Computation times¶
07:42.640 total execution time for auto_examples_inverse files:
01:43.331: Demonstrate impact of whitening on source estimates (
plot_covariance_whitening_dspm.py
)00:48.770: Compute MNE inverse solution on evoked data in a mixed source space (
plot_mixed_source_space_inverse.py
)00:46.836: Compute source power using DICS beamfomer (
plot_dics_source_power.py
)00:28.719: Morph volumetric source estimate (
plot_morph_volume_stc.py
)00:26.004: Compute LCMV inverse solution in volume source space (
plot_lcmv_beamformer_volume.py
)00:25.041: Time-frequency beamforming using DICS (
plot_tf_dics.py
)00:24.870: Time-frequency beamforming using LCMV (
plot_tf_lcmv.py
)00:23.941: Compute LCMV beamformer on evoked data (
plot_lcmv_beamformer.py
)00:22.660: Compute a sparse inverse solution using the Gamma-Map empirical Bayesian method (
plot_gamma_map_inverse.py
)00:19.254: Compute MxNE with time-frequency sparse prior (
plot_time_frequency_mixed_norm_inverse.py
)00:18.171: Morph surface source estimate (
plot_morph_surface_stc.py
)00:12.758: Compute sparse inverse solution with mixed norm: MxNE and irMxNE (
plot_mixed_norm_inverse.py
)00:09.098: Compute point-spread functions (PSFs) for MNE/dSPM/sLORETA (
plot_mne_point_spread_function.py
)00:08.827: Compute cross-talk functions (CTFs) for labels for MNE/dSPM/sLORETA (
plot_mne_crosstalk_function.py
)00:08.098: Generate a functional label from source estimates (
plot_label_from_stc.py
)00:06.653: Compute Rap-Music on evoked data (
plot_rap_music.py
)00:06.078: Plotting the full MNE solution (
plot_vector_mne_solution.py
)00:05.652: Compute MNE-dSPM inverse solution on evoked data in volume source space (
plot_compute_mne_inverse_volume.py
)00:03.740: Reading a source space from a forward operator (
plot_read_source_space.py
)00:03.391: Source localization with a custom inverse solver (
plot_custom_inverse_solver.py
)00:02.698: Compute MNE-dSPM inverse solution on single epochs (
plot_compute_mne_inverse_epochs_in_label.py
)00:01.620: Plot an estimate of data SNR (
plot_snr_estimate.py
)00:01.597: Compute sLORETA inverse solution on raw data (
plot_compute_mne_inverse_raw_in_label.py
)00:01.550: Reading an inverse operator (
plot_read_inverse.py
)00:01.416: Extracting the time series of activations in a label (
plot_label_source_activations.py
)00:00.968: Reading an STC file (
plot_read_stc.py
)00:00.898: Extracting time course from source_estimate object (
plot_label_activation_from_stc.py
)