On 06/25/2011 09:09 AM, Benjamin Root wrote: > > > On Sat, Jun 25, 2011 at 1:57 PM, Nathaniel Smith <n...@pobox.com > <mailto:n...@pobox.com>> wrote: > > On Sat, Jun 25, 2011 at 11:50 AM, Eric Firing <efir...@hawaii.edu > <mailto: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 <mailto: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 > <http://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 <http://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... > > > Actually, no... I should have tested this before replying earlier: > > >>> a = np.ma.array([2, 4], mask=[True, True]) > >>> a > masked_array(data = [-- --], > mask = [ True True], > fill_value = 999999) > > >>> a.sum() > masked > >>> a = np.ma.array([], mask=[]) > >>> a > >>> a > masked_array(data = [], > mask = [], > fill_value = 1e+20) > >>> a.sum() > masked > > They are the same. > > > Anyway, the general point is that in R, NA's propagate, and in > numpy.ma <http://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 > > > If you want NaN behavior, then use NaNs. If you want masked behavior, > then use masks.
But I think that where Mark is heading is towards infrastructure that makes it easy and efficient to do either, as needed, case by case, line by line, for any dtype--not just floats. If he can succeed, that helps all of us. This doesn't have to be "R versus masked arrays", or beginners versus experienced programmers. Eric > > 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
