pyriemann.estimation.Covariances¶

class pyriemann.estimation.Covariances(estimator='scm', **kwds)¶

Estimation of covariance matrices.

Perform a simple covariance matrix estimation for each given input.

Parameters:

estimatorstring, default=”scm”: Covariance matrix estimator, see pyriemann.utils.covariance.covariances().
**kwdsdict: Any further parameters are passed directly to the covariance estimator.

See also

ERPCovariances
XdawnCovariances

__init__(estimator='scm', **kwds)¶: Init.

fit(X, y=None)¶

Fit.

Do nothing. For compatibility purpose.

Parameters:

Xndarray, shape (n_matrices, n_channels, n_times): Multi-channel time-series.
yNone: Not used, here for compatibility with sklearn API.

Returns:

selfCovariances instance: The Covariances instance.

fit_transform(X, y=None)¶

Fit and transform in a single function.

Parameters:

Xndarray, shape (n_matrices, n_channels, n_times): Multi-channel time-series.
yNone: Not used, here for compatibility with sklearn API.

Returns:

X_newndarray, shape (n_matrices, n_channels, n_channels): Covariance matrices.

get_metadata_routing()¶

Get metadata routing of this object.

Please check User Guide on how the routing mechanism works.

Returns:

routingMetadataRequest: A MetadataRequest encapsulating routing information.

get_params(deep=True)¶

Get parameters for this estimator.

Parameters:

deepbool, default=True: If True, will return the parameters for this estimator and contained subobjects that are estimators.

Returns:

paramsdict: Parameter names mapped to their values.

set_output(*, transform=None)¶

Set output container.

See Introducing the set_output API for an example on how to use the API.

Parameters:

transform{“default”, “pandas”, “polars”}, default=None

Configure output of transform and fit_transform.

“default”: Default output format of a transformer
“pandas”: DataFrame output
“polars”: Polars output
None: Transform configuration is unchanged

Added in version 1.4: “polars” option was added.

Returns:

selfestimator instance: Estimator instance.

set_params(**params)¶

Set the parameters of this estimator.

The method works on simple estimators as well as on nested objects (such as Pipeline). The latter have parameters of the form <component>__<parameter> so that it’s possible to update each component of a nested object.

Parameters: