I'm seeing about a factor of 50 difference in performance between
sorting a random integer array versus sorting that same array viewed
as a structured array. Am I doing anything wrong here?
In [2]: x = np.random.randint(10000, size=10000)
In [3]: xarr = x.view(dtype=[('a', np.int)])
In [4]: timeit np.sort(x)
1000 loops, best of 3: 588 us per loop
In [5]: timeit np.sort(xarr)
10 loops, best of 3: 29 ms per loop
In [6]: timeit np.sort(xarr, order=('a',))
10 loops, best of 3: 28.9 ms per loop
I was wondering if this slowdown is expected (maybe the comparison is
dropping back to pure Python or ??). I'm showing a simple example
here, but in reality I'm working with non-trivial structured arrays
where I might want to sort on multiple columns.
Does anyone have suggestions for speeding things up, or have a sort
implementation (perhaps Cython) that has better performance for
structured arrays?
Thanks,
Tom
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