This documentation is for development version 0.18.dev0.


mne.make_forward_solution(info, trans, src, bem, meg=True, eeg=True, mindist=0.0, ignore_ref=False, n_jobs=1, verbose=None)[source]

Calculate a forward solution for a subject.

info : instance of mne.Info | str

If str, then it should be a filename to a Raw, Epochs, or Evoked file with measurement information. If dict, should be an info dict (such as one from Raw, Epochs, or Evoked).

trans : dict | str | None

Either a transformation filename (usually made using mne_analyze) or an info dict (usually opened using read_trans()). If string, an ending of fif or fif.gz will be assumed to be in FIF format, any other ending will be assumed to be a text file with a 4x4 transformation matrix (like the –trans MNE-C option). Can be None to use the identity transform.

src : str | instance of SourceSpaces

If string, should be a source space filename. Can also be an instance of loaded or generated SourceSpaces.

bem : dict | str

Filename of the BEM (e.g., “sample-5120-5120-5120-bem-sol.fif”) to use, or a loaded sphere model (dict).

meg : bool

If True (Default), include MEG computations.

eeg : bool

If True (Default), include EEG computations.

mindist : float

Minimum distance of sources from inner skull surface (in mm).

ignore_ref : bool

If True, do not include reference channels in compensation. This option should be True for KIT files, since forward computation with reference channels is not currently supported.

n_jobs : int

Number of jobs to run in parallel.

verbose : bool, str, int, or None

If not None, override default verbose level (see mne.verbose() and Logging documentation for more).

fwd : instance of Forward

The forward solution.


The --grad option from MNE-C (to compute gradients) is not implemented here.

To create a fixed-orientation forward solution, use this function followed by mne.convert_forward_solution().