--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test/SbpOperators/allocations_test.jl	Thu Apr 07 07:37:02 2022 +0200
@@ -0,0 +1,287 @@
+using Test
+using BenchmarkTools
+
+using Sbplib.Grids
+using Sbplib.SbpOperators
+
+using Sbplib.LazyTensors
+using Sbplib.RegionIndices
+
+@testset "Allocations" begin
+    stencil_set = read_stencil_set(sbp_operators_path()*"standard_diagonal.toml", order=4)
+
+    @testset "1D" begin
+        g₁ = EquidistantGrid(15, 0.,1.)
+
+        H = inner_product(g₁, stencil_set)
+        H⁻¹ = inverse_inner_product(g₁, stencil_set)
+        D₂ = second_derivative(g₁, stencil_set, 1)
+
+        eₗ = boundary_restriction(g₁, stencil_set, CartesianBoundary{1,Lower}())
+        eᵣ = boundary_restriction(g₁, stencil_set, CartesianBoundary{1,Upper}())
+
+        dₗ = normal_derivative(g₁, stencil_set, CartesianBoundary{1,Lower}())
+        dᵣ = normal_derivative(g₁, stencil_set, CartesianBoundary{1,Upper}())
+
+
+
+        @testset "Derivative operator" begin
+            v = rand(size(g₁)...)
+            @test (@ballocated LazyTensors.apply($D₂, $v, 1)) == 0
+            @test (@ballocated LazyTensors.apply($D₂, $v, 6)) == 0
+            @test (@ballocated LazyTensors.apply($D₂, $v, 15)) == 0
+        end
+
+        @testset "inner_product operator" begin
+            v = rand(size(g₁)...)
+
+            @test (@ballocated LazyTensors.apply($H, $v, 1)) == 0
+            @test (@ballocated LazyTensors.apply($H, $v, 6)) == 0
+            @test (@ballocated LazyTensors.apply($H, $v, 15)) == 0
+
+            @test (@ballocated LazyTensors.apply($(H∘H), $v, 5)) == 0
+        end
+
+        @testset "inverse_inner_product operator" begin
+              v = rand(size(g₁)...)
+            @test (@ballocated LazyTensors.apply($H⁻¹, $v, 1)) == 0
+            @test (@ballocated LazyTensors.apply($H⁻¹, $v, 6)) == 0
+            @test (@ballocated LazyTensors.apply($H⁻¹, $v, 15)) == 0
+        end
+
+        @testset "boundary operators" begin
+            v = rand(size(g₁)...)
+            @test (@ballocated LazyTensors.apply($eₗ, $v)) == 0
+            @test (@ballocated LazyTensors.apply($eᵣ, $v)) == 0
+            @test (@ballocated LazyTensors.apply($dₗ, $v)) == 0
+            @test (@ballocated LazyTensors.apply($dᵣ, $v)) == 0
+        end
+
+        @testset "boundary operator transposes" begin
+            v = fill(1.)
+            @test (@ballocated LazyTensors.apply($eₗ', $v, 1)) == 0
+            @test (@ballocated LazyTensors.apply($eₗ', $v, 7)) == 0
+            @test (@ballocated LazyTensors.apply($eₗ', $v, 15)) == 0
+
+            @test (@ballocated LazyTensors.apply($eᵣ', $v, 1)) == 0
+            @test (@ballocated LazyTensors.apply($eᵣ', $v, 7)) == 0
+            @test (@ballocated LazyTensors.apply($eᵣ', $v, 15)) == 0
+
+            @test (@ballocated LazyTensors.apply($dₗ', $v, 1)) == 0
+            @test (@ballocated LazyTensors.apply($dₗ', $v, 7)) == 0
+            @test (@ballocated LazyTensors.apply($dₗ', $v, 15)) == 0
+
+            @test (@ballocated LazyTensors.apply($dᵣ', $v, 1)) == 0
+            @test (@ballocated LazyTensors.apply($dᵣ', $v, 7)) == 0
+            @test (@ballocated LazyTensors.apply($dᵣ', $v, 15)) == 0
+        end
+
+        @testset "sat terms" begin
+            v = rand(size(g₁)...)
