sbplib_julia: test/testSbpOperators.jl comparison

comparison test/testSbpOperators.jl @ 690:1accc3e051d0 refactor/operator_naming

Start changing the name of functions creating operators that are not types to lower case. E.g SecondDerivative->second_derivative

author	Vidar Stiernström <vidar.stiernstrom@it.uu.se>
date	Fri, 12 Feb 2021 16:16:45 +0100
parents	e14627e79a54
children	6ab473e0ea80

comparison

equal deleted inserted replaced

-:621460cf8279
+:1accc3e051d0
 g_1D = EquidistantGrid(121, 0.0, Lx)
 g_2D = EquidistantGrid((121,123), (0.0, 0.0), (Lx, Ly))
 @testset "Constructors" begin
 @testset "1D" begin
-Dₓₓ = SecondDerivative(g_1D,op.innerStencil,op.closureStencils)
+Dₓₓ = second_derivative(g_1D,op.innerStencil,op.closureStencils)
-@test Dₓₓ == SecondDerivative(g_1D,op.innerStencil,op.closureStencils,1)
+@test Dₓₓ == second_derivative(g_1D,op.innerStencil,op.closureStencils,1)
 @test Dₓₓ isa VolumeOperator
 end
 @testset "2D" begin
-Dₓₓ = SecondDerivative(g_2D,op.innerStencil,op.closureStencils,1)
+Dₓₓ = second_derivative(g_2D,op.innerStencil,op.closureStencils,1)
-D2 = SecondDerivative(g_1D,op.innerStencil,op.closureStencils)
+D2 = second_derivative(g_1D,op.innerStencil,op.closureStencils)
 I = IdentityMapping{Float64}(size(g_2D)[2])
 @test Dₓₓ == D2⊗I
 @test Dₓₓ isa TensorMapping{T,2,2} where T
 end
 end
 # 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
 op = read_D2_operator(sbp_operators_path()*"standard_diagonal.toml"; order=2)
-Dₓₓ = SecondDerivative(g_1D,op.innerStencil,op.closureStencils)
+Dₓₓ = second_derivative(g_1D,op.innerStencil,op.closureStencils)
 @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
 op = read_D2_operator(sbp_operators_path()*"standard_diagonal.toml"; order=4)
-Dₓₓ = SecondDerivative(g_1D,op.innerStencil,op.closureStencils)
+Dₓₓ = second_derivative(g_1D,op.innerStencil,op.closureStencils)
 # 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
 # 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
 op = read_D2_operator(sbp_operators_path()*"standard_diagonal.toml"; order=2)
-Dyy = SecondDerivative(g_2D,op.innerStencil,op.closureStencils,2)
+Dyy = second_derivative(g_2D,op.innerStencil,op.closureStencils,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] ≈ evalOn(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
 op = read_D2_operator(sbp_operators_path()*"standard_diagonal.toml"; order=4)
-Dyy = SecondDerivative(g_2D,op.innerStencil,op.closureStencils,2)
+Dyy = second_derivative(g_2D,op.innerStencil,op.closureStencils,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] ≈ evalOn(g_2D,(x,y)->1.) atol = 5e-9
 g_1D = EquidistantGrid(101, 0.0, 1.)
 g_3D = EquidistantGrid((51,101,52), (0.0, -1.0, 0.0), (1., 1., 1.))
 @testset "Constructors" begin
 op = read_D2_operator(sbp_operators_path()*"standard_diagonal.toml"; order=4)
 @testset "1D" begin
-L = Laplace(g_1D, op.innerStencil, op.closureStencils)
