mne.simulation.metrics.spatial_deviation_error#

mne.simulation.metrics.spatial_deviation_error(stc_true, stc_est, src, threshold='50%', per_sample=True)[source]#

Compute the spatial deviation.

The spatial deviation characterizes the spread of the estimate source around the true source.

\[SD = \dfrac{\sum_i|s_i|\|r_{i} - r_{true}\|^2}{\sum_i|s_i|}.\]

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.
thresholdfloat | 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_samplebool: If True the metric is computed for each sample separately. If False, the metric is spatio-temporal.

Returns:

metricfloat | array, shape (n_times,): The metric. float if per_sample is False, else array with the values computed for each time point.

Notes

These metrics are documented in [1] and [2].

New in v1.2.

References

Examples using `mne.simulation.metrics.spatial_deviation_error`#