On Tue, Sep 1, 2015 at 12:06 PM, Oscar Benjamin <[email protected]> wrote:
> > On Tue, 1 Sep 2015 18:43 Phil Hodge <[email protected]> wrote: > > On 09/01/2015 11:14 AM, Oscar Benjamin wrote: > > Just use the next power of 2. Pure powers of 2 are the most efficient > > for FFT algorithms so it potentially works out better than finding a > > smaller but similarly composite size to pad to. Finding the next power > > of 2 is easy to code and never a bad choice. > > It would be better to pad to a power of three or five, or some other > product of small primes, if the pad length would be significantly less > than padding to a power of two. The obvious problem with padding is > that it's different from the real data, so its presence will affect the > result. At the least, it would be good to pad with the mean value of > the original data, or to pad with zero after subtracting the mean from > the original data. > > > > I meant performance wise it's not a bad choice. If you're concerned about > distortion then use the Bluestein algorithm as I showed. > I don't see the problem with padding. After all, the spectrum is an estimate and the effect of the padding, as well as the use of windowing is well understood. However, I would recommend subtracting the average before padding, as otherwise the DC frequency is likely to be of large amplitude and its side lobes will mask the lower frequencies. > -- > Oscar > > > > _______________________________________________ > NumPy-Discussion mailing list > [email protected] > http://mail.scipy.org/mailman/listinfo/numpy-discussion > >
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