Robert Kern wrote:
> Ah, it's Travis's fault. So he can fix it.
> :-)
And lo, it was fixed. Amen.
http://projects.scipy.org/scipy/scipy/changeset/2217
--
Robert Kern
"I have come to believe that the whole world is an enigma, a harmless enigma
that is made terrible by our own mad attempt
Lionel Roubeyrie wrote:
> good news, and thanks for your last comment. However, using nans give some
> errors with scipy.stats:
> lionel52>t=array([1,2,nan,4])
>
> lionel53>stats.nanmean(t)
> ---
> exceptions.NameError
Le jeudi 21 septembre 2006 19:01, Travis Oliphant a écrit :
> Lionel Roubeyrie wrote:
> > find any solution for that. I have tried with arrays of dtype=object, but
> > I have problem when I want to compute min, max, ... with an error like:
> > TypeError: function not supported for these types, and
Lionel Roubeyrie wrote:
> find any solution for that. I have tried with arrays of dtype=object, but I
> have problem when I want to compute min, max, ... with an error like:
> TypeError: function not supported for these types, and can't coerce safely to
> supported types.
>
I just added suppor
Lionel Roubeyrie wrote:
> Hi all,
> Is it possible to put masked values into recarrays, I need a array with
> heterogenous types of datas (datetime objects in the first col, all others
> are float) but with missing values in some records. For the moment, I don't
> find any solution for that.
Ei
Hi all,
Is it possible to put masked values into recarrays, I need a array with
heterogenous types of datas (datetime objects in the first col, all others
are float) but with missing values in some records. For the moment, I don't
find any solution for that. I have tried with arrays of dtype=obj
