mne.simulation.simulate_raw#

mne.simulation.simulate_raw(info, stc=None, trans=None, src=None, bem=None, head_pos=None, mindist=1.0, interp='cos2', n_jobs=None, use_cps=True, forward=None, first_samp=0, max_iter=10000, verbose=None)[source]#

Simulate raw data.

Head movements can optionally be simulated using the head_pos parameter.

Parameters:

infomne.Info: The mne.Info object with information about the sensors and methods of measurement. Used for simulation.

Changed in version 0.18: Support for mne.Info.
stciterable | SourceEstimate | SourceSimulator: The source estimates to use to simulate data. Each must have the same sample rate as the raw data, and the vertices of all stcs in the iterable must match. Each entry in the iterable can also be a tuple of (SourceEstimate, ndarray) to allow specifying the stim channel (e.g., STI001) data accompany the source estimate. See Notes for details.

Changed in version 0.18: Support for tuple, iterable of tuple or SourceEstimate, or SourceSimulator.
transdict | 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). If trans is None, an identity transform will be used.
srcstr | instance of SourceSpaces | None: Source space corresponding to the stc. If string, should be a source space filename. Can also be an instance of loaded or generated SourceSpaces. Can be None if forward is provided.
bemstr | dict | None: BEM solution corresponding to the stc. If string, should be a BEM solution filename (e.g., “sample-5120-5120-5120-bem-sol.fif”). Can be None if forward is provided.
head_posNone | str | dict | tuple | array: Name of the position estimates file. Should be in the format of the files produced by MaxFilter. If dict, keys should be the time points and entries should be 4x4 dev_head_t matrices. If None, the original head position (from info['dev_head_t']) will be used. If tuple, should have the same format as data returned by head_pos_to_trans_rot_t. If array, should be of the form returned by mne.chpi.read_head_pos(). See for example [1].
mindistfloat: Minimum distance between sources and the inner skull boundary to use during forward calculation.
interpstr: Either ‘hann’, ‘cos2’ (default), ‘linear’, or ‘zero’, the type of forward-solution interpolation to use between forward solutions at different head positions.
n_jobsint | None: The number of jobs to run in parallel. If -1, it is set to the number of CPU cores. Requires the joblib package. None (default) is a marker for ‘unset’ that will be interpreted as n_jobs=1 (sequential execution) unless the call is performed under a joblib.parallel_backend() context manager that sets another value for n_jobs.
use_cpsbool: Whether to use cortical patch statistics to define normal orientations for surfaces (default True).
forwardinstance of Forward | None: The forward operator to use. If None (default) it will be computed using bem, trans, and src. If not None, bem, trans, and src are ignored.

New in version 0.17.
first_sampint: The first_samp property in the output Raw instance.

New in version 0.18.
max_iterint: The maximum number of STC iterations to allow. This is a sanity parameter to prevent accidental blowups.

New in version 0.18.
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:

rawinstance of Raw: The simulated raw file.

Data alignment and stim channel encoding#
Channel	Data
M/EEG	`fwd @ stc[0][0].data`	`fwd @ stc[1][0].data`	`...`
STIM	`stc[0][1]`	`stc[1][1]`	`...`
	time →

Examples using `mne.simulation.simulate_raw`#

DICS for power mapping

Generate simulated raw data

Simulate raw data using subject anatomy

Generate simulated source data

mne.simulation.simulate_raw#

Examples using mne.simulation.simulate_raw#

Examples using `mne.simulation.simulate_raw`#