mne.simulation.simulate_sparse_stc(src, n_dipoles, times, data_fun=<function <lambda>>, labels=None, random_state=None, location=’random’, subject=None, subjects_dir=None, surf=’sphere’)[source]

Generate sparse (n_dipoles) sources time courses from data_fun.

This function randomly selects n_dipoles vertices in the whole cortex or one single vertex (randomly in or in the center of) each label if labels is not None. It uses data_fun to generate waveforms for each vertex.


src : instance of SourceSpaces

The source space.

n_dipoles : int

Number of dipoles to simulate.

times : array

Time array

data_fun : callable

Function to generate the waveforms. The default is a 100 nAm, 10 Hz sinusoid as 1e-7 * np.sin(20 * pi * t). The function should take as input the array of time samples in seconds and return an array of the same length containing the time courses.

labels : None | list of Labels

The labels. The default is None, otherwise its size must be n_dipoles.

random_state : None | int | np.random.RandomState

To specify the random generator state.

location : str

The label location to choose. Can be ‘random’ (default) or ‘center’ to use mne.Label.center_of_mass(). Note that for ‘center’ mode the label values are used as weights.

New in version 0.13.

subject : string | None

The subject the label is defined for. Only used with location='center'.

New in version 0.13.

subjects_dir : str, or None

Path to the SUBJECTS_DIR. If None, the path is obtained by using the environment variable SUBJECTS_DIR. Only used with location='center'.

New in version 0.13.

surf : str

The surface to use for Euclidean distance center of mass finding. The default here is “sphere”, which finds the center of mass on the spherical surface to help avoid potential issues with cortical folding.

New in version 0.13.


stc : SourceEstimate

The generated source time courses.


New in version 0.10.0.

Examples using mne.simulation.simulate_sparse_stc