On Wed, Dec 2, 2009 at 7:15 PM, Neal Becker <[email protected]> wrote: > Neal Becker wrote: > >> Keith Goodman wrote: >> ... >>> Oh, I thought he meant there was a numpy function for partial > sorting. >>> >> Actually, I do use this myself. My code is a boost::python wrapper > or >> the std::partial_sum using pyublas. Here's the main pieces: >> >> template<typename out_t, typename in_t> >> inline out_t partial_sum (in_t const& in) { >> out_t out (boost::size (in)); >> std::partial_sum (boost::begin (in), boost::end (in), boost::begin >> (out)); >> return out; >> } >> ... >> def ("partial_sum", >> > &partial_sum<pyublas::numpy_vector<T>,pyublas::numpy_strided_vector<T> >>>); > > Oops, sorry, that's the wrong one (that was partial_sum, not > partial_sort). I don't have a wrapper for that one, but it would > probably be easy enough to do with the same tools as above.
Is a partial sum a cumsum? How does the speed of your code above compare to numpy's cumsum? >> y = np.random.rand(250000) >> timeit y.cumsum() 1000 loops, best of 3: 1.05 ms per loop _______________________________________________ NumPy-Discussion mailing list [email protected] http://mail.scipy.org/mailman/listinfo/numpy-discussion
