mne.chpi.compute_chpi_amplitudes¶

mne.chpi.
compute_chpi_amplitudes
(raw, t_step_min=0.01, t_window='auto', ext_order=1, tmin=0, tmax=None, verbose=None)[source]¶ Compute timevarying cHPI amplitudes.
 Parameters
 rawinstance of
Raw
Raw data with cHPI information.
 t_step_min
float
Minimum time step to use. If correlations are sufficiently high, t_step_max will be used.
 t_window
float
Time window to use to estimate the amplitudes, default is 0.2 (200 ms).
 ext_order
int
The external order for SSSlike 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. tmin
float
Start time of the raw data to use in seconds (must be >= 0).
 tmax
float
End time of the raw data to use in seconds (cannot exceed data duration).
 verbosebool,
str
,int
, orNone
If not None, override default verbose level (see
mne.verbose()
and Logging documentation for more). If used, it should be passed as a keywordargument only.
 rawinstance of
 Returns
 chpi_amplitudes
dict
The timevarying cHPI coil amplitudes, with entries “times”, “proj”, and “slopes”.
 chpi_amplitudes
See also
Notes
This function will:
Get HPI frequencies, HPI status channel, HPI status bits, and digitization order using
_setup_hpi_amplitude_fitting
.Window data using
t_window
(half before and half aftert
) andt_step_min
.Use a linear model (DC + linear slope + sin + cos terms) to fit sinusoidal amplitudes to MEG channels. It uses SVD to determine the phase/amplitude of the sinusoids.
In “auto” mode,
t_window
will be set to the longer of: Five cycles of the lowest HPI or line frequency.
Ensures that the frequency estimate is stable.
 The reciprocal of the smallest difference between HPI and line freqs.
Ensures that neighboring frequencies can be disambiguated.
The output is meant to be used with
compute_chpi_locs()
.New in version 0.20.