+L = laplace(g_1D, op.innerStencil, op.closureStencils)
-@test L == SecondDerivative(g_1D, op.innerStencil, op.closureStencils)
+@test L == second_derivative(g_1D, op.innerStencil, op.closureStencils)
 @test L isa TensorMapping{T,1,1}  where T
 end
 @testset "3D" begin
-L = Laplace(g_3D, op.innerStencil, op.closureStencils)
+L = laplace(g_3D, op.innerStencil, op.closureStencils)
 @test L isa TensorMapping{T,3,3} where T
-Dxx = SecondDerivative(g_3D, op.innerStencil, op.closureStencils,1)
+Dxx = second_derivative(g_3D, op.innerStencil, op.closureStencils,1)
-Dyy = SecondDerivative(g_3D, op.innerStencil, op.closureStencils,2)
+Dyy = second_derivative(g_3D, op.innerStencil, op.closureStencils,2)
-Dzz = SecondDerivative(g_3D, op.innerStencil, op.closureStencils,3)
+Dzz = second_derivative(g_3D, op.innerStencil, op.closureStencils,3)
 @test L == Dxx + Dyy + Dzz
 end
 end
 # Exact differentiation is measured point-wise. In other cases
 # 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
 op = read_D2_operator(sbp_operators_path()*"standard_diagonal.toml"; order=2)
-L = Laplace(g_3D,op.innerStencil,op.closureStencils)
+L = laplace(g_3D,op.innerStencil,op.closureStencils)
 @test L*polynomials[1] ≈ zeros(Float64, size(g_3D)...) atol = 5e-9
 @test L*polynomials[2] ≈ zeros(Float64, size(g_3D)...) atol = 5e-9
 @test L*polynomials[3] ≈ polynomials[1] atol = 5e-9
 @test L*v ≈ Δv 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
 op = read_D2_operator(sbp_operators_path()*"standard_diagonal.toml"; order=4)
-L = Laplace(g_3D,op.innerStencil,op.closureStencils)
+L = laplace(g_3D,op.innerStencil,op.closureStencils)
 # NOTE: high tolerances for checking the "exact" differentiation
 # due to accumulation of round-off errors/cancellation errors?
 @test L*polynomials[1] ≈ zeros(Float64, size(g_3D)...) atol = 5e-9
 @test L*polynomials[2] ≈ zeros(Float64, size(g_3D)...) atol = 5e-9
 @test L*polynomials[3] ≈ polynomials[1] atol = 5e-9
 @test op_l == BoundaryOperator(g_1D,closure_stencil,Lower())
 @test op_l == boundary_operator(g_1D,closure_stencil,CartesianBoundary{1,Lower}())
 @test op_l isa TensorMapping{T,0,1} where T
 op_r = BoundaryOperator{Upper}(closure_stencil,size(g_1D)[1])
-@test op_r == BoundaryRestriction(g_1D,closure_stencil,Upper())
+@test op_r == BoundaryOperator(g_1D,closure_stencil,Upper())
 @test op_r == boundary_operator(g_1D,closure_stencil,CartesianBoundary{1,Upper}())
 @test op_r isa TensorMapping{T,0,1} where T
 end
 @testset "2D" begin
 @inferred apply_transpose(op_r, u, Index(11,Upper))
 end
 end
-@testset "BoundaryRestriction" begin
+@testset "boundary_restriction" begin
 op = read_D2_operator(sbp_operators_path()*"standard_diagonal.toml"; order=4)
 g_1D = EquidistantGrid(11, 0.0, 1.0)
 g_2D = EquidistantGrid((11,15), (0.0, 0.0), (1.0,1.0))
-@testset "Constructors" begin
+@testset "boundary_restriction" begin
 @testset "1D" begin
