Mercurial > repos > public > sbplib_julia
view test/SbpOperators/volumeops/derivatives/second_derivative_test.jl @ 1726:471a948cd2b2 rename_module
Rename project from Sbplib to Diffinitive
author | Vidar Stiernström <vidar.stiernstrom@gmail.com> |
---|---|
date | Sat, 07 Sep 2024 12:11:53 -0700 |
parents | 43aaf710463e |
children |
line wrap: on
line source
using Test using Diffinitive.SbpOperators using Diffinitive.Grids using Diffinitive.LazyTensors import Diffinitive.SbpOperators.VolumeOperator # TODO: Refactor these test to look more like the tests in first_derivative_test.jl. @testset "SecondDerivative" begin operator_path = sbp_operators_path()*"standard_diagonal.toml" stencil_set = read_stencil_set(operator_path; order=4) inner_stencil = parse_stencil(stencil_set["D2"]["inner_stencil"]) closure_stencils = parse_stencil.(stencil_set["D2"]["closure_stencils"]) Lx = 3.5 Ly = 3. g_1D = equidistant_grid(0.0, Lx, 121) g_2D = equidistant_grid((0.0, 0.0), (Lx, Ly), 121, 123) @testset "Constructors" begin @testset "1D" begin Dₓₓ = second_derivative(g_1D, stencil_set) @test Dₓₓ == second_derivative(g_1D, inner_stencil, closure_stencils) @test Dₓₓ isa LazyTensor{Float64,1,1} end @testset "2D" begin Dₓₓ = second_derivative(g_2D,stencil_set,1) @test Dₓₓ isa LazyTensor{Float64,2,2} end end # Exact differentiation is measured point-wise. In other cases # the error is measured in the l2-norm. @testset "Accuracy" begin @testset "1D" begin l2(v) = sqrt(spacing(g_1D)[1]*sum(v.^2)); monomials = () maxOrder = 4; for i = 0:maxOrder-1 f_i(x) = 1/factorial(i)*x^i monomials = (monomials...,eval_on(g_1D,f_i)) end v = eval_on(g_1D,x -> sin(x)) vₓₓ = eval_on(g_1D,x -> -sin(x)) # 2nd order interior stencil, 1nd order boundary stencil, # implies that L*v should be exact for monomials up to order 2. @testset "2nd order" begin stencil_set = read_stencil_set(operator_path; order=2) Dₓₓ = second_derivative(g_1D,stencil_set) @test Dₓₓ*monomials[1] ≈ zeros(Float64,size(g_1D)...) atol = 5e-10 @test Dₓₓ*monomials[2] ≈ zeros(Float64,size(g_1D)...) atol = 5e-10 @test Dₓₓ*monomials[3] ≈ monomials[1] atol = 5e-10 @test Dₓₓ*v ≈ vₓₓ rtol = 5e-2 norm = l2 end # 4th order interior stencil, 2nd order boundary stencil, # implies that L*v should be exact for monomials up to order 3. @testset "4th order" begin stencil_set = read_stencil_set(operator_path; order=4) Dₓₓ = second_derivative(g_1D,stencil_set) # NOTE: high tolerances for checking the "exact" differentiation # due to accumulation of round-off errors/cancellation errors? @test Dₓₓ*monomials[1] ≈ zeros(Float64,size(g_1D)...) atol = 5e-10 @test Dₓₓ*monomials[2] ≈ zeros(Float64,size(g_1D)...) atol = 5e-10 @test Dₓₓ*monomials[3] ≈ monomials[1] atol = 5e-10 @test Dₓₓ*monomials[4] ≈ monomials[2] atol = 5e-10 @test Dₓₓ*v ≈ vₓₓ rtol = 5e-4 norm = l2 end end @testset "2D" begin l2(v) = sqrt(prod(spacing.(g_2D.grids))*sum(v.^2)); binomials = () maxOrder = 4; for i = 0:maxOrder-1 f_i(x,y) = 1/factorial(i)*y^i + x^i binomials = (binomials...,eval_on(g_2D,f_i)) end v = eval_on(g_2D, (x,y) -> sin(x)+cos(y)) v_yy = eval_on(g_2D,(x,y) -> -cos(y)) # 2nd order interior stencil, 1st order boundary stencil, # implies that L*v should be exact for binomials up to order 2. @testset "2nd order" begin stencil_set = read_stencil_set(operator_path; order=2) Dyy = second_derivative(g_2D,stencil_set,2) @test Dyy*binomials[1] ≈ zeros(Float64,size(g_2D)...) atol = 5e-9 @test Dyy*binomials[2] ≈ zeros(Float64,size(g_2D)...) atol = 5e-9 @test Dyy*binomials[3] ≈ eval_on(g_2D,(x,y)->1.) atol = 5e-9 @test Dyy*v ≈ v_yy rtol = 5e-2 norm = l2 end # 4th order interior stencil, 2nd order boundary stencil, # implies that L*v should be exact for binomials up to order 3. @testset "4th order" begin stencil_set = read_stencil_set(operator_path; order=4) Dyy = second_derivative(g_2D,stencil_set,2) # NOTE: high tolerances for checking the "exact" differentiation # due to accumulation of round-off errors/cancellation errors? @test Dyy*binomials[1] ≈ zeros(Float64,size(g_2D)...) atol = 5e-9 @test Dyy*binomials[2] ≈ zeros(Float64,size(g_2D)...) atol = 5e-9 @test Dyy*binomials[3] ≈ eval_on(g_2D,(x,y)->1.) atol = 5e-9 @test Dyy*binomials[4] ≈ eval_on(g_2D,(x,y)->y) atol = 5e-9 @test Dyy*v ≈ v_yy rtol = 5e-4 norm = l2 end end end end