using Test
using DiffOps
using Grids
using SbpOperators
using RegionIndices
using LazyTensors

@testset "BoundaryValue" begin
    op = readOperator(sbp_operators_path()*"d2_4th.txt",sbp_operators_path()*"h_4th.txt")
    g = EquidistantGrid((4,5), (0.0, 0.0), (1.0,1.0))

    e_w = BoundaryValue(op, g, CartesianBoundary{1,Lower}())
    e_e = BoundaryValue(op, g, CartesianBoundary{1,Upper}())
    e_s = BoundaryValue(op, g, CartesianBoundary{2,Lower}())
    e_n = BoundaryValue(op, g, CartesianBoundary{2,Upper}())

    v = zeros(Float64, 4, 5)
    v[:,5] = [1, 2, 3,4]
    v[:,4] = [1, 2, 3,4]
    v[:,3] = [4, 5, 6, 7]
    v[:,2] = [7, 8, 9, 10]
    v[:,1] = [10, 11, 12, 13]

    @test e_w  isa TensorMapping{T,2,1} where T
    @test e_w' isa TensorMapping{T,1,2} where T

    @test domain_size(e_w, (3,2)) == (2,)
    @test domain_size(e_e, (3,2)) == (2,)
    @test domain_size(e_s, (3,2)) == (3,)
    @test domain_size(e_n, (3,2)) == (3,)

    @test size(e_w'*v) == (5,)
    @test size(e_e'*v) == (5,)
    @test size(e_s'*v) == (4,)
    @test size(e_n'*v) == (4,)

    @test collect(e_w'*v) == [10,7,4,1.0,1]
    @test collect(e_e'*v) == [13,10,7,4,4.0]
    @test collect(e_s'*v) == [10,11,12,13.0]
    @test collect(e_n'*v) == [1,2,3,4.0]

    g_x = [1,2,3,4.0]
    g_y = [5,4,3,2,1.0]

    G_w = zeros(Float64, (4,5))
    G_w[1,:] = g_y

    G_e = zeros(Float64, (4,5))
    G_e[4,:] = g_y

    G_s = zeros(Float64, (4,5))
    G_s[:,1] = g_x

    G_n = zeros(Float64, (4,5))
    G_n[:,5] = g_x

    @test size(e_w*g_y) == (4,5)
    @test size(e_e*g_y) == (4,5)
    @test size(e_s*g_x) == (4,5)
    @test size(e_n*g_x) == (4,5)

    @test collect(e_w*g_y) == G_w
    @test collect(e_e*g_y) == G_e
    @test collect(e_s*g_x) == G_s
    @test collect(e_n*g_x) == G_n
end

@testset "NormalDerivative" begin
    op = readOperator(sbp_operators_path()*"d2_4th.txt",sbp_operators_path()*"h_4th.txt")
    g = EquidistantGrid((5,6), (0.0, 0.0), (4.0,5.0))

    d_w = NormalDerivative(op, g, CartesianBoundary{1,Lower}())
    d_e = NormalDerivative(op, g, CartesianBoundary{1,Upper}())
    d_s = NormalDerivative(op, g, CartesianBoundary{2,Lower}())
    d_n = NormalDerivative(op, g, CartesianBoundary{2,Upper}())


    v = evalOn(g, (x,y)-> x^2 + (y-1)^2 + x*y)
    v∂x = evalOn(g, (x,y)-> 2*x + y)
    v∂y = evalOn(g, (x,y)-> 2*(y-1) + x)

    @test d_w  isa TensorMapping{T,2,1} where T
    @test d_w' isa TensorMapping{T,1,2} where T

    @test domain_size(d_w, (3,2)) == (2,)
    @test domain_size(d_e, (3,2)) == (2,)
    @test domain_size(d_s, (3,2)) == (3,)
    @test domain_size(d_n, (3,2)) == (3,)

    @test size(d_w'*v) == (6,)
    @test size(d_e'*v) == (6,)
    @test size(d_s'*v) == (5,)
    @test size(d_n'*v) == (5,)

    @test collect(d_w'*v) ≈ v∂x[1,:]
    @test collect(d_e'*v) ≈ v∂x[5,:]
    @test collect(d_s'*v) ≈ v∂y[:,1]
    @test collect(d_n'*v) ≈ v∂y[:,6]


    d_x_l = zeros(Float64, 5)
    d_x_u = zeros(Float64, 5)
    for i ∈ eachindex(d_x_l)
        d_x_l[i] = op.dClosure[i-1]
        d_x_u[i] = -op.dClosure[length(d_x_u)-i]
    end

    d_y_l = zeros(Float64, 6)
    d_y_u = zeros(Float64, 6)
    for i ∈ eachindex(d_y_l)
        d_y_l[i] = op.dClosure[i-1]
        d_y_u[i] = -op.dClosure[length(d_y_u)-i]
    end

    function ❓(x,y)
        G = zeros(Float64, length(x), length(y))
        for I ∈ CartesianIndices(G)
            G[I] = x[I[1]]*y[I[2]]
        end

        return G
    end

    g_x = [1,2,3,4.0,5]
    g_y = [5,4,3,2,1.0,11]

    G_w = ❓(d_x_l, g_y)
    G_e = ❓(d_x_u, g_y)
    G_s = ❓(g_x, d_y_l)
    G_n = ❓(g_x, d_y_u)


    @test size(d_w*g_y) == (5,6)
    @test size(d_e*g_y) == (5,6)
    @test size(d_s*g_x) == (5,6)
    @test size(d_n*g_x) == (5,6)

    @test collect(d_w*g_y) ≈ G_w
    @test collect(d_e*g_y) ≈ G_e
    @test collect(d_s*g_x) ≈ G_s
    @test collect(d_n*g_x) ≈ G_n
end