mne.viz.plot_chpi_snr#

mne.viz.plot_chpi_snr(snr_dict, axes=None)[source]#

Plot time-varying SNR estimates of the HPI coils.

Parameters:

snr_dictdict

The dictionary returned by compute_chpi_snr. Must have keys times, freqs, TYPE_snr, TYPE_power, and TYPE_resid (where TYPE can be mag or grad or both).

axesNone | list of matplotlib.axes.Axes

Figure axes in which to draw the SNR, power, and residual plots. The number of axes should be 3× the number of MEG sensor types present in snr_dict. If None (the default), a new Figure is created with the required number of axes.

Returns:

figinstance of matplotlib.figure.Figure

A figure with subplots for SNR, power, and residual variance, separately for magnetometers and/or gradiometers (depending on what is present in snr_dict).

Notes

If you supply a list of existing Axes, then the figure legend will not be drawn automatically. If you still want it, running fig.legend(loc='right', title='cHPI frequencies') will recreate it, though you may also need to manually adjust the margin to make room for it (e.g., using fig.subplots_adjust(right=0.8)).

New in version 0.24.

Examples using mne.viz.plot_chpi_snr#

Extracting and visualizing subject head movement

Extracting and visualizing subject head movement