On Tue, 2013-07-09 at 15:14 +0200, Stéfan van der Walt wrote: > On Tue, Jul 9, 2013 at 2:55 PM, Chao YUE <chaoyue...@gmail.com> wrote: > > I am using 1.7.1 version of numpy and np.ma.argmax is not repecting the > > mask? > > > > In [96]: d3 > > Out[96]: > > masked_array(data = > > [[-- -- -- -- 4] > > [5 -- 7 8 9]], > > mask = > > [[ True True True True False] > > [False True False False False]], > > fill_value = 6) > > > > > > In [97]: np.ma.argmax(d3,axis=0) > > Out[97]: array([1, 0, 1, 1, 1]) > > This is the result I would expect. If both values are masked, the > fill value is used, so there is always an argmin value. >
To be honest, I would expect the exact opposite. If there is no value, there is no minimum argument -> either its an error, or it signals invalid in some other way. On masked arrays I would expect it to be masked to signal this. The error for nanargmax is annoying, but it is right to be an error IMO, due to lack of a better representation. (Ideally mabe the user would be given the option to pass an Identity element for those nanfuncs (basically this is always NaN now, which fails for argmax since the result is integer) for which the ufunc does not have an Identity, and for those that do, we should actually use it. - Sebastian > The following workaround should have done the trick, but it exposes a > different bug: > > x = np.ma.array([[0,1,2,3,4],[5,6,7,8, 9]], mask=[[1, 1, 1, 1, 0], [0, > 1, 0, 0 ,0]], dtype=float) > np.nanargmax(x.filled(np.nan), axis=0) > > This breaks with "ValueError: cannot convert float NaN to integer" > > Stéfan > _______________________________________________ > 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
