On Mon, Aug 10, 2015 at 1:40 PM, Benjamin Root <ben.r...@ou.edu> wrote:
> > Not really, it is "simply" because ``np.asarray(set([1, 2, 3]))`` > > returns an object array > > Holy crap! To be pedantic, it looks like it turns it into a numpy scalar, > but still! I wouldn't have expected np.asarray() on a set (or dictionary, > for that matter) to work because order is not guaranteed. Is this expected > behavior? > > Digging into the implementation of in1d(), I can see now how passing a > set() wouldn't be useful at all (as an aside, pretty clever algorithm). I > know sets aren't array-like, but the code that used this seemed to work at > first, and this problem wasn't revealed until I created some unit tests to > exercise some possible corner cases. Silently producing possibly erroneous > results is dangerous. Don't know if better documentation or some better > sanity checking would be called for here, though. > > Ben Root > > > On Mon, Aug 10, 2015 at 1:10 PM, Sebastian Berg < > sebast...@sipsolutions.net> wrote: > >> On Mo, 2015-08-10 at 12:09 -0400, Benjamin Root wrote: >> > Just came across this one today: >> > >> > >>> np.in1d([1], set([0, 1, 2]), assume_unique=True) >> > array([ False], dtype=bool) >> > >> > >>> np.in1d([1], [0, 1, 2], assume_unique=True) >> > >> > array([ True], dtype=bool) >> > >> > >> > I am assuming this has something to do with the fact that order is not >> > guaranteed with set() objects? I was kind of hoping that setting >> > "assume_unique=True" would be sufficient to overcome that problem. >> > Should sets be rejected as an error? >> > >> >> Not really, it is "simply" because ``np.asarray(set([1, 2, 3]))`` >> returns an object array and 1 is not the same as ``set([1, 2, 3])``. >> >> I think earlier numpy versions may have had "short cuts" for short lists >> or something so this may have worked in some cases.... >> > is it possible to get at least a UserWarning when creating an object array and dtype object hasn't been explicitly requested or underlying data is already in an object dtype? Josef > >> - Sebastian >> >> >> > >> > This was using v1.9.0 >> > >> > >> > Cheers! >> > >> > Ben Root >> > >> > _______________________________________________ >> > NumPy-Discussion mailing list >> > NumPy-Discussion@scipy.org >> > http://mail.scipy.org/mailman/listinfo/numpy-discussion >> >> >> _______________________________________________ >> NumPy-Discussion mailing list >> NumPy-Discussion@scipy.org >> http://mail.scipy.org/mailman/listinfo/numpy-discussion >> >> > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion > >
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