On Mon, Jun 3, 2013 at 6:29 AM, Jerome Kieffer <[email protected]> wrote: > Hello, > > I am giving some introduction tutorials to numpy and we notices a big > difference in speed between nuumpy and math for trigonometric > operations: > > In [3]: %timeit numpy.sin(1) > 100000 loops, best of 3: 2.27 us per loop > > In [4]: %timeit math.sin(1) > 10000000 loops, best of 3: 92.3 ns per loop > > While not surprising, I did not expect numpy to be so much slower (25x)...
It is a known limitation of numpy scalars. As soon as you use array that are not tiny, the speed difference disappears and then favors numpy arrays (around 50 on my own machine, but that's platform specific). David _______________________________________________ NumPy-Discussion mailing list [email protected] http://mail.scipy.org/mailman/listinfo/numpy-discussion
