I only skimmed the transcript. I have two things to add:
1. Two postings by Marshall and Roger:
http://www.jsoftware.com/pipermail/programming/2020-February/054999.html
http://www.jsoftware.com/pipermail/programming/2020-February/055012.html
2. Rank is not, on the whole and for the most part, really about
multidimensional data. Roger's posting betrays this. Rank is about
projecting a 2- or 3-dimensional structure onto multidimensional arrays. The
existence of multidimensional arrays enables multiple such projections; the
partitions of the shape, given only rank, or the partitions of the
permutations of the shape (minus some duplicates), given both rank and
transpose. Transpose _is_ really multidimensional; a rare property among
primitives.
On Sun, 29 May 2022, 'robert therriault' via Programming wrote:
A bit late this week because I was travelling, but here is the most recent ArrayCast episode on Rank and Leading Axis theory.
https://www.arraycast.com/episodes/episode28-rank-and-leading-axis
Cheers, bob
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