mne.chpi.compute_chpi_snr

mne.chpi.compute_chpi_snr(raw, t_step_min=0.01, t_window='auto', ext_order=1, tmin=0, tmax=None, verbose=None)

Compute time-varying estimates of cHPI SNR.

Parameters

rawinstance of Raw

Raw data with cHPI information.

t_step_minfloat

Minimum time step to use.

t_windowfloat

Time window to use to estimate the amplitudes, default is 0.2 (200 ms).

ext_orderint

The external order for SSS-like interfence suppression. The SSS bases are used as projection vectors during fitting.

Changed in version 0.20: Added ext_order=1 by default, which should improve detection of true HPI signals.

tminfloat

Start time of the raw data to use in seconds (must be >= 0).

tmaxfloat

End time of the raw data to use in seconds (cannot exceed data duration).

verbosebool | str | int | None

Control verbosity of the logging output. If None, use the default verbosity level. See the logging documentation and mne.verbose() for details. Should only be passed as a keyword argument.

Returns

chpi_snrsdict

The time-varying cHPI SNR estimates, with entries “times”, “freqs”, “snr_mag”, “power_mag”, and “resid_mag” (and/or “snr_grad”, “power_grad”, and “resid_grad”, depending on which channel types are present in raw).

See also

mne.chpi.compute_chpi_locs, mne.chpi.compute_chpi_amplitudes

Notes

New in version 0.24.

Examples using mne.chpi.compute_chpi_snr

Extracting and visualizing subject head movement

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