On Tue, Oct 11, 2011 at 6:33 PM, <josef.p...@gmail.com> wrote: > 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 > > Not government, but maybe Lockheed-Martin when they were doing that Mars probe?
"What? It was negative? Well, that explains why it went down, not up!" ::rimshot:: Thank you folks! I will be here all week! Ben Root
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