Unfortunately, I don’t have a good answer.
For now, I can only tell you what I think might benefit from improvement.
1. Verbosity. I appreciate that bracket syntax such as one in julia or matlab
`[A B C ...]` is not possible, so functional is the only option. E.g. julia has
functions named ‘cat
On Sat, Aug 19, 2023 at 10:49 AM Kevin Sheppard
wrote:
> The easiest way to do this would to to write a pure python implementation
> using Python ints of a masked integer sampler. This way you could draw
> unsigned integers and then treat this as a bit pool. You would than take
> the number of
The easiest way to do this would to to write a pure python implementation
using Python ints of a masked integer sampler. This way you could draw
unsigned integers and then treat this as a bit pool. You would than take
the number of bits needed for your integer, transform these to be a Python
int,
How can we use numpy's random `integers` function to get uniformly selected
integers from an arbitrarily large `high` limit? This is important when dealing
with exact probabilities in combinatorially large solution spaces.
I propose that we add the capability for `integers` to construct arrays
I think ultimately the copy is unnecessary.
That being said introducing prepend and append functions concentrates the
complexity of the mapping in one place. Trying to avoid the extra copy would
probably lead to a more complex implementation of accumulate.
How would in your view the prepend i
Note that this is independent from the memory waste. There are way worse
memory ops in NumPy than this so I don't think that argument applies here
even if it was.
And like I mentioned, this is a very common operation hence internals are
secondary. But it is not an unnecessary copy of the array any