+            neumannSATₗ = H⁻¹∘eₗ'∘dₗ
+            neumannSATᵣ = H⁻¹∘eᵣ'∘dᵣ
+
+
+            @test (@ballocated LazyTensors.apply($neumannSATₗ, $v, 1)) == 0
+            @test (@ballocated LazyTensors.apply($neumannSATₗ, $v, 6)) == 0
+            @test (@ballocated LazyTensors.apply($neumannSATₗ, $v, 15)) == 0
+
+            @test (@ballocated LazyTensors.apply($neumannSATᵣ, $v, 1)) == 0
+            @test (@ballocated LazyTensors.apply($neumannSATᵣ, $v, 6)) == 0
+            @test (@ballocated LazyTensors.apply($neumannSATᵣ, $v, 15)) == 0
+        end
+    end
+
+
+    @testset "2D" begin
+        g₂ = EquidistantGrid((15,15), (0.,0.),(1.,1.))
+
+        H = inner_product(g₂, stencil_set)
+        H⁻¹ = inverse_inner_product(g₂, stencil_set)
+        D₂x = second_derivative(g₂, stencil_set, 1)
+        D₂y = second_derivative(g₂, stencil_set, 2)
+
+        e₁ₗ = boundary_restriction(g₂, stencil_set, CartesianBoundary{1,Lower}())
+        e₁ᵤ = boundary_restriction(g₂, stencil_set, CartesianBoundary{1,Upper}())
+        e₂ₗ = boundary_restriction(g₂, stencil_set, CartesianBoundary{2,Lower}())
+        e₂ᵤ = boundary_restriction(g₂, stencil_set, CartesianBoundary{2,Upper}())
+
+        d₁ₗ = normal_derivative(g₂, stencil_set, CartesianBoundary{1,Lower}())
+        d₁ᵤ = normal_derivative(g₂, stencil_set, CartesianBoundary{1,Upper}())
+        d₂ₗ = normal_derivative(g₂, stencil_set, CartesianBoundary{2,Lower}())
+        d₂ᵤ = normal_derivative(g₂, stencil_set, CartesianBoundary{2,Upper}())
+
+        H₁ₗ = inner_product(boundary_grid(g₂, CartesianBoundary{1,Lower}()), stencil_set)
+        H₁ᵤ = inner_product(boundary_grid(g₂, CartesianBoundary{1,Upper}()), stencil_set)
+        H₂ₗ = inner_product(boundary_grid(g₂, CartesianBoundary{2,Lower}()), stencil_set)
+        H₂ᵤ = inner_product(boundary_grid(g₂, CartesianBoundary{2,Upper}()), stencil_set)
+
+
+        @testset "Derivative operator" begin
+            v = rand(size(g₂)...)
+            @test (@ballocated LazyTensors.apply($D₂x, $v,  1,  7)) == 0
+            @test (@ballocated LazyTensors.apply($D₂x, $v,  6,  7)) == 0
+            @test (@ballocated LazyTensors.apply($D₂x, $v, 15,  7)) == 0
+
+            @test (@ballocated LazyTensors.apply($D₂y, $v,  7,  1)) == 0
+            @test (@ballocated LazyTensors.apply($D₂y, $v,  7,  6)) == 0
+            @test (@ballocated LazyTensors.apply($D₂y, $v,  7, 15)) == 0
+
+            @test (@ballocated LazyTensors.apply($(D₂x∘D₂y), $v,   1,  1)) == 0
+            @test (@ballocated LazyTensors.apply($(D₂x∘D₂y), $v,   7,  6)) == 0
+            @test (@ballocated LazyTensors.apply($(D₂x∘D₂y), $v,  15, 15)) == 0
+        end
+
+        @testset "inner_product operator" begin
+            v = rand(size(g₂)...)
+            @test (@ballocated LazyTensors.apply($H, $v, 1,  1)) == 0
+            @test (@ballocated LazyTensors.apply($H, $v, 1,  6)) == 0
+            @test (@ballocated LazyTensors.apply($H, $v, 1, 15)) == 0
+            @test (@ballocated LazyTensors.apply($H, $v, 6,  1)) == 0
+            @test (@ballocated LazyTensors.apply($H, $v, 6,  6)) == 0
+            @test (@ballocated LazyTensors.apply($H, $v, 6, 15)) == 0
+            @test (@ballocated LazyTensors.apply($H, $v, 15,  1)) == 0
+            @test (@ballocated LazyTensors.apply($H, $v, 15,  6)) == 0
+            @test (@ballocated LazyTensors.apply($H, $v, 15, 15)) == 0
+
+
+            @test (@ballocated LazyTensors.apply($(H∘H), $v, 5, 5)) == 0
+        end
+
+        @testset "inverse_inner_product operator" begin
+            v = rand(size(g₂)...)
