Fourier Tranforms of irregularly sampled data
Hi all, I want to calculate the periodogram of a series of data that have been measured at irregular intervals i.e. A quantity was measured every ten seconds one day and then maybe every 20 seconds a week later etc. Is there any way to do this easily in scipy? I have an algorithm to do this but it is dreadfully slow since it uses python loops and map(). Any help will be greatly appreciated. -Ewald
Ewald Zietsman wrote:
Hi all,
I want to calculate the periodogram of a series of data that have been measured at irregular intervals i.e. A quantity was measured every ten seconds one day and then maybe every 20 seconds a week later etc.
Is there any way to do this easily in scipy? I have an algorithm to do this but it is dreadfully slow since it uses python loops and map().
The Lomb-Scargle periodogram works fairly well here (Google for references). Numerical Recipes 13.8 describes an implementation that utilizes FFTs in a clever way to do speed up the calculation. http://library.lanl.gov/numerical/bookcpdf/c13-8.pdf If you do implement it, I would love to include it in scipy.signal . -- Robert Kern "I have come to believe that the whole world is an enigma, a harmless enigma that is made terrible by our own mad attempt to interpret it as though it had an underlying truth." -- Umberto Eco
On 8/28/06, Robert Kern <robert.kern@gmail.com> wrote:
Ewald Zietsman wrote:
Hi all,
I want to calculate the periodogram of a series of data that have been measured at irregular intervals i.e. A quantity was measured every ten seconds one day and then maybe every 20 seconds a week later etc.
Is there any way to do this easily in scipy? I have an algorithm to do this but it is dreadfully slow since it uses python loops and map().
The Lomb-Scargle periodogram works fairly well here (Google for references). Numerical Recipes 13.8 describes an implementation that utilizes FFTs in a clever way to do speed up the calculation.
It's also worth mentioning more recent work on the topic, which introduces significant improvements (at the cost of a more difficult implementation): On the Fast Fourier Transform of Functions With Singularities Gregory Beylkin Applied and Computational Harmonic Analysis, 2, pp. 363-381, 1995 http://amath.colorado.edu/pub/wavelets/papers/usfft.pdf Cheers, f
participants (3)
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Ewald Zietsman -
Fernando Perez -
Robert Kern