On 1 May 2013 23:12, "Charles R Harris" <charlesr.harris@gmail.com> wrote:
On Wed, May 1, 2013 at 7:10 PM, Benjamin Root <ben.root@ou.edu> wrote:
So, to summarize the thread so far:
Consensus: np.nanmean() np.nanstd() np.minmax() np.argminmax()
Vague Consensus: np.sincos()
If the return of sincos (cossin?) is an array, then it could be reshaped
to be exp(1j*x), which together with exp(2*pi*1j*x) would cover some pretty common cases. Ufuncs already have some convention for what to do with multiple output arguments, right? Presumably whatever they do is what sincos should do. (And minmax/argminmax likewise, for consistency, even if they aren't ufuncs. Though they could be generalized ufuncs, or minmax could be minimummaximum.reduce.) I haven't checked, but I assume that what multiple output argument ufuncs do is to return a tuple. You can't use a single array in the general case, because the multiple output types might not be homogenous. -n