+            @test (@ballocated LazyTensors.apply($H⁻¹, $v, 1,  1)) == 0
+            @test (@ballocated LazyTensors.apply($H⁻¹, $v, 1,  6)) == 0
+            @test (@ballocated LazyTensors.apply($H⁻¹, $v, 1, 15)) == 0
+            @test (@ballocated LazyTensors.apply($H⁻¹, $v, 6,  1)) == 0
+            @test (@ballocated LazyTensors.apply($H⁻¹, $v, 6,  6)) == 0
+            @test (@ballocated LazyTensors.apply($H⁻¹, $v, 6, 15)) == 0
+            @test (@ballocated LazyTensors.apply($H⁻¹, $v, 15,  1)) == 0
+            @test (@ballocated LazyTensors.apply($H⁻¹, $v, 15,  6)) == 0
+            @test (@ballocated LazyTensors.apply($H⁻¹, $v, 15, 15)) == 0
+        end
+
+        @testset "boundary operators" begin
+            v = rand(size(g₂)...)
+            @test (@ballocated LazyTensors.apply($e₁ₗ, $v,  1)) == 0
+            @test (@ballocated LazyTensors.apply($e₁ᵤ, $v,  5)) == 0
+            @test (@ballocated LazyTensors.apply($e₂ₗ, $v, 15)) == 0
+            @test (@ballocated LazyTensors.apply($e₂ᵤ, $v,  3)) == 0
+
+            @test (@ballocated LazyTensors.apply($d₁ₗ, $v,  5)) == 0
+            @test (@ballocated LazyTensors.apply($d₁ᵤ, $v, 15)) == 0
+            @test (@ballocated LazyTensors.apply($d₂ₗ, $v,  1)) == 0
+            @test (@ballocated LazyTensors.apply($d₂ᵤ, $v,  5)) == 0
+        end
+
+        @testset "boundary operator transposes" begin
+            v = rand(first(size(g₂)))
+
+            @test (@ballocated LazyTensors.apply($e₁ₗ', $v, 1,  1)) == 0
+            @test (@ballocated LazyTensors.apply($e₁ₗ', $v, 1,  6)) == 0
+            @test (@ballocated LazyTensors.apply($e₁ₗ', $v, 1, 15)) == 0
+            @test (@ballocated LazyTensors.apply($e₁ₗ', $v, 6,  1)) == 0
+            @test (@ballocated LazyTensors.apply($e₁ₗ', $v, 6,  6)) == 0
+            @test (@ballocated LazyTensors.apply($e₁ₗ', $v, 6, 15)) == 0
+            @test (@ballocated LazyTensors.apply($e₁ₗ', $v, 15,  1)) == 0
+            @test (@ballocated LazyTensors.apply($e₁ₗ', $v, 15,  6)) == 0
+            @test (@ballocated LazyTensors.apply($e₁ₗ', $v, 15, 15)) == 0
+
+            @test (@ballocated LazyTensors.apply($d₂ᵤ', $v, 1,  1)) == 0
+            @test (@ballocated LazyTensors.apply($d₂ᵤ', $v, 1,  6)) == 0
+            @test (@ballocated LazyTensors.apply($d₂ᵤ', $v, 1, 15)) == 0
+            @test (@ballocated LazyTensors.apply($d₂ᵤ', $v, 6,  1)) == 0
+            @test (@ballocated LazyTensors.apply($d₂ᵤ', $v, 6,  6)) == 0
+            @test (@ballocated LazyTensors.apply($d₂ᵤ', $v, 6, 15)) == 0
+            @test (@ballocated LazyTensors.apply($d₂ᵤ', $v, 15,  1)) == 0
+            @test (@ballocated LazyTensors.apply($d₂ᵤ', $v, 15,  6)) == 0
+            @test (@ballocated LazyTensors.apply($d₂ᵤ', $v, 15, 15)) == 0
+        end
+
+        @testset "sat terms" begin
+            v = rand(size(g₂)...)
