Thanks for the comments Ralf! > You cannot switch the default behavior, that will break backwards > compatibility.
The default `kind=None` have no effect on input/output behavior of the function. The only changes a user will see are in terms of speed and memory usage. `unique` will select this new algorithm `"table"` only if it is available (integral array, no axis specified, return_index and return_inverse set to False) and the required memory allocation is not too big (which is arbitrarily defined as six times the allocation of the input array - similar to what the sorting method use). Using `kind="table"` won't affect the input/output either, but it is only available for certain arrays (somewhat similar to the usage of `assume_unique` for `np.isin`). Does this sound fine to you? > Regarding the name, `'table'` is an implementation detail. The end user > should not have to care what the data structure is that is used. I suggest to > use something like "unsorted" and just explain it as the ordering of results > being undefined, which can give significant performance benefits. The names `'table'` and `'sort'` were selected for consistency as these names were recently put in place for `np.isin` and `np.in1d`, and the analogous methods used for `unique` are conceptually similar. I have no particular attachment to either name though. Thanks again! Miles _______________________________________________ NumPy-Discussion mailing list -- numpy-discussion@python.org To unsubscribe send an email to numpy-discussion-le...@python.org https://mail.python.org/mailman3/lists/numpy-discussion.python.org/ Member address: arch...@mail-archive.com
