For example, here's an illustration of the concept that the average distance between random points in a unit hypercube increases with the number of dimensions:
(+/%#)+/&.:*:?1000 1000$0 18.2652 (+/%#)+/&.:*:?4000 1000$0 36.5102 (+/%#)+/&.:*:?10000 1000$0 57.7314 Thanks, -- Raul On Thu, Nov 14, 2019 at 11:16 AM Raul Miller <[email protected]> wrote: > > I stumbled across this today: > https://github.com/leopd/geometric-intuition accompanied by an > assertion that you can find the eigenvectors for a hermitian matrix > from its eigenvalues and the eigenvalues of its submatrices. I have > not yet worked through the details of that, but it sounds plausible > and might be of interest to some of you, here. > > But the repository itself covers a lot more ground than that. > > Anyways, the code is python, but a lot of it is fairly straightforward > to re-implement, and there's good english descriptions and > illustrations, also. So this looks like fun. > > FYI, > -- > Raul ---------------------------------------------------------------------- For information about J forums see http://www.jsoftware.com/forums.htm
