mne.simulation.metrics.peak_position_error#
- mne.simulation.metrics.peak_position_error(stc_true, stc_est, src, threshold='50%', per_sample=True)[source]#
Compute the peak position error.
The peak position error measures the distance between the center-of-mass of the estimated and the true source.
\[PPE = \| \dfrac{\sum_i|s_i|r_{i}}{\sum_i|s_i|} - r_{true}\|,\]where \(r_{true}\) is a true dipole position, \(r_i\) and \(|s_i|\) denote respectively the position and amplitude of i-th dipole in source estimate.
Threshold is used on estimated source for focusing the metric to strong amplitudes and omitting the low-amplitude values.
- Parameters
- stc_trueinstance of (Vol|Mixed)SourceEstimate
The source estimates containing correct values.
- stc_estinstance of (Vol|Mixed)SourceEstimate
The source estimates containing estimated values e.g. obtained with a source imaging method.
- srcinstance of
SourceSpaces The source space on which the source estimates are defined.
- threshold
float|str The threshold to apply to source estimates before computing the recall. If a string the threshold is a percentage and it should end with the percent character.
- per_sample
bool If True the metric is computed for each sample separately. If False, the metric is spatio-temporal.
- Returns
Notes
These metrics are documented in 1 and 2.
New in v1.2.
References
- 1
Matti Stenroos and Olaf Hauk. Minimum-norm cortical source estimation in layered head models is robust against skull conductivity error. NeuroImage, 81:265–272, November 2013. doi:10.1016/j.neuroimage.2013.04.086.
- 2
Fa-Hsuan Lin, Thomas Witzel, Seppo P. Ahlfors, Steven M. Stufflebeam, John W. Belliveau, and Matti S. Hämäläinen. Assessing and improving the spatial accuracy in MEG source localization by depth-weighted minimum-norm estimates. NeuroImage, 31(1):160–171, 2006. doi:10.1016/j.neuroimage.2005.11.054.
