On Tue, Oct 11, 2011 at 7:13 PM, Benjamin Root <ben.r...@ou.edu> wrote: > On Tue, Oct 11, 2011 at 2:51 PM, Matthew Brett <matthew.br...@gmail.com> > wrote: >> >> Hi >> >> On Tue, Oct 11, 2011 at 3:16 PM, Charles R Harris >> <charlesr.har...@gmail.com> wrote: >> > >> > >> > On Tue, Oct 11, 2011 at 12:23 PM, Matthew Brett >> > <matthew.br...@gmail.com> >> > wrote: >> >> >> >> Hi, >> >> >> >> I recently ran into this: >> >> >> >> In [68]: arr = np.array(-128, np.int8) >> >> >> >> In [69]: arr >> >> Out[69]: array(-128, dtype=int8) >> >> >> >> In [70]: np.abs(arr) >> >> Out[70]: -128 >> >> >> > >> > This has come up for discussion before, but no consensus was ever >> > reached. >> > One solution is for abs to return an unsigned type, but then combining >> > that >> > with signed type of the same number of bits will cause both to be cast >> > to >> > higher precision. IIRC, matlab was said to return +127 as abs(-128), >> > which, >> > if true, is quite curious. >> >> octave-3.2.3:1> a = int8([-128, 127]) >> a = >> >> -128 127 >> >> octave-3.2.3:2> abs(a) >> ans = >> >> 127 127 >> >> Matlab is the same. That is curious... >> >> See you, >> >> Matthew > > Well, it _is_ only off by 0.78%. That should be good enough for government > work, right?
So, which government is using numpy, only off by 200% Josef > > 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
