Chris Colbert wrote: > what machine spec are you using? Dual 2Ghz PPC OS-X 10.4. Python2.5, numpy 1.3.0rc1 (hmm -- I should upgrade that!)
> Using your last function line2array5 WITH float conversion, i get the > following timing on a mobile quad core extreme: > > In [24]: a = np.arange(100).astype(str).tostring() > > In [25]: a > Out[25]: > '0123456789111111111122222222223333333333444444444455555555556666666666777777777788888888889999999999' > > In [26]: %timeit line2array(a, 1) > 10000 loops, best of 3: 37.1 µs per loop > > In [27]: a = np.arange(1000).astype(str).tostring() > > In [28]: %timeit line2array(a, 10) > 10000 loops, best of 3: 45.2 µs per loop and I get, timing it the same way (I forgot about ipython's timeit!): In [83]: %timeit line2array5(a, 1) 10000 loops, best of 3: 125 µs per loop In [84]: a = np.arange(1000).astype(str).tostring() In [85]: %timeit line2array5(a, 1) 1000 loops, best of 3: 1.09 ms per loop similar to yours, but longer with an older machine. I wonder why my other timings came out the way they did? -Chris -- Christopher Barker, Ph.D. Oceanographer Emergency Response Division NOAA/NOS/OR&R (206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception [email protected] _______________________________________________ NumPy-Discussion mailing list [email protected] http://mail.scipy.org/mailman/listinfo/numpy-discussion
