I’ve started to look into wavelet-TFR, and MNE offers
tfr_morlet. But what about other wavelet transformations? After discussion with colleagues, I’d like to try to compute a TFR representation with morlet wavelet + other wavelets at once.
In the case of
tfr_morlet, the function
_compute_tfr creates one wavelet per frequency of interest to account for variable time-window duration, decreasing with frequency (depending on the number of cycles set).
Next step, the wavelets are passed to
_time_frequency_loop as an array of shape
(n_tapers, n_wavelets, n_times) with
n_tapers=1 for wavelet-based TFR.
Next step, the CWT is computed (as a generator used in
With the wavelets
_cwt_gen) provided as a list of wavelets (1D array): one wavelet per frequency of interest. The CWT generator yields the TFR for each epoch
Now, what if I want to have both a morlet wavelet + a daubechies wavelet? (as an example only). I’m stuck at this stage:
- Should I combine both wavelets before CWT? And how?
- Should I compute 2 times the CWT, one with each wavelet, and combine the TFR? And how?
EDIT: Not entirely sure, but it looks like I’m referring to DWT.
I’m waiting for the literature that my colleague will forward me about wavelet representation of EEG data, if it checks out, I could add another TFR function in which you provide a list of wavelets to use (by name probably).