On 13 Mar 2024, at 6:01 PM, Dom Grigonis wrote:
So my array sizes in this case are 3e8. Thus, 32bit ints would be needed. So it
is not a solution for this case.
Nevertheless, such concept would still be worthwhile for cases where integers
are say max 256bits (or unlimited), then even if memory
> On 16 Feb 2024, at 2:48 am, Marten van Kerkwijk
> wrote:
>
>> In [45]: %timeit np.add.reduce(a, axis=None)
>> 42.8 µs ± 2.44 µs per loop (mean ± std. dev. of 7 runs, 10,000 loops each)
>>
>> In [43]: %timeit dotsum(a)
>> 26.1 µs ± 718 ns per loop (mean ± std. dev. of 7 runs, 10,000 loops ea
On 11 Aug 2023, at 7:52 pm, Robert Kern
mailto:robert.k...@gmail.com>> wrote:
>>> np.cumsum([[1, 2, 3], [4, 5, 6]])
array([ 1, 3, 6, 10, 15, 21])
```
which matches your example in the cumsum0() documentation. Did something change
in a recent release?
That's not what's in his example.
The exa
On 22 Jan 2023, at 10:40 am, Samuel Dupree
mailto:sdup...@speakeasy.net>> wrote:
I believe I know what is going on, but I don't understand why.
The line for the first derivative that failed to coincide with the points in
the plot for the cosine is actually the interpolated first derivative sca
