plt.loglog(freqs[below50], psd[0, below50], label='max SNR')
plt.loglog(freqs[below50], psd[-1, below50], label='min SNR')
plt.loglog(freqs[below50], psd[:, below50].mean(axis=0), label='mean')
plt.fill_between(freqs[bandfilt], 0, 100,\
color='green', alpha=0.5)
plt.xlabel("log(frequency)")
plt.ylabel("log(power)")
plt.legend()
#%%
pattern = mne.EvokedArray(data=ssd.patterns_[:4].T,
info=mne.pick_info(raw.info, ssd.picks_))
pattern.plot_topomap(units=dict(mag='A.U.'), time_format='')
#%%
X_dnoised = ssd.apply(raw)
#%%
# ssd_denoised=ssd.apply(raw)
# plt.figure()
# plt.psd(mne.filter.filter_data(ssd_denoised[10], raw.info['sfreq'],l_freq=freqs_sig[0], h_freq=freqs_sig[1],
# l_trans_bandwidth=1, h_trans_bandwidth=1,
# fir_design='firwin'))
# plt.psd(mne.filter.filter_data(raw.get_data()[picks[10]], raw.info['sfreq'],l_freq=freqs_sig[0], h_freq=freqs_sig[1],
# l_trans_bandwidth=1, h_trans_bandwidth=1,
# fir_design='firwin'))
# #%% epochs
# file_name='/mnt/Datos/BML_CNCRS/Spoc/ECOG_epochs_wofb_sub_000_sess_right_run_0.p'
# with open(file_name, 'rb') as handle:
# sub_ = pickle.load(handle)
# data=sub_['epochs']
# label_ips=sub_['label_ips']
