I am an admirer of the numpy doc string style. I'd like to propose a simple
enhancement to the Returns section that should make the common case more
readable, while maintaining backward compatibility with existing
documentation.
The current numpy documentation spec [1] requires that return values
*Announcement*
MDArray version 0.5.3 has Just been released. MDArray is a multi
dimensional array implemented for JRuby inspired by NumPy (www.numpy.org)
and Masahiro Tanaka´s Narray (narray.rubyforge.org). MDArray stands on the
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On Wed, Jun 19, 2013 at 7:48 AM, Charles R Harris wrote:
>
>
> On Wed, Jun 19, 2013 at 5:45 AM, Matthew Brett wrote:
>
>> Hi,
>>
>> On Wed, Jun 19, 2013 at 1:43 AM, Frédéric Bastien
>> wrote:
>> > Hi,
>> >
>> >
>> > On Mon, Jun 17, 2013 at 5:03 PM, Julian Taylor
>> > wrote:
>> >>
>> >> On 17.06
On 21 June 2013 19:57, Charles R Harris wrote:
> You could check the numpy/core/src/umath/test_rational.c.src code to see if
> you are missing something.
My code is based in large part on exactly those examples (I don't
think I could have got this far using the documentation alone!), but
I've rec
Hi list,
i want to calculate the least squares fit of some data with
missing values. So i masked all values using numpys masked array
module.
Unfortunately using linalg.lstsq i only get nan data back. Can
somebody help me solve this problem?
The output of np.linalg.lstsq ist:
(masked_array(data
Hello All,
I am pleased to announce the latest version of xdress, in preparation for
SciPy 2013. For more information please visit the website:
http://xdress.org
Be Well
Anthony
XDress 0.2 Release Notes
XDress is an automatic wrapper generator f
