[Numpy-discussion] nanmean(), nanstd() and other "missing" functions for 1.8

Charles R Harris charlesr.harris at gmail.com
Thu May 2 10:28:58 EDT 2013


On Thu, May 2, 2013 at 7:47 AM, Robert Kern <robert.kern at gmail.com> wrote:

> On Thu, May 2, 2013 at 2:38 PM, Charles R Harris
> <charlesr.harris at gmail.com> wrote:
> >
> > On Thu, May 2, 2013 at 7:28 AM, Robert Kern <robert.kern at gmail.com>
> wrote:
> >>
> >> On Thu, May 2, 2013 at 12:03 PM, Nathaniel Smith <njs at pobox.com> wrote:
> >> > On 1 May 2013 23:12, "Charles R Harris" <charlesr.harris at gmail.com>
> >> > wrote:
> >> >>
> >> >> On Wed, May 1, 2013 at 7:10 PM, Benjamin Root <ben.root at 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.
> >>
> >> It couldn't be a mere reshape, since the complex dtype requires the
> >> real and imag components to be adjacent to each other. They wouldn't
> >> be so if sincos's return type is an array (nor even the cossin
> >> alternative). It always requires a memory copy (except in the "who
> >> cares?" case of a scalar). Composition with an efficient
> >> np.tocomplex(real, imag) implementation would cover those use cases
> >> whether sincos returns tuples or arrays.
> >
> > I would assume the basic return type would be complex, i.e., the cos/sin
> > adjacent. The cos/sin parts would then be real/imag views into the array.
>
> You mean that the implementation of cossin (to make things easier on
> ourselves) would create an (N,2) contiguous array, fill it with the
> cos and sin results, then reshape it to return the expected (2,N)
>

Just return the transpose.

Chuck
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mail.python.org/pipermail/numpy-discussion/attachments/20130502/eaeb4b30/attachment.html>


More information about the NumPy-Discussion mailing list