Hi, I was trying to sort an array (N, 3) by rows, and firstly come with this solution:
N = 1000000 arr = np.random.randint(-100, 100, size=(N, 3)) dt = np.dtype([('x', int),('y', int),('z', int)]) *arr.view(dtype=dt).sort(axis=0)* Then I found another way using lexsort function *:* *idx = np.lexsort([arr[:, 2], arr[:, 1], arr[:, 0]])* *arr = arr[idx]* Which is 4 times faster than the previous solution. And now i have several questions: Why is the first way so much slower? What is the fastest way in numpy to sort array by rows? Why is the order of keys in lexsort function reversed? The last question was really the root of the problem for me with the lexsort function. And I still can not understand the idea of such an order (the last is the primary), it seems to me confusing. Thank you!!! With kind regards, Kirill. p.s.: One more thing, when i first try to use lexsort. I catch this strange exception: *np.lexsort(arr, axis=1)* ---------------------------------------------------------------------------AxisError Traceback (most recent call last)<ipython-input-278-5162b6ccb8f6> in <module>()----> 1 np.lexsort(ls, axis=1) AxisError: axis 1 is out of bounds for array of dimension 1
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