On Fri, Aug 2, 2024 at 1:28 AM Andrew Nelson wrote:
> When using the new `Generator`s for stochastic optimisation I sometimes
> find myself possessing a great solution, but am wondering what path the
> random number generation took to get to that point.
>
> I know that I can get the current state
On Fri, Aug 2, 2024 at 9:37 AM Robert Kern wrote:
> On Fri, Aug 2, 2024 at 1:28 AM Andrew Nelson wrote:
>
>> When using the new `Generator`s for stochastic optimisation I sometimes
>> find myself possessing a great solution, but am wondering what path the
>> random number generation took to get
The next NumPy Optimization Team meeting will be held this Monday, August
5th at 5 pm UTC.
Join us via Zoom:
https://numfocus-org.zoom.us/j/81261288210?pwd=iwV99tGSjR61RTGEERKM4QKxe46g1n.1
.
Everyone is welcome and encouraged to attend.
To add to the meeting agenda the topics you’d like to discuss,
If you missed the NumPy 2.0 birds-of-a-feather session at SciPy 2024, here
is your lucky second chance!
Join an AMA with Nathan Goldbaum, a NumPy maintainer from Quansight Labs,
hosted by OpenTeams to discuss the team’s work on NumPy 2.0 and future
direction of the project. This is also an opportu
>
>
>>
>> - the seed/SeedSequence that was used to construct the BitGenerator
>>
>
> >>> rng = np.random.default_rng()
> >>> rng.bit_generator.seed_seq
> SeedSequence(
> entropy=186013007116029215180532390504704448637,
> )
>
> In some older versions of numpy, the attribute was semi-private as
>
