@seberg @pv I was under the impression this was pretty much done for 1.13. Is that the case?

It's done for (g)ufuncs (and thus also for in-place binops and most of numpy.linalg), and dot. There however may still be some problematic code paths in other operations, such as in indexed assignment. I did not make an exhaustive check on what's left.

It is true, it might be only smaller things left, had not thought about it much (in general things with an out argument are in danger that are not a ufunc):

• copyto (should be identical to non-advanced indexing assignments)
• median/percentile (use _ureduce python function which could possible get the treatment)
• np.choose seems to have an out argument, so in principel can overlap.
• np.take can overlap with out
• The weird indexing likes (which I would avoid personally but...) put, putmask, place.
• np.around
• (possibly apply_(along|over)_axis)
• and probably a few more, looked around a bit but not very systematically

Reviewing this as part of my 10 random issues, as requested in a 3/20/19 request.

I am 95% sure this is done and just forgotten to be closed, because in 2019 I have seen these overlap checks in the assignment code, including in code involving assignment to slices of an array.

I'm going to go ahead and close this, please reopen if that's wrong.

Is this really safe to close? Has anyone checked the list above?

I think the only unresolved case is when an array has overlap due to striding tricks. PR #12609 tries to make arrays with 0 strides read-only, in response to issue #2705.

But specifically - has someone gone through that list above and checked whether they are resolved or not? It seems to me that this issue should stay open until someone has done that.

I'll go through it now...

Indexing assignments do use it, advanced indexing does not. I doubt a lot of the other functions I listed above never got treatment.

These seem OK:

• copyto is OK since it goes through PyArray_AssignArray, which has an overlap check.
• _ureduce code (eg, median/percentile) looks OK since it is pure python and delegates to ufuncs
• around is ok because it delegates to ufuncs

Problematic:

• np.take There is no overlap detection. Demonstration: np.take(x, [1,2,3], out=x[2:5], mode='wrap') -> array([1., 1., 1.]).
• np.choose no overlap detection. Demonstration: np.choose([0,0,0], [x[:3], x[:3], x[:3]], out=x[1:4], mode='wrap') -> array([1, 1, 1])
• I didn't carefully check, but I expect put and others in that file are the same.

Note that for both of these, with mode='raise', which is the default, a copy of out is always made to avoid clobbering out if an error occurs during processing, so there will be no risk of overlap. (incidentally, this seems unexpectedly inefficient for most people!).

So if we think those last ones should be fixed, we should keep this open.

Closing, #13182 covered the last outstanding cases. Please reopen if I misunderstood