On Wed, Jun 29, 2011 at 2:21 PM, Eric Firing <efir...@hawaii.edu> wrote: > In addition, for new code, the full-blown masked array module may not be > needed. A convenience it adds, however, is the automatic masking of > invalid values: > > In [1]: np.ma.log(-1) > Out[1]: masked > > I'm sure this horrifies some, but there are times and places where it is > a genuine convenience, and preferable to having to use a separate > operation to replace nan or inf with NA or whatever it ends up being.
Err, but what would this even get you? NA, NaN, and Inf basically all behave the same WRT floating point operations anyway, i.e., they all propagate? Is the idea that if ufunc's gain a skipna=True flag, you'd also like to be able to turn it into a skipna_and_nan_and_inf=True flag? -- Nathaniel _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
