Hi,
I started venturing down the rabbit hole of trying to write a patch to add
support for numpy to convert python 3 dictionary keys
(collections.abc.ViewMapping objects), which is open issue #5718 and am
having trouble orienting myself. I'm unclear as to where the python entry
point into array is
Thank you Juan, I've just joined GitHub and I've submitted the description
of the bug.
On Tue, Jul 19, 2016 at 2:55 PM, Juan Nunez-Iglesias
wrote:
> https://github.com/numpy/numpy/issues
>
>
> From: John Ladasky
> Reply: Discussion of Numerical Python
>
> Date: 20 July 2016 at 7:49:10 AM
> T
https://github.com/numpy/numpy/issues
From: John Ladasky
Reply: Discussion of Numerical Python
Date: 20 July 2016 at 7:49:10 AM
To: Discussion of Numerical Python
Subject: Re: [Numpy-discussion] Numpy set_printoptions, silent failure,
bug?
Hi Robert,
>
> Thanks for your reply. If no one
Hi Robert,
Thanks for your reply. If no one disagrees with you or with me that this
is a Numpy bug, I would appreciate being directed to the appropriate page
to submit a bug-fix request.
On Tue, Jul 19, 2016 at 2:43 PM, Robert Kern wrote:
> On Tue, Jul 19, 2016 at 10:41 PM, John Ladasky wrot
On Tue, Jul 19, 2016 at 10:41 PM, John Ladasky wrote:
> Should this be considered a Numpy bug, or is there some reason that
set_printoptions would legitimately need to accept a dictionary as a single
argument?
There is no such reason. One could certainly add more validation to the
arguments to n
Hi there,
I've been using Numpy for several years and appreciate it very much.
The following minimal code has been tried on Python 3.4 and 3.5, with Numpy
1.8 and Numpy 1.11, respectively. I want to temporarily change the way
that a Numpy array is printed, then change it back.
import numpy as n
On Fri, Jul 15, 2016 at 3:50 PM, Matti Picus wrote:
> Am I missing something simple? I
> - install git, subversion, gcc, gfortran (Ubuntu 16.04)
> - create a clean python2 virtual env (no numpy)
> - activate it
> - git clone numpy
> - cd into it
> - python runtests.py
> - wait
> And it fails test
On Tue, Jul 19, 2016 at 3:53 PM, Ecem sogancıoglu wrote:
> Hello All,
>
> there seems to be a performance issue with the covariance function in
> numpy 1.9 and later.
>
> Code example:
> *np.cov(np.random.randn(700,37000))*
>
> In numpy 1.8, this line of code requires 4.5755 seconds.
> In numpy 1
Hello All,
there seems to be a performance issue with the covariance function in numpy
1.9 and later.
Code example:
*np.cov(np.random.randn(700,37000))*
In numpy 1.8, this line of code requires 4.5755 seconds.
In numpy 1.9 and later, the same line of code requires more than 30.3709 s
execution t
