On Sat, Jun 25, 2011 at 11:50 AM, Eric Firing <efir...@hawaii.edu> wrote: > On 06/25/2011 07:05 AM, Nathaniel Smith wrote: >> On Sat, Jun 25, 2011 at 9:26 AM, Matthew Brett<matthew.br...@gmail.com> >> wrote: >>> To clarify, you're proposing for: >>> >>> a = np.sum(np.array([np.NA, np.NA]) >>> >>> 1) -> np.NA >>> 2) -> 0.0 >> >> Yes -- and in R you get actually do get NA, while in numpy.ma you >> actually do get 0. I don't think this is a coincidence; I think it's > > No, you don't: > > In [2]: np.ma.array([2, 4], mask=[True, True]).sum() > Out[2]: masked > > In [4]: np.sum(np.ma.array([2, 4], mask=[True, True])) > Out[4]: masked
Huh. So in numpy.ma, sum([10, NA]) and sum([10]) are the same, but sum([NA]) and sum([]) are different? Sounds to me like you should file a bug on numpy.ma... Anyway, the general point is that in R, NA's propagate, and in numpy.ma, masked values are ignored (except, apparently, if all values are masked). Here, I actually checked these: Python: np.ma.array([2, 4], mask=[True, False]).sum() -> 4 R: sum(c(NA, 4)) -> NA -- Nathaniel _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