-e_l = BoundaryRestriction(g_1D,op.eClosure,Lower())
+e_l = boundary_restriction(g_1D,op.eClosure,Lower())
-@test e_l == BoundaryRestriction(g_1D,op.eClosure,CartesianBoundary{1,Lower}())
+@test e_l == boundary_restriction(g_1D,op.eClosure,CartesianBoundary{1,Lower}())
 @test e_l == BoundaryOperator(g_1D,op.eClosure,Lower())
 @test e_l isa BoundaryOperator{T,Lower} where T
 @test e_l isa TensorMapping{T,0,1} where T
-e_r = BoundaryRestriction(g_1D,op.eClosure,Upper())
+e_r = boundary_restriction(g_1D,op.eClosure,Upper())
-@test e_r == BoundaryRestriction(g_1D,op.eClosure,CartesianBoundary{1,Upper}())
+@test e_r == boundary_restriction(g_1D,op.eClosure,CartesianBoundary{1,Upper}())
 @test e_r == BoundaryOperator(g_1D,op.eClosure,Upper())
 @test e_r isa BoundaryOperator{T,Upper} where T
 @test e_r isa TensorMapping{T,0,1} where T
 end
 @testset "2D" begin
-e_w = BoundaryRestriction(g_2D,op.eClosure,CartesianBoundary{1,Upper}())
+e_w = boundary_restriction(g_2D,op.eClosure,CartesianBoundary{1,Upper}())
 @test e_w isa InflatedTensorMapping
 @test e_w isa TensorMapping{T,1,2} where T
 end
 end
 @testset "Application" begin
 @testset "1D" begin
-e_l = BoundaryRestriction(g_1D, op.eClosure, CartesianBoundary{1,Lower}())
+e_l = boundary_restriction(g_1D, op.eClosure, CartesianBoundary{1,Lower}())
-e_r = BoundaryRestriction(g_1D, op.eClosure, CartesianBoundary{1,Upper}())
+e_r = boundary_restriction(g_1D, op.eClosure, CartesianBoundary{1,Upper}())
 v = evalOn(g_1D,x->1+x^2)
 u = fill(3.124)
 @test (e_l*v)[] == v[1]
 @test (e_r*v)[] == v[end]
 @test (e_r*v)[1] == v[end]
 end
 @testset "2D" begin
-e_w = BoundaryRestriction(g_2D, op.eClosure, CartesianBoundary{1,Lower}())
+e_w = boundary_restriction(g_2D, op.eClosure, CartesianBoundary{1,Lower}())
-e_e = BoundaryRestriction(g_2D, op.eClosure, CartesianBoundary{1,Upper}())
+e_e = boundary_restriction(g_2D, op.eClosure, CartesianBoundary{1,Upper}())
-e_s = BoundaryRestriction(g_2D, op.eClosure, CartesianBoundary{2,Lower}())
+e_s = boundary_restriction(g_2D, op.eClosure, CartesianBoundary{2,Lower}())
-e_n = BoundaryRestriction(g_2D, op.eClosure, CartesianBoundary{2,Upper}())
+e_n = boundary_restriction(g_2D, op.eClosure, CartesianBoundary{2,Upper}())
 v = rand(11, 15)
 u = fill(3.124)
 @test e_w*v == v[1,:]
 @test e_n*v == v[:,end]
 end
 end
 end
-@testset "NormalDerivative" begin
+@testset "normal_derivative" begin
 g_1D = EquidistantGrid(11, 0.0, 1.0)
 g_2D = EquidistantGrid((11,12), (0.0, 0.0), (1.0,1.0))
-@testset "Constructors" begin
+@testset "normal_derivative" begin
 op = read_D2_operator(sbp_operators_path()*"standard_diagonal.toml"; order=4)
 @testset "1D" begin
-d_l = NormalDerivative(g_1D, op.dClosure, Lower())
+d_l = normal_derivative(g_1D, op.dClosure, Lower())
-@test d_l == NormalDerivative(g_1D, op.dClosure, CartesianBoundary{1,Lower}())
+@test d_l == normal_derivative(g_1D, op.dClosure, CartesianBoundary{1,Lower}())
