Simulation

mne.simulation:

Data simulation code.

add_chpi(raw[, head_pos, interp, n_jobs, ...])	Add cHPI activations to raw data.
add_ecg(raw[, head_pos, interp, n_jobs, ...])	Add ECG noise to raw data.
add_eog(raw[, head_pos, interp, n_jobs, ...])	Add blink noise to raw data.
add_noise(inst, cov[, iir_filter, ...])	Create noise as a multivariate Gaussian.
simulate_evoked(fwd, stc, info[, cov, nave, ...])	Generate noisy evoked data.
simulate_raw(info[, stc, trans, src, bem, ...])	Simulate raw data.
simulate_stc(src, labels, stc_data, tmin, tstep)	Simulate sources time courses from waveforms and labels.
simulate_sparse_stc(src, n_dipoles, times[, ...])	Generate sparse (n_dipoles) sources time courses from data_fun.
select_source_in_label(src, label[, ...])	Select source positions using a label.
SourceSimulator(src[, tstep, duration, ...])	Class to generate simulated Source Estimates.

mne.simulation.metrics:

Metrics module for compute stc-based metrics.

cosine_score(stc_true, stc_est[, per_sample])	Compute cosine similarity between 2 source estimates.
region_localization_error(stc_true, stc_est, src)	Compute region localization error (RLE) between 2 source estimates.
f1_score(stc_true, stc_est[, threshold, ...])	Compute the F1 score, also known as balanced F-score or F-measure.
precision_score(stc_true, stc_est[, ...])	Compute the precision.
recall_score(stc_true, stc_est[, threshold, ...])	Compute the recall.
roc_auc_score(stc_true, stc_est[, per_sample])	Compute ROC AUC between 2 source estimates.
spatial_deviation_error(stc_true, stc_est, src)	Compute the spatial deviation.
peak_position_error(stc_true, stc_est, src)	Compute the peak position error.