Merge pull request #18 from bionanoimaging/fix_type_tools

added new methods to similar_arr_type to deal with SubArray ReshapedA…

.gitignore

@@ -0,0 +1,5 @@
+Manifest.toml
+test/Manifest.toml
+exmaples/Manifest.toml
+
+docs/build/

Project.toml

@@ -1,7 +1,7 @@
 name = "NDTools"
 uuid = "98581153-e998-4eef-8d0d-5ec2c052313d"
 authors = ["Rainer Heintzmann <heintzmann@gmail.com>", "Felix Wechsler <fxw+git@mailbox.org>"]
-version = "0.6.0"
+version = "0.7.0"
 
 [deps]
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"

src/type_tools.jl

@@ -1,12 +1,12 @@
 export real_arr_type, complex_arr_type, similar_arr_type
 
 """
-    real_arr_type(::Type{TA}) where {TA<:AbstractArray}
+    real_arr_type(::Type{TA}, dims::Val = Val(N)) where {TA<:AbstractArray}
 
 returns the same array type but using `(real(eltype()))` as the element type
 # Arguments
 + `TA`:     The array type to convert to an eltype of `real(eltype(TA))`
-+ `dims`:   The number of dimensions of the returned array type
++ `dims`:   The (optional) number of dimensions of the returned array type, default is Val(N) or Val(1) depending on whether the dimensions of the array are inferrable
 
 # Example
 ```jldoctest
@@ -16,26 +16,26 @@ Vector{Float64} (alias for Array{Float64, 1})
 julia> real_arr_type(Array{ComplexF64,3})
 Array{Float64, 3}
 
-julia> real_arr_type(Array{ComplexF64,3}, dims=4)
+julia> real_arr_type(Array{ComplexF64,3}, dims=Val(4))
 Array{Float64, 4}
 ```
 """
-function real_arr_type(::Type{TA}; dims=N) where {T,N, TA<:AbstractArray{T,N}}
-    similar_arr_type(TA, dtype=real(eltype(TA)), dims=dims)
+function real_arr_type(::Type{TA}, dims::Val=Val(N)) where {T,N, TA<:AbstractArray{T,N}}
+    similar_arr_type(TA, real(eltype(TA)), dims)
 end
 
-function real_arr_type(::Type{TA}; dims=1) where {TA<:AbstractArray}
-    similar_arr_type(TA, dtype=real(eltype(TA)), dims=dims)
+function real_arr_type(::Type{TA}, dims::Val=Val(1)) where {TA<:AbstractArray}
+    similar_arr_type(TA, real(eltype(TA)), dims)
 end
 
 """
-    complex_arr_type(::Type{TA}) where {TA<:AbstractArray}
+    complex_arr_type(::Type{TA}, dims::Val = VLa(N)) where {TA<:AbstractArray}
 
-returns the same array type but using `(complex(eltype()))` as the element type
+returns the same array type but using `(complex(eltype()))` as the element type, default is Val(N) or Val(1) depending on whether the dimensions of the array are inferrable
 
 # Arguments
 + `TA`:     The array type to convert to an eltype of `complex(eltype(TA))`
-+ `dims`:   The number of dimensions of the returned array type
++ `dims`:   The (optional) number of dimensions of the returned array type
 
 # Example
 ```jldoctest
@@ -45,28 +45,28 @@ Vector{ComplexF32} (alias for Array{Complex{Float32}, 1})
 julia> complex_arr_type(Array{Float32,3})
 Array{ComplexF32, 3}
 
-julia> complex_arr_type(Array{Float32,3},dims=1)
+julia> complex_arr_type(Array{Float32,3}, Val(1))
 Vector{ComplexF32} (alias for Array{Complex{Float32}, 1})
 ```
 """
-function complex_arr_type(::Type{TA}; dims=N) where {T,N, TA<:AbstractArray{T,N}}
-    similar_arr_type(TA, dtype=complex(eltype(TA)), dims=dims)
+function complex_arr_type(::Type{TA}, dims::Val=Val(N)) where {T,N, TA<:AbstractArray{T,N}}
+    similar_arr_type(TA, complex(eltype(TA)), dims)
 end
 
-function complex_arr_type(::Type{TA}; dims=1) where {TA<:AbstractArray}
-    similar_arr_type(TA, dtype=complex(eltype(TA)), dims=dims)
+function complex_arr_type(::Type{TA}, dims::Val=Val(1)) where {TA<:AbstractArray}
+    similar_arr_type(TA, complex(eltype(TA)), dims)
 end
 
 
 """
-    similar_arr_type(::Type{TA}) where {TA<:AbstractArray}
+    similar_arr_type(::Type{TA}, , T2::Type=Type{T}, N2::Val=Val(N)) where {TA<:AbstractArray}
 
 returns a similar array type but using as TA, but eltype and ndims can be changed.
 
