Implement tests for PiecewiseLegendrePolyVector

[terasakisatoshi]

Ref #51

[terasakisatoshi]

Using Pluto notebook, I'm writing tests

using Markdown
using InteractiveUtils

# ╔═╡ e59fe3f2-a166-11ef-34c5-e76693e02115
using SparseIR

# ╔═╡ 1876a95e-8cef-4add-af2c-5af171f1b6f6
begin
    using StableRNGs: StableRNG
    using Test
end

# ╔═╡ f9841528-e9ad-4ffa-bc39-3b36506ce149
sve_result = SparseIR.SVEResult(LogisticKernel(1.0))

# ╔═╡ 1c69cea9-cc82-4c8e-86b4-ae0a652fd759
foreach(println, sve_result.u[1].data)

# ╔═╡ 3b56eb73-26f2-4c10-9262-ff3a330bf07e
sve_result.u[1].knots

# ╔═╡ 5d06aa6a-2e4a-4c0e-af1a-bacf93d23fcf
sve_result.u[1].l

# ╔═╡ afef9f6c-f1d5-4ddd-aa70-cba3a4818293
foreach(println, sve_result.u[2].data)

# ╔═╡ 3b0f871a-0223-4f0a-9a72-3c0fe646762c
sve_result.u[2].knots

# ╔═╡ 7ecec192-d154-4e49-b86e-9b572ca831bc
foreach(println, sve_result.u[3].data)

# ╔═╡ 0f318cd4-b81b-471c-99af-e827b6ca0db7
sve_result.u[3].knots

# ╔═╡ 5d1fa13c-da4d-4a80-b1e3-5723a7822652
sve_result.u[3].l

# ╔═╡ ec27c11b-6910-410f-9cca-dfa1d486b7ef
begin
    data1 = reshape(
        [
            0.49996553669802485
            -0.009838135710548356
            0.003315915376286483
            -2.4035906967802686e-5
            3.4824832610792906e-6
            -1.6818592059096e-8
            1.5530850593697272e-9
            -5.67191158452736e-12
            3.8438802553084145e-13
            -1.12861464373688e-15
            -1.4028528586225198e-16
            5.199431653846204e-18
            -3.490774002228127e-16
            4.339342349553959e-18
            -8.247505551908268e-17
            7.379549188001237e-19
            0.49996553669802485
            0.009838135710548356
            0.003315915376286483
            2.4035906967802686e-5
            3.4824832610792906e-6
            1.6818592059096e-8
            1.5530850593697272e-9
            5.67191158452736e-12
            3.8438802553084145e-13
            1.12861464373688e-15
            -1.4028528586225198e-16
            -5.199431653846204e-18
            -3.490774002228127e-16
            -4.339342349553959e-18
            -8.247505551908268e-17
            -7.379549188001237e-19
        ],
        16,
        2,
    )

    knots1 = [-1.0, 0.0, 1.0]
    l1 = 0
end

# ╔═╡ 4f869c8a-2266-4b46-a087-4a1bd816be3b
begin
    data2 = reshape(
        [
            -0.43195475509329695
            0.436151579050162
            -0.005257007544885257
            0.0010660519696441624
            -6.611545612452212e-6
            7.461310619506964e-7
            -3.2179499894475862e-9
            2.5166526274315926e-10
            -8.387341925898803e-13
            5.008268649326024e-14
            3.7750894390998034e-17
            -2.304983535459561e-16
            3.0252856483620636e-16
            -1.923751082183687e-16
            7.201014354168769e-17
            -3.2715804561902326e-17
            0.43195475509329695
            0.436151579050162
            0.005257007544885257
            0.0010660519696441624
            6.611545612452212e-6
            7.461310619506964e-7
            3.2179499894475862e-9
            2.5166526274315926e-10
            8.387341925898803e-13
            5.008268649326024e-14
            -3.7750894390998034e-17
            -2.304983535459561e-16
            -3.0252856483620636e-16
            -1.923751082183687e-16
            -7.201014354168769e-17
            -3.2715804561902326e-17
        ],
        16,
        2,
    )

    knots2 = [-1.0, 0.0, 1.0]
    l2 = 1
end

# ╔═╡ 679b430d-156c-42bf-8494-6bef308b635c
begin
    data3 = reshape(
        [
            -0.005870438661638806
            -0.8376202388555938
            0.28368166184926036
            -0.0029450618222246236
            0.0004277118923277169
            -2.4101642603229184e-6
            2.2287962786878678e-7
            -8.875091544426018e-10
            6.021488924175155e-11
            -1.8705305570705647e-13
            9.924398482443944e-15
            4.299521053905097e-16
            -1.0697019178666955e-16
            3.6972269778329906e-16
            -8.848885164903329e-17
            6.327687614609368e-17
            -0.005870438661638806
            0.8376202388555938
            0.28368166184926036
            0.0029450618222246236
            0.0004277118923277169
            2.4101642603229184e-6
            2.2287962786878678e-7
            8.875091544426018e-10
            6.021488924175155e-11
            1.8705305570705647e-13
            9.924398482443944e-15
            -4.299521053905097e-16
            -1.0697019178666955e-16
            -3.6972269778329906e-16
            -8.848885164903329e-17
            -6.327687614609368e-17
        ],
        16,
        2,
    )

    knots3 = [-1.0, 0.0, 1.0]
    l3 = 2
end

# ╔═╡ bf5a1d96-261a-41dd-99d0-284e8f00354d
begin
    pwlp1 = SparseIR.PiecewiseLegendrePoly(data1, knots1, l1)
    pwlp2 = SparseIR.PiecewiseLegendrePoly(data2, knots2, l2)
    pwlp3 = SparseIR.PiecewiseLegendrePoly(data3, knots3, l3)

    polys = SparseIR.PiecewiseLegendrePolyVector([pwlp1, pwlp2, pwlp3])
end

# ╔═╡ c0f095dd-d1fd-4c54-87b1-6ce00a7e49c9
@testset "PiecewiseLegendrePolyVector" begin
    @test length(polys) == 3

    polys = SparseIR.PiecewiseLegendrePolyVector(
        [
            SparseIR.PiecewiseLegendrePoly(data1, knots1, l1)
            SparseIR.PiecewiseLegendrePoly(data2, knots2, l2)
            SparseIR.PiecewiseLegendrePoly(data3, knots3, l3)
        ],
    )

    @test SparseIR.xmin(polys) == SparseIR.xmin(pwlp1)
    @test SparseIR.xmax(polys) == SparseIR.xmax(pwlp1)
    @test SparseIR.knots(polys) == SparseIR.knots(pwlp1)
    @test SparseIR.Δx(polys) == SparseIR.Δx(pwlp1)
    @test SparseIR.polyorder(polys) == SparseIR.polyorder(pwlp1)
    @test SparseIR.norms(polys) == SparseIR.norms(pwlp1)
    @test SparseIR.symm(polys) == SparseIR.symm.([pwlp1, pwlp2, pwlp3])

    @testset "polys(x::Float64)" begin
        x = rand(StableRNG(42))
        @test polys(x) == [pwlp1(x), pwlp2(x), pwlp3(x)]
        @test SparseIR.data(polys) ==
              cat(SparseIR.data.([pwlp1, pwlp2, pwlp3])..., dims = 3)
    end
    @testset "polys(x::Array)" begin
        x = rand(StableRNG(42), 2, 1, 4)
        tar = polys(x)
        @test size(tar) == (3, 2, 1, 4)
        ref = reshape(vcat([[pwlp1(e), pwlp2(e), pwlp3(e)] for e in x]...), 3, 2, 1, 4)
        @test tar == ref
    end
end