At 11:55 PM 10/31/2007, Travis wrote: >Ray S wrote: > > I am using > > fftRes = abs(fft.rfft(data_array[end-2**15:end])) > > >At first glance, I would say that I don't expect memory to be growing >here, so it looks like a problem with rfft that deserves looking into.
I saw that Numeric did also (I still use Numeric for smaller array speed) but much more slowly. I will try to repeat with a small demo and post. >Does data_array keep growing? no, it is a 64k circular buffer Which reminds me, I've been wanting to try to build a Numeric circular buffer object; one that, when sliced or assigned to, auto-magically wraps as needed, exposing only an extra pointer attribute for the "end". I currently always do it with Python if-s and pointer vars for these products that only do "real time" data analysis. >From: "Anne Archibald" <[EMAIL PROTECTED]> >If the range is *really* small, you can try using a DFT - sometimes >that is fast enough, and gives you just the bins you're curious about. I've considered weave'ing a simple sine transform with specified range, but until I do and test I won't know if my own implementation is any faster than just the FFTPACK. >If the range is bigger than that, but still a small fraction of the >FFT size, you can do some tricks where you band-pass filter the data >... >There are also "zoom fft" and "chirp-z" techniques which are supposed >to give you only part of the FFT, but the wisdom is that unless you >want less than a few percent of the data points you're better just >FFTing and throwing lots of data away. I've tried zoom before; the issue was just that - 2 FFTs and a shift or convolution eats a lot of CPU cycles and falls behind the real time data. The range of interest in the Fourrier domain is small, 3kHz-7kHz. The sample rate is high for precise phase information. I've got some more testing to do, it seems. Thanks, Ray -- No virus found in this outgoing message. Checked by AVG Free Edition. Version: 7.5.503 / Virus Database: 269.15.15/1101 - Release Date: 10/31/2007 10:06 AM _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
