Masked array seems definitely to be the way to go, thanks a lot. I must say that this entire issue doesn't make much sense to me: my understanding is the a NaN is different from an INF, therefore one would assume that really there is no reason why a not-number should not be ignored by default by all the array manipulating functions.
On 6/25/07, Pierre GM <[EMAIL PROTECTED]> wrote: > On Monday 25 June 2007 14:15:20 Giorgio F. Gilestro wrote: > > Thanks. > > Actually those I care the most are average and std. > > Is there a way to know the number of NaN in an array? > > Giorgio, > You could use: > numpy.isnan(x).sum() > > But once again > <push_product> > masked arrays were designed to handle this kind of situation seamlessly. Just > create a masked_array > masked_array(x, mask=isnan(x)) > and use the regular functions/methods on the masked array. > </push_product> > _______________________________________________ > Numpy-discussion mailing list > Numpy-discussion@scipy.org > http://projects.scipy.org/mailman/listinfo/numpy-discussion > _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