 # Arguments
 + `TA`:     The array type to convert to an eltype of `complex(eltype(TA))`
-+ `dims`:   The number of dimensions of the returned array type
-+ `dtype`:  The `eltype()` of the returned array type.
++ `T2`:  The `eltype()` of the returned array type. Use `eltype(TA)` to keep the same type. Default is `eltype(TA)`.
++ `N2`:   The number of dimensions of the returned array type. Please specify this as a ::Val type to be type-stable. Default is Val(1).
 
 # Example
 
@@ -77,14 +77,28 @@ Vector{ComplexF64} (alias for Array{Complex{Float64}, 1})
 julia> similar_arr_type(Array{ComplexF64,3})
 Array{ComplexF64, 3}
 
-julia> similar_arr_type(Array{ComplexF64,3}, dims=2, dtype=Int)
+julia> similar_arr_type(Array{ComplexF64,3}, Int, Val(2))
 Matrix{Int64} (alias for Array{Int64, 2})
 ```
 """
-function similar_arr_type(::Type{TA}; dims=N, dtype=T) where {T,N, TA<:AbstractArray{T,N}}
-    typeof(similar(TA(undef, ntuple(x->0, N)), dtype, ntuple(x->0, dims)))
+function similar_arr_type(::Type{TA}, T2::Type=Type{T}, N2::Val=Val(N)) where {T, N, TA<:AbstractArray{T,N}}
+    typeof(similar(TA(undef, ntuple(x->0, N)), T2, ntuple(x->0, N2)))
 end
-
-function similar_arr_type(::Type{TA}; dims=1, dtype=eltype(TA)) where {TA<:AbstractArray}
-    typeof(similar(TA(undef), dtype, ntuple(x->0, dims)))
+
+function similar_arr_type(::Type{TA}, T2::Type=Type{T}, N2::Val=Val(N)) where {T, N, P, I, L, TA<:SubArray{T,N,P,I,L}}
+    similar_arr_type(P, T2, N2)
+end
+
+function similar_arr_type(::Type{TA}, T2::Type=Type{T}, N2::Val=Val(N)) where {T, N, P, MI, TA<:Base.ReshapedArray{T,N,P,MI}}
+    similar_arr_type(P, T2, N2)
+end
+
+# note that T refers to the new type (if not explicitely specified) and therefore replaces the eltype of the array as defined by P
+function similar_arr_type(::Type{TA}, T2::Type=Type{T}, N2::Val=Val(N)) where {T, N, O, P, B, TA<:Base.ReinterpretArray{T,N,O,P,B}}
+    similar_arr_type(P, T2, N2)
+end
+
+# specifically for not fully specified arrays
+function similar_arr_type(::Type{TA}, T2::Type=eltype(TA), N2::Val=Val(1)) where {TA<:AbstractArray}
+    typeof(similar(TA(undef), T2, ntuple(x->0, N2)))
 end

test/type_tools.jl

@@ -1,11 +1,15 @@
 @testset "Test Type Tools" begin
     sz = (11,12)
     @test real_arr_type(Array{Float32,2}) == Matrix{Float32}
-    @test complex_arr_type(Array{Float32,1}, dims=2) == Matrix{ComplexF32}
-    @test real_arr_type(Array{Float32}, dims=2) == Matrix{Float32}
-    @test complex_arr_type(Array{Float32}, dims=2) == Matrix{ComplexF32}
-    @test real_arr_type(Array{ComplexF64,2}, dims=1) == Vector{Float64}
+    @test complex_arr_type(Array{Float32,1}, Val(2)) == Matrix{ComplexF32}
+    @test real_arr_type(Array{Float32}, Val(2)) == Matrix{Float32}
+    @test complex_arr_type(Array{Float32}, Val(2)) == Matrix{ComplexF32}
+    @test real_arr_type(Array{ComplexF64,2}, Val(1)) == Vector{Float64}
     @test complex_arr_type(Array{ComplexF64,1}) == Vector{ComplexF64}
-    @test similar_arr_type(Array{ComplexF64,1}, dims=2, dtype=Int) == Matrix{Int}
-    @test similar_arr_type(Array{ComplexF64}, dims=2, dtype=Int) == Matrix{Int}
+
+    @test similar_arr_type(Array{ComplexF64,1}, Int, Val(2)) == Matrix{Int}
+    @test similar_arr_type(Array{ComplexF64}, Float64, Val(2)) == Matrix{Float64}
+    @test similar_arr_type(typeof(view(ones(10,10),2:5,2:5)), Float64, Val(1)) == Vector{Float64}
+    @test similar_arr_type(typeof(reinterpret(Int, ones(10))), Float32, Val(2)) == Matrix{Float32}
+    @test similar_arr_type(typeof(reshape(view(ones(25),1:25), 5,5)), Int, Val(1)) == Vector{Int}
 end