mne.chpi.compute_chpi_locs(info, chpi_amplitudes, t_step_max=1.0, too_close='raise', adjust_dig=False, verbose=None)[source]#

Compute locations of each cHPI coils over time.


The mne.Info object with information about the sensors and methods of measurement.


The time-varying cHPI coil amplitudes, with entries “times”, “proj”, and “slopes”. Typically obtained by mne.chpi.compute_chpi_amplitudes().


Maximum time step to use.


How to handle HPI positions too close to the sensors, can be 'raise' (default), 'warning', or 'info'.


If True, adjust the digitization locations used for fitting based on the positions localized at the start of the file.

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.


The time-varying cHPI coils locations, with entries “times”, “rrs”, “moments”, and “gofs”.


This function is designed to take the output of mne.chpi.compute_chpi_amplitudes() and:

  1. Get HPI coil locations (as digitized in info['dig']) in head coords.

  2. If the amplitudes are 98% correlated with last position (and Δt < t_step_max), skip fitting.

  3. Fit magnetic dipoles using the amplitudes for each coil frequency.

The number of fitted points n_pos will depend on the velocity of head movements as well as t_step_max (and t_step_min from mne.chpi.compute_chpi_amplitudes()).

New in v0.20.

Examples using mne.chpi.compute_chpi_locs#

Extracting and visualizing subject head movement

Extracting and visualizing subject head movement