remove NaiveSurfaceNets and cleanup tests (support autodiff again)

Author: sjkelly

src/Meshing.jl

@@ -11,13 +11,11 @@ include("algorithmtypes.jl")
 include("common.jl")
 include("marching_tetrahedra.jl")
 include("marching_cubes.jl")
-include("surface_nets.jl")
 include("roots.jl")
 include("adaptive.jl")
 
 export isosurface,
        MarchingCubes,
-       MarchingTetrahedra,
-       NaiveSurfaceNets
+       MarchingTetrahedra
 
 end # module

src/algorithmtypes.jl

@@ -41,31 +41,9 @@ making this algorithm useful for topological analysis.
 - `iso` specifies the iso level to use for surface extraction.
 - `eps` is the tolerence around a voxel corner to ensure manifold mesh generation.
 """
-Base.@kwdef struct MarchingTetrahedra{T} <: AbstractMeshingAlgorithm
+Base.@kwdef struct MarchingTetrahedra{T,E} <: AbstractMeshingAlgorithm
     iso::T = 0.0
-    eps::T = 1e-3
-end
-
-"""
-    NaiveSurfaceNets(iso=0.0, eps=1e-3)
-    NaiveSurfaceNets(;iso=0.0, eps=1e-3)
-    NaiveSurfaceNets(iso)
-    NaiveSurfaceNets(iso,eps)
-
-Specifies the use of the Naive Surface Nets algorithm for isosurface extraction.
-This algorithm has a slight performance advantage in some cases over Marching Cubes.
-Each vertex is guaranteed to not be repeated (useful for topological analysis),
-however the algorithm does not guarantee accuracy and generates quad faces.
-
-- `iso` specifies the iso level to use for surface extraction.
-- `eps` is the tolerence around a voxel corner to ensure manifold mesh generation.
-- `reduceverts` reserved for future use.
-"""
-struct NaiveSurfaceNets{T} <: AbstractMeshingAlgorithm
-    iso::T
-    eps::T
-    reduceverts::Bool
-    insidepositive::Bool
+    eps::E = 1e-3
 end
 
 """
@@ -83,7 +61,7 @@ may be large and it will be difficult to extract topological/connectivity inform
 - `eps` (default: 1e-3) is the tolerence around a voxel corner to ensure manifold mesh generation.
 - `reduceverts` (default: true) if true will merge vertices within a voxel to reduce mesh size by around 30% and with slight performance improvement.
 """
-struct AdaptiveMarchingCubes{T} <: AbstractAdaptiveMeshingAlgorithm
+struct AdaptiveMarchingCubes{T,E} <: AbstractAdaptiveMeshingAlgorithm
     iso::T
     eps::T
     rtol::T
@@ -104,4 +82,3 @@ end
 #
 
 default_face_length(::Union{MarchingCubes,MarchingTetrahedra}) = 3
-default_face_length(::NaiveSurfaceNets) = 4

src/marching_cubes.jl

@@ -5,7 +5,10 @@ include("lut/mc.jl")
 function isosurface(sdf::AbstractArray{T,3}, method::MarchingCubes, X=-1:1, Y=-1:1, Z=-1:1) where {T}
     nx, ny, nz = size(sdf)
 
-    vts = NTuple{3,float(T)}[]
+    # find widest type
+    FT = promote_type(eltype(first(X)), eltype(first(Y)), eltype(first(Z)), eltype(T), typeof(method.iso))
+
+    vts = NTuple{3,float(FT)}[]
     fcs = NTuple{3,Int}[]
 
     xp = LinRange(first(X), last(X), nx)
@@ -44,7 +47,7 @@ function isosurface(f::Function, method::MarchingCubes, X=-1:1, Y=-1:1, Z=-1:1;
     nx, ny, nz = samples[1], samples[2], samples[3]
 
     # find widest type
-    FT = promote_type(eltype(first(X)), eltype(first(Y)), eltype(first(Z)), eltype(T))
+    FT = promote_type(eltype(first(X)), eltype(first(Y)), eltype(first(Z)), eltype(T), typeof(method.iso))
 
     vts = NTuple{3,float(FT)}[]
     fcs = NTuple{3,Int}[]

src/marching_tetrahedra.jl

@@ -128,9 +128,11 @@ end
 
 function isosurface(sdf::AbstractArray{T, 3}, method::MarchingTetrahedra, X=-1:1, Y=-1:1, Z=-1:1) where {T}
 
+    FT = promote_type(eltype(first(X)), eltype(first(Y)), eltype(first(Z)), eltype(T), typeof(method.iso), typeof(method.eps))
+
     vts    = Dict{Int, Int}()
     fcs = NTuple{3,Int}[]
-    vtsAry = NTuple{3,float(T)}[]
+    vtsAry = NTuple{3,float(FT)}[]
 
     # process each voxel
     nx::Int, ny::Int, nz::Int = size(sdf)
@@ -163,7 +165,7 @@ end
 function isosurface(f::F, method::MarchingTetrahedra, X=-1:1, Y=-1:1, Z=-1:1;
                     samples::NTuple{3,T}=_DEFAULT_SAMPLES) where {F, T}
 
-    FT = promote_type(eltype(first(X)), eltype(first(Y)), eltype(first(Z)), eltype(T))
+    FT = promote_type(eltype(first(X)), eltype(first(Y)), eltype(first(Z)), eltype(T), typeof(method.iso), typeof(method.eps))
 
     vts    = Dict{Int, Int}()
     fcs    = NTuple{3,Int}[]