Pvals in tort generated signal

[m-bellv]

Hello,

I was interested in comparing how low vs high PAC coupling looks, and so was interested in the included function to generate signals. However, I noticed that even when assigning high values of coupling (chi =0.0), pvalues aren't detected as significant above the permutations, though this isn't true when generating the signal with wavelet.

For instance, using:

f_pha = 6 # frequency phase for the coupling
f_amp = 90 # frequency amplitude for the coupling
n_epochs = 1 # number of trials

sf = 1000. # sampling frequency
n_times = 10*sf # number of time points

data, time = pac_signals_wavelet(f_pha=f_pha, f_amp=f_amp, noise=0.8,
n_epochs=n_epochs, n_times=n_times, sf=sf, pp=0.0)
p = Pac(idpac=(2, 3, 0), f_pha=(2, 29, 1, .2), f_amp=(30, 120, 5, 1))
xpac = p.filterfit(sf, data2, n_perm=n_perm, n_jobs=4, random_state=0 ).squeeze()
xpac_smean = xpac[pval < .05].mean()
p.comodulogram(xpac, title='Modulation Index (MI)', cmap='viridis', vmin=0., pvalues=pval,
levels=.05)

I am able to produce the figure as given in https://etiennecmb.github.io/tensorpac/auto_examples/stats/plot_pvalues.html#sphx-glr-auto-examples-stats-plot-pvalues-py

However, when generating the signal using tort:
data, time = pac_signals_tort(f_pha=f_pha, f_amp=f_amp, sf=sf, n_times=n_times, n_epochs=n_epochs,
chi=0.0, noise=2.4, dpha=0.0, damp=0.0, rnd_state=0)
p = Pac(idpac=(2, 3, 0), f_pha=(2, 29, 1, .2), f_amp=(30, 120, 5, 1))
xpac = p.filterfit(sf, data, n_perm=n_perm, n_jobs=4,
random_state=0).squeeze()

pval = p.infer_pvalues(p=0.05)
xpac_smean = xpac[pval < .05].mean()
p.comodulogram(xpac, title='Modulation Index (MI) - wavelet', cmap='viridis', vmin=0., pvalues=pval,
levels=.05)

I get a similar region with high MI but it is no longer significant

And this is true with different noise levels, using dcomplex='hilbert' or 'wavelet', different methods of permutation calculation, different numbers of permutations, and different MI calculation methods (I have tried 2 for tort and 5 for gaussian copula). Is this an issue with the pac_signals_tort function, or an issue within the permutation generation?