def test_preferred_phase():
"""Test the prefered phase."""
data = np.random.rand(2, 1024)
p = Pac(idpac=(4, 0, 0))
pha = p.filter(1024, data, axis=1, ftype='phase')
amp = p.filter(1024, data, axis=1, ftype='amplitude')
p.pp(pha, amp, axis=2)
# Generate 100 datasets with a 6<->100hz coupling :
sf = 1024.
ntrials = 100
data, time = pac_signals_wavelet(fpha=6, famp=100, ntrials=ntrials, sf=sf,
noise=.7, npts=2000, pp=np.pi/2)
# Define a Pac object. Here, we are not going to use the idpac variable :
p = Pac(fpha=[5, 7], famp=(60, 200, 10, 1))
# Extract the phase and the amplitude :
pha = p.filter(sf, data, axis=1, ftype='phase')
amp = p.filter(sf, data, axis=1, ftype='amplitude')
# Now, compute the PP :
ambin, pp, vecbin = p.pp(pha, amp, axis=2, nbins=72)
# Reshape the PP to be (ntrials, namp) :
pp = np.squeeze(pp).T
# Reshape the amplitude to be (nbins, namp, ntrials) and take the mean across
# datasets :
ambin = np.squeeze(ambin).mean(-1)
plt.figure(figsize=(20, 35))
# Plot the prefered phase :
plt.subplot(221)
plt.pcolormesh(p.yvec, np.arange(100), np.rad2deg(pp), cmap='Spectral_r')
cb = plt.colorbar()
plt.clim(vmin=-180., vmax=180.)
plt.axis('tight')
