pyriemann.utils.mean.mean_covariance¶
- pyriemann.utils.mean.mean_covariance(covmats, metric='riemann', sample_weight=None, **kwargs)¶
Mean of SPD matrices according to a metric.
- Parameters
- covmatsndarray, shape (n_matrices, n_channels, n_channels)
Set of SPD matrices.
- metricstring, default=’riemann’
The metric for mean, can be: ‘ale’, ‘alm’, ‘euclid’, ‘harmonic’, ‘identity’, ‘kullback_sym’, ‘logdet’, ‘logeuclid’, ‘riemann’, ‘wasserstein’, or a callable function.
- sample_weightNone | ndarray, shape (n_matrices,), default=None
Weights for each matrix. If None, it uses equal weights.
- **kwargsdict
The keyword arguments passed to the sub function.
- Returns
- Cndarray, shape (n_channels, n_channels)
Mean of SPD matrices.