 @test d_l isa BoundaryOperator{T,Lower} where T
 @test d_l isa TensorMapping{T,0,1} where T
 end
 @testset "2D" begin
 op = read_D2_operator(sbp_operators_path()*"standard_diagonal.toml"; order=4)
-d_w = NormalDerivative(g_2D, op.dClosure, CartesianBoundary{1,Lower}())
+d_w = normal_derivative(g_2D, op.dClosure, CartesianBoundary{1,Lower}())
-d_n = NormalDerivative(g_2D, op.dClosure, CartesianBoundary{2,Upper}())
+d_n = normal_derivative(g_2D, op.dClosure, CartesianBoundary{2,Upper}())
 Ix = IdentityMapping{Float64}((size(g_2D)[1],))
 Iy = IdentityMapping{Float64}((size(g_2D)[2],))
-d_l = NormalDerivative(restrict(g_2D,1),op.dClosure,Lower())
+d_l = normal_derivative(restrict(g_2D,1),op.dClosure,Lower())
-d_r = NormalDerivative(restrict(g_2D,2),op.dClosure,Upper())
+d_r = normal_derivative(restrict(g_2D,2),op.dClosure,Upper())
 @test d_w ==  d_l⊗Iy
 @test d_n ==  Ix⊗d_r
 @test d_w isa TensorMapping{T,1,2} where T
 @test d_n isa TensorMapping{T,1,2} where T
 end
 v∂x = evalOn(g_2D, (x,y)-> 2*x + y)
 v∂y = evalOn(g_2D, (x,y)-> 2*(y-1) + x)
 # TODO: Test for higher order polynomials?
 @testset "2nd order" begin
 op = read_D2_operator(sbp_operators_path()*"standard_diagonal.toml"; order=2)
-d_w = NormalDerivative(g_2D, op.dClosure, CartesianBoundary{1,Lower}())
+d_w = normal_derivative(g_2D, op.dClosure, CartesianBoundary{1,Lower}())
-d_e = NormalDerivative(g_2D, op.dClosure, CartesianBoundary{1,Upper}())
+d_e = normal_derivative(g_2D, op.dClosure, CartesianBoundary{1,Upper}())
-d_s = NormalDerivative(g_2D, op.dClosure, CartesianBoundary{2,Lower}())
+d_s = normal_derivative(g_2D, op.dClosure, CartesianBoundary{2,Lower}())
-d_n = NormalDerivative(g_2D, op.dClosure, CartesianBoundary{2,Upper}())
+d_n = normal_derivative(g_2D, op.dClosure, CartesianBoundary{2,Upper}())
 @test d_w*v ≈ v∂x[1,:] atol = 1e-13
 @test d_e*v ≈ -v∂x[end,:] atol = 1e-13
 @test d_s*v ≈ v∂y[:,1] atol = 1e-13
 @test d_n*v ≈ -v∂y[:,end] atol = 1e-13
 end
 @testset "4th order" begin
 op = read_D2_operator(sbp_operators_path()*"standard_diagonal.toml"; order=4)
-d_w = NormalDerivative(g_2D, op.dClosure, CartesianBoundary{1,Lower}())
+d_w = normal_derivative(g_2D, op.dClosure, CartesianBoundary{1,Lower}())
-d_e = NormalDerivative(g_2D, op.dClosure, CartesianBoundary{1,Upper}())
+d_e = normal_derivative(g_2D, op.dClosure, CartesianBoundary{1,Upper}())
-d_s = NormalDerivative(g_2D, op.dClosure, CartesianBoundary{2,Lower}())
+d_s = normal_derivative(g_2D, op.dClosure, CartesianBoundary{2,Lower}())
-d_n = NormalDerivative(g_2D, op.dClosure, CartesianBoundary{2,Upper}())
+d_n = normal_derivative(g_2D, op.dClosure, CartesianBoundary{2,Upper}())
 @test d_w*v ≈ v∂x[1,:] atol = 1e-13
 @test d_e*v ≈ -v∂x[end,:] atol = 1e-13
 @test d_s*v ≈ v∂y[:,1] atol = 1e-13
 @test d_n*v ≈ -v∂y[:,end] atol = 1e-13

Mercurial > repos > public > sbplib_julia

comparison test/testSbpOperators.jl @ 690:1accc3e051d0 refactor/operator_naming