+            u = rand(size(g₂)[1])
+            # neumannSAT₁ₗ = H⁻¹∘e₁ₗ'∘H₁ₗ∘d₁ₗ
+            # neumannSAT₂ᵤ = H⁻¹∘e₂ᵤ'∘H₂ᵤ∘d₂ᵤ
+
+            neumannSAT₁ₗ = e₁ₗ'∘d₁ₗ
+            neumannSAT₂ᵤ = e₂ᵤ'∘d₂ᵤ
+
+            # indices = [1,6,15]
+            indices = [1]
+
+            @testset for i ∈ indices
+                @testset for j ∈ indices
+                    @test        (@ballocated LazyTensors.apply($(e₁ₗ'∘d₁ₗ),         $v, $i, $j)) == 0
+                    @test        (@ballocated LazyTensors.apply($(d₁ₗ'∘e₁ₗ),         $v, $i, $j)) == 0
+
+                    @test_broken (@ballocated LazyTensors.apply($(H⁻¹∘e₁ₗ'∘H₁ₗ∘d₁ₗ), $v, $i, $j)) == 0
+                    @test_broken (@ballocated LazyTensors.apply($(e₁ₗ'∘H₁ₗ∘d₁ₗ∘H⁻¹), $v, $i, $j)) == 0
+                    @test        (@ballocated LazyTensors.apply($(e₁ₗ'∘H₁ₗ∘d₁ₗ),     $v, $i, $j)) == 0
+                    @test_broken (@ballocated LazyTensors.apply($(H⁻¹∘e₁ₗ'∘d₁ₗ),     $v, $i, $j)) == 0
+                    @test        (@ballocated LazyTensors.apply($(H⁻¹∘D₂x),          $v, $i, $j)) == 0
+                    @test        (@ballocated LazyTensors.apply($(H⁻¹∘D₂y),          $v, $i, $j)) == 0
+                    @test_broken (@ballocated LazyTensors.apply($(H⁻¹∘D₂x∘D₂y),      $v, $i, $j)) == 0
+                    @test_broken (@ballocated LazyTensors.apply($(D₂x∘e₁ₗ'∘H₁ₗ∘d₁ₗ), $v, $i, $j)) == 0
+                    @test_broken (@ballocated LazyTensors.apply($(D₂y∘e₁ₗ'∘H₁ₗ∘d₁ₗ), $v, $i, $j)) == 0
+                    @test        (@ballocated LazyTensors.apply($(D₂x∘e₁ₗ'∘d₁ₗ),     $v, $i, $j)) == 0
+                    @test        (@ballocated LazyTensors.apply($(D₂y∘e₁ₗ'∘d₁ₗ),     $v, $i, $j)) == 0
+
+                    @test (@ballocated LazyTensors.apply($(H⁻¹∘e₁ₗ'), $u, $i, $j)) == 0
+                    @test (@ballocated LazyTensors.apply($(e₁ₗ'∘H₁ₗ), $u, $i, $j)) == 0
+                    @test (@ballocated LazyTensors.apply($(H₁ₗ∘d₁ₗ),  $v, $i)) == 0
+
+                    @test_broken (@ballocated LazyTensors.apply($(H⁻¹∘e₁ₗ'∘H₁ₗ), $u, $i, $j)) == 0
+                    @test        (@ballocated LazyTensors.apply($(H₁ₗ∘e₁ₗ∘H⁻¹),  $v, $i)) == 0
+                    @test        (@ballocated LazyTensors.apply($(H₁ₗ∘d₁ₗ∘H⁻¹),  $v, $i)) == 0
+
+                    @test_broken (@ballocated LazyTensors.apply($(e₁ₗ'∘e₁ₗ∘e₁ₗ'∘e₁ₗ), $v, $i, $j)) == 0
+                    @test        (@ballocated LazyTensors.apply($(e₁ₗ'∘e₁ₗ∘e₁ₗ'),     $u, $i, $j)) == 0
+                    @test        (@ballocated LazyTensors.apply($(e₁ₗ∘e₁ₗ'∘e₁ₗ),      $v, $i)) == 0
+                    @test        (@ballocated LazyTensors.apply($(e₁ₗ'∘e₁ₗ),          $v, $i, $j)) == 0
+                    @test        (@ballocated LazyTensors.apply($(e₁ₗ∘e₁ₗ'),          $u, $i)) == 0
+
+
