HYPRE.jl/test/runtests.jl

# SPDX-License-Identifier: MIT

using HYPRE
using HYPRE.Internals
using HYPRE.LibHYPRE
using LinearAlgebra
using MPI
using PartitionedArrays
using SparseArrays
using SparseMatricesCSR
using Test

MPI.Init()

@testset "HYPREMatrix" begin
    H = HYPREMatrix()
    @test H.IJMatrix == HYPRE_IJMatrix(C_NULL)
    @test H.ParCSRMatrix == HYPRE_ParCSRMatrix(C_NULL)

    H = Internals.init_matrix(MPI.COMM_WORLD, 1, 5)
    @test H.IJMatrix != HYPRE_IJMatrix(C_NULL)
    @test H.ParCSRMatrix == HYPRE_ParCSRMatrix(C_NULL)
    Internals.assemble_matrix(H)
    @test H.IJMatrix != HYPRE_IJMatrix(C_NULL)
    @test H.ParCSRMatrix != HYPRE_ParCSRMatrix(C_NULL)
end

@testset "HYPREMatrix(::SparseMatrixCS(C|R))" begin
    ilower, iupper = 4, 6
    CSC = convert(SparseMatrixCSC{HYPRE_Complex, HYPRE_Int}, sparse([
        1 2 0 0 3
        0 4 0 5 0
        0 6 7 0 8
    ]))
    CSR = sparsecsr(findnz(CSC)..., size(CSC)...)
    @test CSC == CSR
    csc = Internals.to_hypre_data(CSC, ilower, iupper)
    csr = Internals.to_hypre_data(CSR, ilower, iupper)
    @test csc[1]::HYPRE_Int == csr[1]::HYPRE_Int == 3 # nrows
    @test csc[2]::Vector{HYPRE_Int} == csr[2]::Vector{HYPRE_Int} == [3, 2, 3] # ncols
    @test csc[3]::Vector{HYPRE_BigInt} == csr[3]::Vector{HYPRE_BigInt} == [4, 5, 6] # rows
    @test csc[4]::Vector{HYPRE_BigInt} == csr[4]::Vector{HYPRE_BigInt} == [1, 2, 5, 2, 4, 2, 3, 5] # cols
    @test csc[5]::Vector{HYPRE_Complex} == csr[5]::Vector{HYPRE_Complex} == 1:8 # values

    # Optimizations for CSR matrix
    @test csr[4] == CSR.colval
    @test_broken csr[4] === CSR.colval
    @test csr[5] == CSR.nzval
    @test_broken csr[5]::Vector{HYPRE_Complex} === CSR.nzval

    @test_throws ArgumentError Internals.to_hypre_data(CSC, ilower, iupper-1)
    @test_throws ArgumentError Internals.to_hypre_data(CSR, ilower, iupper+1)

    ilower, iupper = 6, 10
    CSC = sprand(5, 10, 0.3)
    CSR = sparsecsr(findnz(CSC)..., size(CSC)...)
    @test CSC == CSR
    H = HYPREMatrix(CSC, ilower,  iupper)
    @test H.IJMatrix != HYPRE_IJMatrix(C_NULL)
    @test H.ParCSRMatrix != HYPRE_ParCSRMatrix(C_NULL)
    H = HYPREMatrix(CSR, ilower,  iupper)
    @test H.IJMatrix != HYPRE_IJMatrix(C_NULL)
    @test H.ParCSRMatrix != HYPRE_ParCSRMatrix(C_NULL)
end

function tomain(x)
    g = gather(x)
    be = get_backend(g.values)
    if be isa SequentialBackend
        return g.values.parts[1]
    else # if be isa MPIBackend
        return g.values.part
    end
end

@testset "HYPREMatrix(::PSparseMatrix)" begin
    # Sequential backend
    function diag_data(backend, parts)
        is_seq = backend isa SequentialBackend
        rows = PRange(parts, 10)
        cols = PRange(parts, 10)
        I, J, V = map_parts(parts) do p
            i = Int[]
            j = Int[]
            v = Float64[]
            if (is_seq && p == 1) || !is_seq
                append!(i, [1, 2, 3, 4, 5, 6])
                append!(j, [1, 2, 3, 4, 5, 6])
                append!(v, [1, 2, 3, 4, 5, 6])
            end
            if (is_seq && p == 2) || !is_seq
                append!(i, [4, 5, 6, 7, 8, 9, 10])
                append!(j, [4, 5, 6, 7, 8, 9, 10])
                append!(v, [4, 5, 6, 7, 8, 9, 10])
            end
            return i, j, v
        end
        add_gids!(rows, I)
        assemble!(I, J, V, rows)
        add_gids!(cols, J)
        return I, J, V, rows, cols
    end

    backend = SequentialBackend()
    parts = get_part_ids(backend, 2)
    CSC = PSparseMatrix(diag_data(backend, parts)...; ids=:global)
    CSR = PSparseMatrix(sparsecsr, diag_data(backend, parts)...; ids=:global)

