How to find the FFT of an unevenly sampled signal in python3?

Question

I have a data with unevenly spaced (time) samples. How can I find the FFT of the signal and plot it.

Actually would you mind sharing what you try to accomplish, then a more targetted answer could be proposed. — Peter Tillemans, Jun 17 '16 at 15:27
[here](https://stackoverflow.com/a/53772921/4999991) I have provided an example using `Scipy.signal.resample`. I hope it helps. — Foad S. Farimani, Dec 14 '18 at 03:16

score 4 · Answer 1 · answered May 14 '20 at 19:34

Apart from the suggested answers, if your goal is find the frequencies (and not have to use FFT for some reason - which I can't infer from your question), you can consider using periodograms; more specifically, the Lomb-Scargle Periodogram - which can yield frequencies corresponding to unevenly spaced data.

Here is a great answer illustrating this suggestion.

score 1 · Answer 2 · edited Apr 13 '17 at 12:47

You can't do an FFT of an unevenly sampled signal. That invalidates the assumptions of the math the FFT is based upon.

You'll have to resample the signal so you have evenly spaced samples.

This is slightly out of scope of this forum, but you can start in the dsp stackexchange

If you want a quick and dirty solution use the following approach :

choose a time delay less than or equal your smallest time between points --> dt or alternatively 20% of the inverse of the maximum frequency you are interested in.
make a buffer with N points with N a power of 2 and N*dt > Tmax - Tmin, or whatever the time window you are interested in.
distribute your points over the 2 closest points, or if you do not mind a bit more 'fuzz' just put it at the nearest point.

You'll end up with a buffer with spikes and zeroes in it, but with the same energy as your original signal.

Now FFT and only use the lowest 20% or so of the frequency lines.

This is an incredibly 'raw' and 'approximative' way of doing things, but it will give some approximation of wiggly power bars over frequency. You can clean the signal up by applying windows.

Note that digital signal processing is a field unto itself. I recommend to explore that rabbithole, but do expect to spent quite some time down there.

score 0 · Answer 3 · answered Jun 17 '16 at 19:56

To use an FFT, you will need to created a vector of samples evenly spaced in time.

If the signal was bandlimited to below a sample rate implied by the widest sample spacings, you can try polynomial interpolation between your unevenly spaced samples to create a grid of about the same number of equally spaced samples in time. But, depending on polynomial degree, this might be highly sensitive to any noise in the bandlimiting or sampling process.

How to find the FFT of an unevenly sampled signal in python3?

3 Answers3