One of the most discussed and commented issues in the recent history of
NumPy is about to be closed. Don’t forget to cast your vote via reaction on
the new NumPy logo design by this Friday, June 26th.
Here are the three candidates:
https://github.com/numpy/numpy.org/issues/326
https://github.com/nu
norm='forward' is my preference out of the names suggested so far. The
option seems reasonable and should be pretty low maintenance to add.
For SciPy, we would probably be willing to make the corresponding changes
in the scipy.fft module (but probably not in the outdated scipy.fftpack
module).
O
On Wed, Jun 24, 2020 at 3:31 PM Neal Becker wrote:
> Consider the following:
>
> from numpy.random import default_rng
> rs = default_rng()
>
> Now how do I re-seed the generator?
> I thought perhaps rs.bit_generator.seed(), but there is no such attribute.
>
In general, reseeding an existing gene
Hello members of Numpy Community
My name is Christian Takashi Nakata
Currently, I'm working with computer vision in my master's degree and your
project ideas for the GSoD caught my attention.
I've always wanted to work on open source projects, especially in libraries
that I usually use.
I would l
Just call
rs = default_rng()
Again.
On Wed, Jun 24, 2020, 20:31 Neal Becker wrote:
> Consider the following:
>
> from numpy.random import default_rng
> rs = default_rng()
>
> Now how do I re-seed the generator?
> I thought perhaps rs.bit_generator.seed(), but there is no such attribute.
>
>
Consider the following:
from numpy.random import default_rng
rs = default_rng()
Now how do I re-seed the generator?
I thought perhaps rs.bit_generator.seed(), but there is no such attribute.
Thanks,
Neal
--
*Those who don't understand recursion are doomed to repeat it*
I think it's also important to get the thoughts of the SciPy community on
this topic so that we avoid divergence between numpy.fft and scipy.fft. I
would recommend sending this discussion to the scipy mailing list as well.
~Ross
On Tue, Jun 23, 2020 at 4:11 PM Feng Yu wrote:
> Your approach sou
randomgen 1.19.0 has been released with bug fixes and new features.
*New Features*
- A helper class that lets users define custom bit generators in Python
(slow) or numba (fast). This simplifies experimenting with alternative
configurations. The UserBitGenerator can be used with
numpy
