pyriemann.utils.viz.plot_embedding(X, y=None, *, metric='riemann', title='Embedding of covariances', embd_type='Spectral', normalize=True)

Plot 2D embedding of SPD matrices.

Xndarray, shape (n_matrices, n_channels, n_channels)

Set of SPD matrices.

yNone | ndarray, shape (n_matrices,), default=None

Labels for each matrix.

metricstring, default=’riemann’

Metric used in the embedding. Can be {‘riemann’ ,’logeuclid’ , ‘euclid’} for Locally Linear Embedding and {‘riemann’ ,’logeuclid’ , ‘euclid’ , ‘logdet’, ‘kullback’, ‘kullback_right’, ‘kullback_sym’} for Spectral Embedding.

titlestr, default=”Embedding of covariances”

Title string for plot.

embd_type{‘Spectral’ ,’LocallyLinear’}, default=’Spectral’

Embedding type.

normalizebool, default=True

If True, the plot is normalized from -1 to +1.

figmatplotlib figure

Figure of embedding.