Hi again,

So out of curiosity, I just spend a couple hours looking for variations of:
"(immutable/persistent) (tensor/multidimentional array/multidimentional 
data structure) implementation"
and my conclusion is that I did not easily find examples of implementations 
of data structures tailored for such specific needs as tensor manipulation. 
It must not be the right way to search for this.

What I found however was many references to Okasaki's work on immutable 
data structures. This question [1] with it's answer provide good starting 
points in my opinion. Okasaki's book seems to focus on how to 
design/implement fuctional data structures so it could give good insights 
for the raw data structure at the base of your ndarray type.

Maybe the first thing to do would be to clearly define all the operations 
you want to have for your ndarray in some document. Then design a data 
structure considering trade-off for all the operations supported. 
Apparently, there is a paper for the numpy arrays listed on scipy website 
[2]. These are not immutable however so I don't know if it is usefull.

In hope that it may help,
Cheers,
Matthieu

[1] interesting question: https://cs.stackexchange.com/a/25953/34063
[2] scipy citations: https://www.scipy.org/citing.html

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