I am trying to build a custom iterator for the QuasiMonteCarlo.jl
package.
I did not find an example doing the kind of things I want.
 I need first to generate 3 big matrices
for 1:M

“randomize” in place these matrices

compute something with the result and store the result
end
I don’t know how to build an iterator that store something and then use it at every iteration.
Here is a very simplified version of the problematic
# Iteration 0 > create a matrix
N = d*n
X = reshape(range(0, step = π, length = N) .% 1, d, n)
# Iteration 1:M > do something in place on the matrix
shuffle!(X)
Ideally, once the iterator is defined, application would look like
mean(X for MyIterator(M, args))
From the docs on iterators I cannot figure out, how to store and use an X
in the iterator.
Define a data structure (a struct
) that stores whatever you need, then define an iterate
method for it.
For example, the Sobol.jl package defines a SobolSeq
data structure, and then has an iterate
method for it.
Thanks!
I used your piece of code + that which looks simpler (and maybe more up to date according to docs?).
using Random
struct MyIterator{T <: Real}
X::Matrix{T}
count::Int
end
MyIterator(n::Integer, d::Integer, M::Integer) = MyIterator(reshape(range(0, step = π, length = d*n), d, n).%1, M)
Base.length(s::MyIterator) = s.count
Base.iterate(s::MyIterator{T}, state=1) where {T} = state > s.count ? nothing : (shuffle!(@view(s.X[:,:])), state+1) # view for in place modification of s.X
Base.eltype(::Type{MyIterator{T}}) where {T} = Matrix{T}
# it works
for i in MyIterator(5,2,3) println(i) end
collect(MyIterator(5,2,3))