Hi All, I was using numpy's `any` function earlier and realized that it might not be as performant as I assumed. See the code below: ``` In [1]: import numpy as np
In [2]: a = np.zeros(1_000_000) In [3]: a[100] = 1 In [4]: b = np.zeros(2_000_000) In [5]: b[100] = 1 In [6]: %timeit np.any(a) 1.33 ms ± 15.1 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each) In [7]: %timeit np.any(b) 2.65 ms ± 71.1 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) In [8] %timeit any(a) 13.4 µs ± 354 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each) In [9]: %timeit any(b) 13.3 µs ± 219 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each) ``` It looks like `np.any` does not terminate early as soon as it finds a non-zero element, compared to the built-in any function. So this prompted me to go look at the source code for `PyArray_Any`: https://github.com/numpy/numpy/blob/623bc1fae1d47df24e7f1e29321d0c0ba2771ce0/numpy/core/src/multiarray/calculation.c#L790 . Taking a peek at the `PyArray_GenericReduceFunction` it looks like it just calls the `reduce` function from python on every single element of the array and there is no mechanism in place to short-circuit the call if an element has been found early. It seems worthwhile to have a specific function that allows early stopping of the reduction? So my question is: Is there a reason why maintainers did not implement such a feature? I would also like to know if everyone thinks its worthwhile to implement one? Im guessing there are many unsuspecting users like myself who call the `np.any` function on arrays assuming early-stopping is supported. I think existing code that calls the function would benefit a lot. Let me know what you think. Regards -- Sent from: http://numpy-discussion.10968.n7.nabble.com/ _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion
