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)[source]#

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 | None: End time of the raw data to use in seconds (cannot exceed data duration). If None (default), the current end of the data is used.
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).

Examples using `mne.chpi.compute_chpi_snr`#