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Ref: https://pybispectra.readthedocs.io/1.3/auto_examples/plot_compute_pac.html While running the first example, I see the region
Code snippetpac_results_full = pac.results.get_results(copy=False)
vmin = np.nanmin(pac_results_full)
vmax = np.nanmax(pac_results_full)
fig, axes = pac.results.plot(f1s=(0, 20), f2s=(20, 100), cbar_range=(vmin, vmax)) |
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Replies: 1 comment
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Hi @bkowshik, thanks for your question. I wouldn't read into this much beyond it being a by-product of how the data was simulated. If you look at the PSD of the data, you can see the 10 Hz peak in activity at channel x, and the 60 Hz peak with ±10 Hz lobes in channel y. The 60+10 Hz lobe gives the 10-60 Hz PAC which is expected. However, the strength of the 60-10 Hz lobe also means that, for this simulation, there is also 10-50 Hz PAC present. |
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Hi @bkowshik, thanks for your question. I wouldn't read into this much beyond it being a by-product of how the data was simulated.
If you look at the PSD of the data, you can see the 10 Hz peak in activity at channel x, and the 60 Hz peak with ±10 Hz lobes in channel y. The 60+10 Hz lobe gives the 10-60 Hz PAC which is expected. However, the strength of the 60-10 Hz lobe also means that, for this simulation, there is also 10-50 Hz PAC present.