Sebastian,
I think the core issue you pointed out is indeed correct, but your detailed
explanation is backwards, since `maximum(arr[:, 0], arr[:, 1])` implements
`arr.max(axis=1)` instead of `arr.max(axis=0)`. So OP's transpose method is
essentially approach 1, which for this array shape has less
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On Fri, 2025-03-21 at 23:22 +0100, Tiziano Zito via NumPy-Discussion
wrote:
> Hi George,
>
> what you see is due to the memory layout of numpy arrays. If you
> switch your array to F-order you'll see that the two functions have
> the same timings, i.e. both are fast (on my machine 25 times faster
Very interesting! Thanks for the quick response!
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