    @test tomain(copy(CSC)) == tomain(copy(CSR)) ==
        Diagonal([1, 2, 3, 8, 10, 12, 7, 8, 9, 10])

    map_parts(CSC.values, CSC.rows.partition, CSC.cols.partition,
              CSR.values, CSR.rows.partition, CSR.cols.partition, parts) do args...
        cscvalues, cscrows, csccols, csrvalues, csrrows, csrcols, p = args
        csc = Internals.to_hypre_data(cscvalues, cscrows, csccols)
        csr = Internals.to_hypre_data(csrvalues, csrrows, csrcols)
        if p == 1
            nrows = 5
            ncols = [1, 1, 1, 1, 1]
            rows = [1, 2, 3, 4, 5]
            cols = [1, 2, 3, 4, 5]
            values = [1, 2, 3, 8, 10]
        else # if p == 1
            nrows = 5
            ncols = [1, 1, 1, 1, 1]
            rows = [6, 7, 8, 9, 10]
            cols = [6, 7, 8, 9, 10]
            values = [12, 7, 8, 9, 10]
        end
        @test csc[1]::HYPRE_Int == csr[1]::HYPRE_Int == nrows
        @test csc[2]::Vector{HYPRE_Int} == csr[2]::Vector{HYPRE_Int} == ncols
        @test csc[3]::Vector{HYPRE_BigInt} == csr[3]::Vector{HYPRE_BigInt} == rows
        @test csc[4]::Vector{HYPRE_BigInt} == csr[4]::Vector{HYPRE_BigInt} == cols
        @test csc[5]::Vector{HYPRE_Complex} == csr[5]::Vector{HYPRE_Complex} == values
    end

    # MPI backend
    backend = MPIBackend()
    parts = MPIData(1, MPI.COMM_WORLD, (1,)) # get_part_ids duplicates the comm
    CSC = PSparseMatrix(diag_data(backend, parts)...; ids=:global)
    CSR = PSparseMatrix(sparsecsr, diag_data(backend, parts)...; ids=:global)

    @test tomain(copy(CSC)) == tomain(copy(CSR)) ==
        Diagonal([1, 2, 3, 8, 10, 12, 7, 8, 9, 10])

    map_parts(CSC.values, CSC.rows.partition, CSC.cols.partition,
              CSR.values, CSR.rows.partition, CSR.cols.partition, parts) do args...
        cscvalues, cscrows, csccols, csrvalues, csrrows, csrcols, p = args
        csc = Internals.to_hypre_data(cscvalues, cscrows, csccols)
        csr = Internals.to_hypre_data(csrvalues, csrrows, csrcols)
        nrows = 10
        ncols = fill(1, 10)
        rows = collect(1:10)
        cols = collect(1:10)
        values = [1, 2, 3, 8, 10, 12, 7, 8, 9, 10]
        @test csc[1]::HYPRE_Int == csr[1]::HYPRE_Int == nrows
        @test csc[2]::Vector{HYPRE_Int} == csr[2]::Vector{HYPRE_Int} == ncols
        @test csc[3]::Vector{HYPRE_BigInt} == csr[3]::Vector{HYPRE_BigInt} == rows
        @test csc[4]::Vector{HYPRE_BigInt} == csr[4]::Vector{HYPRE_BigInt} == cols
        @test csc[5]::Vector{HYPRE_Complex} == csr[5]::Vector{HYPRE_Complex} == values
    end

end

@testset "HYPREVector" begin
    h = HYPREVector()
    @test h.IJVector == HYPRE_IJVector(C_NULL)
    @test h.ParVector == HYPRE_ParVector(C_NULL)

    h = Internals.init_vector(MPI.COMM_WORLD, 1, 5)
    @test h.IJVector != HYPRE_IJVector(C_NULL)
    @test h.ParVector == HYPRE_ParVector(C_NULL)
    Internals.assemble_vector(h)
    @test h.IJVector != HYPRE_IJVector(C_NULL)
    @test h.ParVector != HYPRE_ParVector(C_NULL)
end

@testset "HYPREVector(::Vector)" begin
    ilower, iupper = 1, 10
    b = rand(HYPRE_Complex, 10)
    h = HYPREVector(b, ilower, iupper)
    @test h.IJVector != HYPRE_IJVector(C_NULL)
    @test h.ParVector != HYPRE_ParVector(C_NULL)
    @test_throws ArgumentError HYPREVector([1, 2], ilower, iupper)

    ilower, iupper = 1, 10
    b = rand(HYPRE_Complex, 10)
    nvalues, indices, values = Internals.to_hypre_data(b, ilower, iupper)
    @test nvalues::HYPRE_Int == 10
    @test indices::Vector{HYPRE_Int} == collect(1:10)
    @test values::Vector{HYPRE_Complex} === b # === for correct eltype

    b = rand(1:10, 10)
    nvalues, indices, values = Internals.to_hypre_data(b, ilower, iupper)
    @test nvalues::HYPRE_Int == 10
    @test indices::Vector{HYPRE_Int} == collect(1:10)
    @test values::Vector{HYPRE_Complex} == b # == for other eltype
    @test_throws ArgumentError Internals.to_hypre_data([1, 2], ilower, iupper)
end

@testset "HYPREMatrix(::PVector)" begin
end