+                    @test (@ballocated LazyTensors.apply($H, $v, $i, $j)) == 0
+                    @test (@ballocated LazyTensors.apply($(H∘H), $v, $i, $j)) == 0
+                    @test_broken (@ballocated LazyTensors.apply($(H∘H∘H), $v, $i, $j)) == 0
+                    @test_broken (@ballocated LazyTensors.apply($(H∘H∘H∘H), $v, $i, $j)) == 0
+                end
+                @test (@ballocated LazyTensors.apply($(e₁ₗ∘d₁ₗ'), $u, $i)) == 0
+                @test (@ballocated LazyTensors.apply($(d₁ₗ∘e₁ₗ'), $u, $i)) == 0
+
+                @test (@ballocated LazyTensors.apply($(e₁ₗ∘H∘d₁ₗ'), $u, $i)) == 0
+                @test (@ballocated LazyTensors.apply($(d₁ₗ∘H∘e₁ₗ'), $u, $i)) == 0
+
+                @test (@ballocated LazyTensors.apply($(H₁ₗ∘e₁ₗ∘d₁ₗ'), $u, $i)) == 0
+                @test (@ballocated LazyTensors.apply($(H₁ₗ∘d₁ₗ∘e₁ₗ'), $u, $i)) == 0
+
+                @test_broken (@ballocated LazyTensors.apply($(H₁ₗ∘e₁ₗ∘H∘d₁ₗ'), $u, $i)) == 0
+                @test_broken (@ballocated LazyTensors.apply($(H₁ₗ∘d₁ₗ∘H∘e₁ₗ'), $u, $i)) == 0
+
+                @test_broken (@ballocated LazyTensors.apply($(e₁ₗ∘H∘d₁ₗ'∘H₁ₗ), $u, $i)) == 0
+                @test_broken (@ballocated LazyTensors.apply($(d₁ₗ∘H∘e₁ₗ'∘H₁ₗ), $u, $i)) == 0
+            end
+            @test (@ballocated LazyTensors.apply($neumannSAT₁ₗ, $v,  1,  1)) == 0
+            @test (@ballocated LazyTensors.apply($neumannSAT₁ₗ, $v,  1,  6)) == 0
+            @test (@ballocated LazyTensors.apply($neumannSAT₁ₗ, $v,  1, 15)) == 0
+            @test (@ballocated LazyTensors.apply($neumannSAT₁ₗ, $v,  6,  1)) == 0
+            @test (@ballocated LazyTensors.apply($neumannSAT₁ₗ, $v,  6,  6)) == 0
+            @test (@ballocated LazyTensors.apply($neumannSAT₁ₗ, $v,  6, 15)) == 0
+            @test (@ballocated LazyTensors.apply($neumannSAT₁ₗ, $v, 15,  1)) == 0
+            @test (@ballocated LazyTensors.apply($neumannSAT₁ₗ, $v, 15,  6)) == 0
+            @test (@ballocated LazyTensors.apply($neumannSAT₁ₗ, $v, 15, 15)) == 0
+
+            @test (@ballocated LazyTensors.apply($neumannSAT₂ᵤ, $v,  1,  1)) == 0
+            @test (@ballocated LazyTensors.apply($neumannSAT₂ᵤ, $v,  1,  6)) == 0
+            @test (@ballocated LazyTensors.apply($neumannSAT₂ᵤ, $v,  1, 15)) == 0
+            @test (@ballocated LazyTensors.apply($neumannSAT₂ᵤ, $v,  6,  1)) == 0
+            @test (@ballocated LazyTensors.apply($neumannSAT₂ᵤ, $v,  6,  6)) == 0
+            @test (@ballocated LazyTensors.apply($neumannSAT₂ᵤ, $v,  6, 15)) == 0
+            @test (@ballocated LazyTensors.apply($neumannSAT₂ᵤ, $v, 15,  1)) == 0
+            @test (@ballocated LazyTensors.apply($neumannSAT₂ᵤ, $v, 15,  6)) == 0
+            @test (@ballocated LazyTensors.apply($neumannSAT₂ᵤ, $v, 15, 15)) == 0
+        end
+
+    end
+end