& fkiraly [MNT] bump numpy version bound to <1.25 and fix compatibility issues #3907

[aquemy]

Fixes #3907

• moves upper bound for numpy to 1.25 (1.24 is out)
• fixes some compatibility issues due to some high precision numbers in doctests (by @fkiraly)

[fkiraly]

why are these failing? Seems like failure from numerical errors? It is numpy related.

[jorenham]

@fkiraly It looks like a classic case of rounding errors
https://github.com/sktime/sktime/actions/runs/3655740138/jobs/6180108575#step:7:470

[fkiraly]

yes, but it did not happen before? What changed?

This produces different values on windows than on unix??

I would suggest to remove the printout from doctest and separately test until some lower amount of significant digits.
Seems to be a numerical accuracy issue.

[aquemy]

I am bumping the upper bound to 1.24 to test is this was not introduced later.

[fkiraly]

yes, looks like 1.23

It also looks like it is only about the printout (number of significant digits printed), my preferred approach would be moving the tests to pytest and testing approximate equality rather than precise equality of the printout.

Would you like to do that? Otherwise I can do that too, it should not take too long.

[aquemy]

I am afraid I will not have time to do it this week so feel free to take over.

[jorenham]

numpy 1.24 was just realeased FYI
https://github.com/numpy/numpy/releases/tag/v1.24.0

[fkiraly]

@jorenham, yes, I was going to fix this and release 0.15.0 with numpy and sklearn compatibilities.

[fkiraly]

FYI @RNKuhns, the compatibility issues came from your old doctests!

Not to blame anyone, just a learning moment for me as well - looks like some numerical routines subtly changed in numpy, and you put a lot of digits after the comma in the expected doctest output.

I fixed that by moving the test out to pytest and increasing the floating point tolerance for an equality check.