# Time Frequency Analysis (wavelet)

%matplotlib qt

import mne
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
from mne.time_frequency import tfr_morlet, psd_multitaper

data_path = '/Users/kevinhsu/Documents/D/000_experiment/compounding_VR/2013_megdata'

sid = 1
epochs_file = data_path + '/%.3dnn_raw_epo.fif' % sid
epochs = mne.read_epochs(epochs_file)
epochs

Reading /Users/kevinhsu/Documents/D/000_experiment/compounding_VR/2013_megdata/001nn_raw_epo.fif ...
Isotrak not found
Found the data of interest:
t = -100.00 ... 700.00 ms
0 CTF compensation matrices available
287 matching events found
Applying baseline correction (mode: mean)
Not setting metadata
0 projection items activated

<EpochsFIF | 287 events (all good), -0.1 - 0.7 sec, baseline [-0.1, 0], ~275.7 MB, data loaded,
'pseudo': 143
'words': 144>

epochs.plot_psd(fmin=2., fmax=40.)

Using multitaper spectrum estimation with 7 DPSS windows


# define frequencies of interest (log-spaced)
#freqs = np.logspace(*np.log10([6, 35]), num=8)
freqs = np.arange(2., 30., 3.)
n_cycles = freqs / 2.  # different number of cycle per frequency
power, itc = tfr_morlet(epochs, freqs=freqs, n_cycles=n_cycles, use_fft=True,
                        return_itc=True, decim=3, n_jobs=1)

power.plot_topo(baseline=(-0.1, 0), mode='logratio', title='Average power')

Applying baseline correction (mode: logratio)


power.plot_topomap(ch_type='mag', tmin=0.1, tmax=0.2, fmin=5, fmax=7,
                   baseline=(-0.1, 0), mode='logratio',
                   title='Theta', show=False)

Applying baseline correction (mode: logratio)


power.plot_topomap(ch_type='mag', tmin=0.1, tmax=0.2, fmin=8, fmax=12,
                   baseline=(-0.1, 0), mode='logratio',
                   title='Alpha', show=False)

Applying baseline correction (mode: logratio)