--- a/src/Grids/Grids.jl	Fri Dec 01 14:58:05 2023 +0100
+++ b/src/Grids/Grids.jl	Fri Dec 01 15:01:44 2023 +0100
@@ -1,3 +1,4 @@
+# TODO: Double check that the interfaces for indexing and iterating are fully implemented and tested for all grids.
 module Grids
 
 using Sbplib.RegionIndices
@@ -32,11 +33,17 @@
 export equidistant_grid
 
 
+# CurvilinearGrid
+export CurvilinearGrid
+export jacobian
+export logicalgrid
+
 abstract type BoundaryIdentifier end
 
 include("grid.jl")
 include("tensor_grid.jl")
 include("equidistant_grid.jl")
 include("zero_dim_grid.jl")
+include("curvilinear_grid.jl")
 
 end # module

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/src/Grids/curvilinear_grid.jl	Fri Dec 01 15:01:44 2023 +0100
@@ -0,0 +1,46 @@
+# TBD: Rename to MappedGrid?
+struct CurvilinearGrid{T,D, GT<:Grid{<:Any,D}, CT<:AbstractArray{T,D}, JT<:AbstractArray{<:AbstractArray{<:Any, 2}, D}} <: Grid{T,D}
+    logicalgrid::GT
+    physicalcoordinates::CT
+    jacobian::JT
+end
+
+jacobian(g::CurvilinearGrid) = g.jacobian
+logicalgrid(g::CurvilinearGrid) = g.logicalgrid
+
+
+# Indexing interface
+Base.getindex(g::CurvilinearGrid, I::Vararg{Int}) = g.physicalcoordinates[I...]
+Base.eachindex(g::CurvilinearGrid) = eachindex(g.logicalgrid)
+
+Base.firstindex(g::CurvilinearGrid, d) = firstindex(g.logicalgrid, d)
+Base.lastindex(g::CurvilinearGrid, d) = lastindex(g.logicalgrid, d)
+
+# Iteration interface
+
+Base.iterate(g::CurvilinearGrid) = iterate(g.physicalcoordinates)
+Base.iterate(g::CurvilinearGrid, state) = iterate(g.physicalcoordinates, state)
+
+Base.IteratorSize(::Type{<:CurvilinearGrid{<:Any, D}}) where D = Base.HasShape{D}()
+Base.length(g::CurvilinearGrid) = length(g.logicalgrid)
+Base.size(g::CurvilinearGrid) = size(g.logicalgrid)
+Base.size(g::CurvilinearGrid, d) = size(g.logicalgrid, d)
+
+boundary_identifiers(g::CurvilinearGrid) = boundary_identifiers(g.logicalgrid)
+boundary_indices(g::CurvilinearGrid, id::TensorGridBoundary) = boundary_indices(g.logicalgrid, id)
+
+function boundary_grid(g::CurvilinearGrid, id::TensorGridBoundary)
+    b_indices = boundary_indices(g.logicalgrid, id)
+    return CurvilinearGrid(
+        boundary_grid(g.logicalgrid, id),
+        g.physicalcoordinates[b_indices...],
+        g.jacobian[b_indices...],
+    )
+end
+
+
+
+# Do we add a convenience function `curvilinear_grid`? It could help with
+# creating the logical grid, evaluating functions and possibly calculating the
+# entries in the jacobian.
+

--- a/src/Grids/tensor_grid.jl	Fri Dec 01 14:58:05 2023 +0100
+++ b/src/Grids/tensor_grid.jl	Fri Dec 01 15:01:44 2023 +0100
@@ -1,3 +1,5 @@
+# TODO: Check this file and other grids for duplicate implementation of general methods implemented for Grid
+
 """
     TensorGrid{T,D} <: Grid{T,D}
 

