This documentation is for development version 0.18.dev0.

mne.simulation.simulate_evoked

mne.simulation.simulate_evoked(fwd, stc, info, cov, nave=30, iir_filter=None, random_state=None, use_cps=True, verbose=None)[source]

Generate noisy evoked data.

Note

No projections from info will be present in the output evoked. You can use e.g. evoked.add_proj or evoked.set_eeg_reference to add them afterward as necessary.

Parameters:
fwd : Forward

a forward solution.

stc : SourceEstimate object

The source time courses.

info : dict

Measurement info to generate the evoked.

cov : Covariance object

The noise covariance.

nave : int

Number of averaged epochs (defaults to 30).

New in version 0.15.0.

iir_filter : None | array

IIR filter coefficients (denominator) e.g. [1, -1, 0.2].

random_state : None | int | ~numpy.random.RandomState

To specify the random generator state.

use_cps : bool (default True)

Whether to use cortical patch statistics to define normal orientations when converting to fixed orientation (if necessary).

New in version 0.15.

verbose : bool, str, int, or None

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

Returns:
evoked : Evoked object

The simulated evoked data

Notes

To make the equivalence between snr and nave, when the snr is given instead of nave:

nave = (1 / 10 ** ((actual_snr - snr)) / 20) ** 2

where actual_snr is the snr to the generated noise before scaling.

New in version 0.10.0.