Hi Stéfan, I ran into a problem:
>>> min_typecode( (18446744073709551615L,) ) # ok <type 'numpy.uint64'> >>> min_typecode( (0, 18446744073709551615L,) ) # ? Traceback (most recent call last): ... ValueError: Can only handle integer arrays. It seems that np.asarray converts the input sequence into a float64 array in the second case (same behaviour with np.array). Anyone knows the reason behind? python 2.7.4 win32 numpy 1.7.1 Gregorio 2013/9/4 Gregorio Bastardo <[email protected]>: > @Stéfan: the 'np.all' calls are now unnecessary on line 26 > > @Stéfan, Robert: Is it worth to bring this solution into numpy? I mean > it's probably not a rare problem, and now users have to bring this > snippet into their codebase. > > Gregorio > > 2013/9/3 Stéfan van der Walt <[email protected]>: >> On Tue, Sep 3, 2013 at 2:47 PM, Robert Kern <[email protected]> wrote: >>>> Here's one way of doing it: https://gist.github.com/stefanv/6413742 >>> >>> You can probably reduce the amount of work by only comparing a.min() and >>> a.max() instead of the whole array. >> >> Thanks, fixed. >> >> Stéfan >> _______________________________________________ >> NumPy-Discussion mailing list >> [email protected] >> http://mail.scipy.org/mailman/listinfo/numpy-discussion _______________________________________________ NumPy-Discussion mailing list [email protected] http://mail.scipy.org/mailman/listinfo/numpy-discussion
