Fix NumPy deprecation of setting np.int16 with out-of-bound value

[dhomeier]

Description

This pull request is to address deprecation in NumPy 1.24 of implicit casting of np.int types with out-of-bond numbers (thus forcing an overflow); replacing this with an explicit np.array(a).astype(np.int16)

Fixes #13834

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[github-actions]

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[mhvk]

I think it has been pure luck that this test worked -- that it wrapped around automatically. I think we should just be explicit and write n[1] = 60000 - 65536

[dhomeier]

But by construction fits.Column is setting it with a int16 that is declared to be interpreted as uint16, so would make sense to create it this way. Or perhaps a bit more explicitly
np.array([1, 60000, 0], dtype=np.uint16).astype(np.int16)

[mhvk]

OK, that's true. Maybe use your more explicit route?

[mhvk]

Don't want to hold up this nice fix for no reason, so let me approve. If you have the oomph to add the dtype='u2', then please do, otherwise also fine to just merge.

[mhvk]

Thanks!

[saimn]

Thanks!