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
The function np.where just chooses elements from two arrays that are both
computed before np.where is even executed. See this StackOverflow answer
https://stackoverflow.com/a/29950752/4681187 if you want to suppress the
error.
On Thu, Apr 25, 2024 at 8:16 PM 840362492--- via NumPy-Discussion <
num
man eyes rather than computers, I think this should
not cause too much of a compatibility problem.
What do you all think?
Sincerely,
Fang Zhang
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