Show noise levels from empty room data#

This shows how to use mne.io.Raw.plot_psd() to examine noise levels of systems. See [1] for an example.

# Author: Eric Larson <larson.eric.d@gmail.com>
#
# License: BSD-3-Clause
import os.path as op
import mne

data_path = mne.datasets.sample.data_path()

raw_erm = mne.io.read_raw_fif(op.join(data_path, 'MEG', 'sample',
                                      'ernoise_raw.fif'), preload=True)
Opening raw data file /home/circleci/mne_data/MNE-sample-data/MEG/sample/ernoise_raw.fif...
Isotrak not found
    Read a total of 3 projection items:
        PCA-v1 (1 x 102)  idle
        PCA-v2 (1 x 102)  idle
        PCA-v3 (1 x 102)  idle
    Range : 19800 ... 85867 =     32.966 ...   142.965 secs
Ready.
Reading 0 ... 66067  =      0.000 ...   109.999 secs...

We can plot the absolute noise levels:

raw_erm.plot_psd(tmax=10., average=True, spatial_colors=False,
                 dB=False, xscale='log')
Gradiometers, Magnetometers
NOTE: plot_psd() is a legacy function. New code should use .compute_psd().plot().
Effective window size : 0.426 (s)

References#

Total running time of the script: ( 0 minutes 2.873 seconds)

Estimated memory usage: 168 MB

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