docs for more info.
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"""
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struct MOInput{T<:AbstractVector} <: AbstractVector{Tuple{Any,Int}}
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struct MOInputIsotopicByOutputs{S,T<:AbstractVector{S}} <: AbstractVector{Tuple{S,Int}}
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x::T
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out_dim::Integer
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end
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Base.length(inp::MOInput) = inp.out_dim * length(inp.x)
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Base.size(inp::MOInput, d) = d::Integer == 1 ? inp.out_dim * size(inp.x, 1) : 1
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Base.size(inp::MOInput) = (inp.out_dim * size(inp.x, 1),)
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Base.lastindex(inp::MOInput) = length(inp)
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Base.firstindex(inp::MOInput) = 1
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function Base.getindex(inp::MOInput, ind::Integer)
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if ind > 0
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out_dim = ind ÷ length(inp.x) + 1
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ind = ind % length(inp.x)
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if ind == 0
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ind = length(inp.x)
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out_dim -= 1
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end
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return (inp.x[ind], out_dim::Int)
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else
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throw(BoundsError(string("Trying to access at ", ind)))
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end
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const IsotopicMOInputs = Union{MOInputIsotopicByFeatures,MOInputIsotopicByOutputs}
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function Base.getindex(inp::MOInputIsotopicByOutputs, ind::Integer)
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@boundscheck checkbounds(inp, ind)
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output_index, feature_index = fldmod1(ind, length(inp.x))
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feature = @inbounds inp.x[feature_index]
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return feature, output_index
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end
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Base.iterate(inp::MOInput) = (inp[1], 1)
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function Base.iterate(inp::MOInput, state)
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return (state < length(inp)) ? (inp[state + 1], state + 1) : nothing
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function Base.getindex(inp::MOInputIsotopicByFeatures, ind::Integer)
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@boundscheck checkbounds(inp, ind)
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feature_index, output_index = fldmod1(ind, inp.out_dim)
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feature = @inbounds inp.x[feature_index]
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return feature, output_index
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end
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Base.size(inp::IsotopicMOInputs) = (inp.out_dim * length(inp.x),)
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"""
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MOInput(x::AbstractVector, out_dim::Integer)
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A data type to accommodate modelling multi-dimensional output data.
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`MOInput(x, out_dim)` has length `length(x) * out_dim`.
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```jldoctest
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julia> x = [1, 2, 3];
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julia> MOInput(x, 2)
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6-element KernelFunctions.MOInputIsotopicByOutputs{Int64, Vector{Int64}}:
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(1, 1)
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(2, 1)
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(3, 1)
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(1, 2)
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(2, 2)
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(3, 2)
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```
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As shown above, an `MOInput` represents a vector of tuples.
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The first `length(x)` elements represent the inputs for the first output, the second
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`length(x)` elements represent the inputs for the second output, etc.
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See [Inputs for Multiple Outputs](@ref) in the docs for more info.
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`MOInput` will be deprecated in version 0.11 in favour of `MOInputIsotopicByOutputs`,
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and removed in version 0.12.
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"""
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const MOInput = MOInputIsotopicByOutputs

‎test/mokernels/moinput.jl

Lines changed: 44 additions & 16 deletions
Original file line numberDiff line numberDiff line change
@@ -1,19 +1,47 @@
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@testset "moinput" begin
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x = [rand(5) for _ in 1:4]
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mgpi = MOInput(x, 3)
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@test length(mgpi) == 12
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@test size(mgpi) == (12,)
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@test size(mgpi, 1) == 12
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@test size(mgpi, 2) == 1
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@test lastindex(mgpi) == 12
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@test firstindex(mgpi) == 1
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@test iterate(mgpi) == (mgpi[1], 1)
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@test iterate(mgpi, 2) == (mgpi[3], 3)
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@test_throws BoundsError mgpi[0]
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@test mgpi[2] == (x[2], 1)
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@test mgpi[5] == (x[1], 2)
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@test mgpi[7] == (x[3], 2)
18-
@test all([(x_, i) for i in 1:3 for x_ in x] .== mgpi)
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type_1 = AbstractVector{Tuple{Vector{Float64},Int}}
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type_2 = AbstractVector{Tuple{AbstractVector{Vector{Float64}},Int}}
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6+
@testset "isotopicbyoutputs" begin
7+
ibo = MOInput(x, 3)
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@test ibo == KernelFunctions.MOInputIsotopicByOutputs(x, 3)
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@test isa(ibo, type_1) == true
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@test isa(ibo, type_2) == false
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@test length(ibo) == 12
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@test size(ibo) == (12,)
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@test size(ibo, 1) == 12
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@test size(ibo, 2) == 1
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@test lastindex(ibo) == 12
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@test firstindex(ibo) == 1
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@test_throws BoundsError ibo[0]
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22+
@test ibo[2] == (x[2], 1)
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@test ibo[5] == (x[1], 2)
24+
@test ibo[7] == (x[3], 2)
25+
@test all([(x_, i) for i in 1:3 for x_ in x] .== ibo)
26+
end
27+
28+
@testset "isotopicbyfeatures" begin
29+
ibf = KernelFunctions.MOInputIsotopicByFeatures(x, 3)
30+
31+
@test isa(ibf, type_1) == true
32+
@test isa(ibf, type_2) == false
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@test length(ibf) == 12
35+
@test size(ibf) == (12,)
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@test size(ibf, 1) == 12
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@test size(ibf, 2) == 1
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@test lastindex(ibf) == 12
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@test firstindex(ibf) == 1
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@test_throws BoundsError ibf[0]
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@test ibf[2] == (x[1], 2)
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@test ibf[5] == (x[2], 2)
44+
@test ibf[7] == (x[3], 1)
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@test all([(x_, i) for x_ in x for i in 1:3] .== ibf)
46+
end
1947
end

‎test/runtests.jl

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@@ -183,8 +183,8 @@ include("test_utils.jl")
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KernelFunctions;
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doctestfilters=[
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r"{([a-zA-Z0-9]+,\s?)+[a-zA-Z0-9]+}",
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r"(Array{[a-zA-Z0-9]+,\s?1}|Vector{[a-zA-Z0-9]+})",
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r"(Array{[a-zA-Z0-9]+,\s?2}|Matrix{[a-zA-Z0-9]+})",
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r"(Array{[a-zA-Z0-9]+,\s?1}|\s?Vector{[a-zA-Z0-9]+})",
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r"(Array{[a-zA-Z0-9]+,\s?2}|\s?Matrix{[a-zA-Z0-9]+})",
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],
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)
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end

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