Changed struct types for multiple dispatch, still broken

src/NMRInversions.jl

@@ -17,6 +17,10 @@ to do list:
 - Move the makie gui to extension
 - rename svd function to create_kernel, and make it more user friendly
 - add L curve method 
+- change multiple dispatch, from ::inversion1D to ::Type{inversion1D}, and use the stuct as input instead of defining variable with struct name
+abstract type A end
+struct a <: A end
+foo(a::Type{<:A})
 
 """
 
@@ -29,15 +33,16 @@ customtypes = Dict(
     :PFG => :inversion1D,
     :IRCPMG => :inversion2D
 )
-struct inversion1D end
-struct inversion2D end
+
+abstract type inversion1D end
+abstract type inversion2D end
 export inversion1D, inversion2D
 
-for (v, t) in customtypes
+for (a, A) in customtypes
     eval(
         quote
-            $v = $t()
-            export $v
+            struct $a <: $A end
+            export $a
         end
     )
 end

src/inversions_1D.jl

@@ -7,7 +7,7 @@ struct invres1D
     alpha::Real
 end
 
-function invert(exptype::inversion1D, file::String=pick_file(pwd()); kwargs...)
+function invert(exptype::Type{<:inversion1D}, file::String=pick_file(pwd()); kwargs...)
 
     csvmatrix = readdlm(file, ',')
     x = csvmatrix[:, 1]
@@ -36,13 +36,13 @@ function invert(exptype::inversion1D, file::String=pick_file(pwd()); kwargs...)
 end
 
 
-function invert(exptype::inversion1D, x::AbstractArray, y::Vector{<:Complex}; varargs...)
+function invert(exptype::Type{<:inversion1D}, x::AbstractArray, y::Vector{<:Complex}; varargs...)
 
     invert(exptype, x, y_re; varargs...)
 
 end
 
-function invert(exptype::inversion1D, x::AbstractArray, y::Vector{<:Real};
+function invert(exptype::Type{<:inversion1D}, x::AbstractArray, y::Vector{<:Real};
     lims=(-5, 1, 128),
     α=1, order=0, solver=brd,
     savedata=false, makeplot=false)

src/inversions_2D.jl

@@ -9,15 +9,15 @@ struct invres2D
 end
 
 
-function invert(exptype::inversion2D,directory::String=pick_folder(pwd());kwargs...)
+function invert(exptype::Type{<:inversion2D}, directory::String=pick_folder(pwd()); kwargs...)
 
-    invert(exptype, import_spinsolve(directory)... ;kwargs...)
+    invert(exptype, import_spinsolve(directory)...; kwargs...)
 
 end
 
 
 function invert(
-    exptype::inversion2D, t_direct::AbstractVector, t_indirect::AbstractVector, Raw::AbstractMatrix;
+    exptype::Type{<:inversion2D}, t_direct::AbstractVector, t_indirect::AbstractVector, Raw::AbstractMatrix;
     α=:gcv, rdir=(-5, 1, 100), rindir=(-5, 1, 100),
     solver=brd, aopt=:none, order=0, savedata::Bool=true, plot::Bool=true)
 

src/kernels.jl

@@ -3,7 +3,7 @@ Create a kernel for the inversion of 1D data.
 x is the experiment x axis (time or b factor etc.)
 X is the range for the output x axis (T1, T2, D etc.)
 """
-function create_kernel(exptype::inversion1D, x::Vector, X::Vector=exp10.(range(-5, 1, 100)))
+function create_kernel(exptype::Type{<:inversion1D}, x::Vector, X::Vector=exp10.(range(-5, 1, 100)))
     if exptype == IR
         kernel_eq = (t, T) -> 1 - 2 * exp(-t / T)
     elseif exptype in [CPMG, PFG]
@@ -60,7 +60,7 @@ t_direct is the direct dimension acquisition parameter
 t_indirect is the indirect dimension acquisition parameter
 Raw is the 2D data matrix of complex data
 """
-function create_kernel(exptype::inversion2D, x_direct::AbstractVector, x_indirect::AbstractVector, Data::AbstractMatrix;
+function create_kernel(exptype::Type{<:inversion1D}, x_direct::AbstractVector, x_indirect::AbstractVector, Data::AbstractMatrix;
     rdir=(-5, 1, 100), rindir=(-5, 1, 100))
 
     G = real.(Data) 
@@ -106,7 +106,7 @@ end
 
 
 
-function create_kernel_svd(exptype::inversion1D, t::AbstractVector, g::AbstractVector; rdir=(-5, 1, 100))
+function create_kernel_svd(exptype::Type{<:inversion1D}, t::AbstractVector, g::AbstractVector; rdir=(-5, 1, 100))
 
     if exptype == IR
         kernel_eq = (t, T) -> 1 - 2 * exp(-t / T)