update some functions

src/1.JWAS/src/build_MME.jl

@@ -1,14 +1,18 @@
-#return column index for each level of variables in incidence matrix X
-#e.g. "A1"=>1,"A2"=>2
-function mkDict(a)
- aUnique = unique(a)
- d = Dict()
- names = Array{Any}(undef,size(aUnique,1))
- for (i,s) in enumerate(aUnique)
- names[i] = s
- d[s] = i
- end
- return d,names
+"""
+ mkDict(a::Vector{T}) where T <: Any
+
+ Get column index in the incidence matrix for each level of a factor (categorical variable) 
+ input: a=["a1","a4","a1","a2"] 
+ output: d=Dict("a2" => 3, "a1" => 1, "a4" => 2), level_names=["a1","a4","a2"]
+
+ note: enumerate(level_names) gives a list of tuples (index, element), reverse() to reverse (index,element) to (element,index)
+"""
+function mkDict(a::Vector{T}) where T <: Any
+ # Create a vector of unique levels from a
+ level_names = unique(a) #e.g., ["a1","a2","a1"] -> ["a1","a2"]
+ # Create a dictionary mapping each element to its index in level_names
+ d = Dict(map(reverse, enumerate(level_names))) #e.g., Dict("a1"=>1,"a2"=>2), level_names=["a1","a2"]
+ return d, level_names
 end
 
 """

src/1.JWAS/src/markers/tools4genotypes.jl

@@ -1,28 +1,28 @@
-#the function below using pointers is deprecated
-function get_column(X,j)
- nrow,ncol = size(X)
- if j>ncol||j<0
- error("column number is wrong!")
- end
- indx = 1 + (j-1)*nrow
- ptr = pointer(X,indx)
- unsafe_wrap(Array,ptr,nrow) #pointer_to_array(ptr,nrow) #deprected in Julia 0.5
-end
+"""
+ get_column_ref(X::Vector{T})
 
-function get_column_ref(X)
- ncol = size(X)[2]
- xArray = Array{Union{Array{Float64,1},Array{Float32,1}}}(undef,ncol)
- for i=1:ncol
- xArray[i] = get_column(X,i)
- end
- return xArray
+ To obtain a vector of views (alias/pointer) for each column of the input matrix WITHOUT COPYING the underlying data. 
+ input: a matrix X
+ output: a vector containing views of each column of the input matrix X
+"""
+function get_column_ref(X::AbstractArray{T,2}) where T <: Any
+ return [view(X, :, i) for i in 1:size(X, 2)] # Create a vector of views for each column of the matrix X
 end
 
-function center!(X)
- nrow = size(X,1)
- colMeans = mean(X,dims=1)
- BLAS.axpy!(-1,ones(nrow)*colMeans,X)
- return colMeans
+"""
+ This function centers columns of the input matrix X by subtracting their means along each column. The function operates in-place by modifying the original matrix X.
+
+ Input:
+ - X::AbstractMatrix: a matrix to be centered
+
+ Output:
+ - col_means::Vector: a vector of mean values for each column in the original matrix, computed before centering.
+"""
+function center!(X::AbstractArray{T,2}) where T <: Any
+ col_means = mean(X, dims=1) # Calculate the means in each column
+ X .-= col_means # Subtract column means from X, 
+ # Note: in-place, using broadcasting, i.e. X[i,j] -= col_means[j]
+ return col_means # Return a row vector of column means (size 1 by ncol)
 end
 
 function getXpRinvX(X, Rinv)
@@ -39,8 +39,8 @@ mutable struct GibbsMats
  X::Union{Array{Float64,2},Array{Float32,2}}
  nrows::Int64
  ncols::Int64
- xArray::Array{Union{Array{Float64,1},Array{Float32,1}},1}
- xRinvArray::Array{Union{Array{Float64,1},Array{Float32,1}},1}
+ xArray #do not declare type because it is a vector of views
+ xRinvArray #do not declare type because it is a vector of views
  xpRinvx::Union{Array{Float64,1},Array{Float32,1}}
  function GibbsMats(X::Union{Array{Float64,2},Array{Float32,2}},Rinv)
  nrows,ncols = size(X)