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test/Grids/curvilinear_grid_test.jl	Fri Dec 01 15:01:44 2023 +0100
@@ -0,0 +1,145 @@
+using Sbplib.Grids
+using Sbplib.RegionIndices
+using Test
+using StaticArrays
+
+@testset "CurvilinearGrid" begin
+    lg = equidistant_grid((11,11), (0,0), (1,1)) # TODO: Change dims of the grid to be different
+    x̄ = map(ξ̄ -> 2ξ̄, lg)
+    J = map(ξ̄ -> @SArray(fill(2., 2, 2)), lg)
+    cg = CurvilinearGrid(lg, x̄, J)
+
+    # TODO: Test constructor for different dims of range and domain for the coordinates
+    # TODO: Test constructor with different type than TensorGrid. a dummy type?
+
+    @test_broken false # @test_throws ArgumentError("Sizes must match") CurvilinearGrid(lg, map(ξ̄ -> @SArray[ξ̄[1], ξ̄[2], -ξ̄[1]], lg), rand(SMatrix{2,3,Float64},15,11))
+
+
+    @test cg isa Grid{SVector{2, Float64},2}
+
+    @test jacobian(cg) isa Array{<:AbstractMatrix}
+    @test logicalgrid(cg) isa Grid
+
+    @testset "Indexing Interface" begin
+        cg = CurvilinearGrid(lg, x̄, J)
+        @test cg[1,1] == [0.0, 0.0]
+        @test cg[4,2] == [0.6, 0.2]
+        @test cg[6,10] == [1., 1.8]
+
+        @test cg[begin, begin] == [0.0, 0.0]
+        @test cg[end,end] == [2.0, 2.0]
+        @test cg[begin,end] == [0., 2.]
+
+        @test eachindex(cg) == CartesianIndices((11,11))
+
+        @testset "cartesian indexing" begin
+            cases = [
+                 (1,1) ,
+                 (3,5) ,
+                 (10,6),
+                 (1,1) ,
+                 (3,2) ,
+            ]
+
+            @testset "i = $is" for (lg, is) ∈ cases
+                @test cg[CartesianIndex(is...)] == cg[is...]
+            end
+        end
+
+        @testset "eachindex" begin
+            @test eachindex(cg) == CartesianIndices((11,11))
+        end
+
+        @testset "firstindex" begin
+            @test firstindex(cg, 1) == 1
+            @test firstindex(cg, 2) == 1
+        end
+
+        @testset "lastindex" begin
+            @test lastindex(cg, 1) == 11
+            @test lastindex(cg, 2) == 11
+        end
+    end
+    # TODO: Test with different types of logical grids
+
+    @testset "Iterator interface" begin
+        sg = CurvilinearGrid(
+            equidistant_grid((15,11), (0,0), (1,1)),
+            map(ξ̄ -> @SArray[ξ̄[1], ξ̄[2], -ξ̄[1]], lg), rand(SMatrix{2,3,Float64},15,11)
+        )
+
+        @test eltype(cg) == SVector{2,Float64}
+        @test eltype(sg) == SVector{3,Float64}
+
+        @test eltype(typeof(cg)) == SVector{2,Float64}
+        @test eltype(typeof(sg)) == SVector{3,Float64}
+
+        @test size(cg) == (11,11)
+        @test size(sg) == (15,11)
+
+        @test size(cg,2) == 11
+        @test size(sg,2) == 11
+
+        @test length(cg) == 121
+        @test length(sg) == 165
+
+        @test Base.IteratorSize(cg) == Base.HasShape{2}()
+        @test Base.IteratorSize(typeof(cg)) == Base.HasShape{2}()
+
+        @test Base.IteratorSize(sg) == Base.HasShape{2}()
+        @test Base.IteratorSize(typeof(sg)) == Base.HasShape{2}()
+
+        element, state = iterate(cg)
+        @test element == lg[1,1].*2
+        element, _ =  iterate(cg, state)
+        @test element == lg[2,1].*2
+
+        element, state = iterate(sg)
+        @test element == sg.physicalcoordinates[1,1]
+        element, _ = iterate(sg, state)
+        @test element == sg.physicalcoordinates[2,1]
+
+        @test collect(cg) == 2 .* lg
+    end
+
+    @testset "Base" begin
+        @test ndims(cg) == 2
+    end
+
+    @testset "boundary_identifiers" begin
+        @test boundary_identifiers(cg) == boundary_identifiers(lg)
+    end
+
+    @testset "boundary_indices" begin
+        @test boundary_indices(cg, CartesianBoundary{1,Lower}()) == boundary_indices(lg,CartesianBoundary{1,Lower}())
+        @test boundary_indices(cg, CartesianBoundary{2,Lower}()) == boundary_indices(lg,CartesianBoundary{2,Lower}())
+        @test boundary_indices(cg, CartesianBoundary{1,Upper}()) == boundary_indices(lg,CartesianBoundary{1,Upper}())
+    end
+
+    @testset "boundary_grid" begin
+        @test boundary_grid(cg, TensorGridBoundary{1, Lower}()) == 2. * boundary_grid(lg,TensorGridBoundary{1, Lower}())
+        @test_broken boundary_grid(cg, TensorGridBoundary{1, Upper}()) == 2. * boundary_grid(lg,TensorGridBoundary{1, Upper}())
+        @test_broken boundary_grid(cg, TensorGridBoundary{2, Lower}()) == 2. * boundary_grid(lg,TensorGridBoundary{2, Lower}())
+        @test_broken boundary_grid(cg, TensorGridBoundary{2, Upper}()) == 2. * boundary_grid(lg,TensorGridBoundary{2, Upper}())
+    end
+
+    # TBD: Should curvilinear grid support refining and coarsening?
+    # This would require keeping the coordinate mapping around which seems burdensome, and might increase compilation time?
+    @testset "refine" begin
+        @test_broken refine(cg, 1) == cg
+        @test_broken refine(cg, 2) == CurvilinearGrid(refine(lg,2), x̄, J)
+        @test_broken refine(cg, 3) == CurvilinearGrid(refine(lg,3), x̄, J)
+    end
+
+    @testset "coarsen" begin
+        lg = equidistant_grid((11,11), (0,0), (1,1)) # TODO: Change dims of the grid to be different
+        x̄ = map(ξ̄ -> 2ξ̄, lg)
+        J = map(ξ̄ -> @SArray(fill(2., 2, 2)), lg)
+        cg = CurvilinearGrid(lg, x̄, J)
+
+        @test_broken coarsen(cg, 1) == cg
+        @test_broken coarsen(cg, 2) == CurvilinearGrid(coarsen(lg,2), x̄, J)
+
+        @test_broken false # @test_throws DomainError(3, "Size minus 1 must be divisible by the ratio.") coarsen(cg, 3)
+    end
+end