mne.preprocessing.compute_maxwell_basis#

mne.preprocessing.compute_maxwell_basis(info, origin='auto', int_order=8, ext_order=3, calibration=None, coord_frame='head', regularize='in', ignore_ref=True, bad_condition='error', mag_scale=100.0, extended_proj=(), verbose=None)[source]#

Compute the SSS basis for a given measurement info structure.

Parameters

infomne.Info: The mne.Info object with information about the sensors and methods of measurement.
originarray-like, shape (3,) | str: Origin of internal and external multipolar moment space in meters. The default is 'auto', which means (0., 0., 0.) when coord_frame='meg', and a head-digitization-based origin fit using fit_sphere_to_headshape() when coord_frame='head'. If automatic fitting fails (e.g., due to having too few digitization points), consider separately calling the fitting function with different options or specifying the origin manually.
int_orderint: Order of internal component of spherical expansion.
ext_orderint: Order of external component of spherical expansion.
calibrationstr | None: Path to the '.dat' file with fine calibration coefficients. File can have 1D or 3D gradiometer imbalance correction. This file is machine/site-specific.
coord_framestr: The coordinate frame that the origin is specified in, either 'meg' or 'head'. For empty-room recordings that do not have a head<->meg transform info['dev_head_t'], the MEG coordinate frame should be used.
regularizestr | None: Basis regularization type, must be “in” or None. “in” is the same algorithm as the “-regularize in” option in MaxFilter™.
ignore_refbool: If True, do not include reference channels in compensation. This option should be True for KIT files, since Maxwell filtering with reference channels is not currently supported.
bad_conditionstr: How to deal with ill-conditioned SSS matrices. Can be “error” (default), “warning”, “info”, or “ignore”.
mag_scalefloat | str: The magenetometer scale-factor used to bring the magnetometers to approximately the same order of magnitude as the gradiometers (default 100.), as they have different units (T vs T/m). Can be 'auto' to use the reciprocal of the physical distance between the gradiometer pickup loops (e.g., 0.0168 m yields 59.5 for VectorView).
extended_projlist: The empty-room projection vectors used to extend the external SSS basis (i.e., use eSSS).

New in version 0.21.
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

Sndarray, shape (n_meg, n_moments): The basis that can be used to reconstruct the data.
pSndarray, shape (n_moments, n_good_meg): The (stabilized) pseudoinverse of the S array.
reg_momentsndarray, shape (n_moments,): The moments that were kept after regularization.
n_use_inint: The number of kept moments that were in the internal space.

Notes

This outputs variants of \(\mathbf{S}\) and \(\mathbf{S^\dagger}\) from equations 27 and 37 of 1 with the coil scale for magnetometers already factored in so that the resulting denoising transform of the data to obtain \(\hat{\phi}_{in}\) from equation 38 would be:

phi_in = S[:, :n_use_in] @ pS[:n_use_in] @ data_meg_good

New in version 0.23.

References

1: Samu Taulu and Matti Kajola. Presentation of electromagnetic multichannel data: the signal space separation method. Journal of Applied Physics, 97(12):124905, 2005. doi:10.1063/1.1935742.

mne.preprocessing.compute_fine_calibration

mne.preprocessing.compute_proj_ecg