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 of figure.

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.


New in version 0.2.6.