Multitaper spectrogram plot¶

Below is a code sample for plotting spectrograms

from ieeg.viz.ensemble import chan_grid
from ieeg.timefreq.multitaper import spectrogram
from ieeg.timefreq.utils import crop_pad
from ieeg.navigate import channel_outlier_marker
from ieeg.viz.parula import parula_map
import numpy as np
import mne

Load Data¶

misc_path = mne.datasets.misc.data_path()
raw = mne.io.read_raw(misc_path / 'seeg' / 'sample_seeg_ieeg.fif')

Using default location ~/mne_data for misc...
Creating /home/docs/mne_data
Dataset misc version 0.0 out of date, latest version is 0.27
Downloading file 'mne-misc-data-0.27.tar.gz' from 'https://codeload.github.com/mne-tools/mne-misc-data/tar.gz/0.27' to '/home/docs/mne_data'.

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Untarring contents of '/home/docs/mne_data/mne-misc-data-0.27.tar.gz' to '/home/docs/mne_data'
Attempting to create new mne-python configuration file:
/home/docs/.mne/mne-python.json
Download complete in 30s (278.8 MB)
Opening raw data file /home/docs/mne_data/MNE-misc-data/seeg/sample_seeg_ieeg.fif...
    Range : 1310640 ... 1370605 =   1311.411 ...  1371.411 secs
Ready.

Remove bad channels¶

# mark channel outliers as bad
raw.info['bads'] = channel_outlier_marker(raw, 3)

# Exclude bad channels
raw.drop_channels(raw.info['bads'])
raw.load_data()

# CAR (common average reference)
raw.set_eeg_reference(ref_channels="average", ch_type='seeg')

outlier round 1 channels: ['LAMY 7']
outlier round 1 channels: ['LAMY 7', 'LPHG 6']
outlier round 1 channels: ['LAMY 7', 'LPHG 6', 'LBRI 3']
outlier round 1 channels: ['LAMY 7', 'LPHG 6', 'LBRI 3', 'RAHP 3']
outlier round 2 channels: ['LAMY 7', 'LPHG 6', 'LBRI 3', 'RAHP 3', 'LENT 3']
outlier round 2 channels: ['LAMY 7', 'LPHG 6', 'LBRI 3', 'RAHP 3', 'LENT 3', 'LPIT 5']
outlier round 3 channels: ['LAMY 7', 'LPHG 6', 'LBRI 3', 'RAHP 3', 'LENT 3', 'LPIT 5', 'LENT 2']
outlier round 3 channels: ['LAMY 7', 'LPHG 6', 'LBRI 3', 'RAHP 3', 'LENT 3', 'LPIT 5', 'LENT 2', 'LENT 7']
outlier round 4 channels: ['LAMY 7', 'LPHG 6', 'LBRI 3', 'RAHP 3', 'LENT 3', 'LPIT 5', 'LENT 2', 'LENT 7', 'LPLI 8']
outlier round 5 channels: ['LAMY 7', 'LPHG 6', 'LBRI 3', 'RAHP 3', 'LENT 3', 'LPIT 5', 'LENT 2', 'LENT 7', 'LPLI 8', 'RAHP 2']
outlier round 6 channels: ['LAMY 7', 'LPHG 6', 'LBRI 3', 'RAHP 3', 'LENT 3', 'LPIT 5', 'LENT 2', 'LENT 7', 'LPLI 8', 'RAHP 2', 'LPIT 6']
Reading 0 ... 59965  =      0.000 ...    60.000 secs...
Applying average reference.
Applying a custom ('sEEG',) reference.

	General
	Filename(s)	sample_seeg_ieeg.fif
	MNE object type	Raw
	Measurement date	2019-10-18 at 11:09:44 UTC
	Participant	sub-1
	Experimenter	Unknown
	Acquisition
	Duration	00:01:01 (HH:MM:SS)
	Sampling frequency	999.41 Hz
	Time points	59,966
	Channels
	sEEG
	Head & sensor digitization	122 points
	Filters
	Highpass	0.00 Hz
	Lowpass	499.71 Hz

Calculate Spectra¶

freq = np.arange(10, 200., 6.)
spectra = spectrogram(raw, freq, 'Response', -1.2, 1.2, 'Fixation', -1.2, 0.2,
                      n_jobs=1, verbose=10, time_bandwidth=10, n_cycles=freq/2)
crop_pad(spectra, "0.5s")

Used Annotations descriptions: [np.str_('Fixation'), np.str_('Go Cue'), np.str_('ISI Onset'), np.str_('Response')]
Not setting metadata
8 matching events found
No baseline correction applied
0 projection items activated
Using data from preloaded Raw for 8 events and 3399 original time points ...
1 bad epochs dropped
Not setting metadata
8 matching events found
No baseline correction applied
0 projection items activated
Using data from preloaded Raw for 8 events and 2400 original time points ...
0 bad epochs dropped
NOTE: tfr_multitaper() is a legacy function. New code should use .compute_tfr(method="multitaper").
Data is self data: True
  Copying, fancy indexed picks
NOTE: tfr_multitaper() is a legacy function. New code should use .compute_tfr(method="multitaper").
Data is self data: True
  Copying, fancy indexed picks

Data type	TFR
Data source	Evoked
Number of averaged trials	7
Dims	channel, freq, time
Estimation method	multitaper
Number of channels	108
Number of timepoints	1399
Number of frequency bins	32
Frequency range	10.00 – 196.00 Hz

Plot data¶

chan_grid(spectra, vlim=(0.7, 1.4), cmap=parula_map)

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[<Figure size 1250.45x1875.67 with 60 Axes>, <Figure size 1250.45x1875.67 with 60 Axes>]

Total running time of the script: (1 minutes 35.919 seconds)

Estimated memory usage: 4696 MB