pyriemann.channelselection.FlatChannelRemover

class pyriemann.channelselection.FlatChannelRemover

Finds and removes flat channels.

Attributes:

channels_ndarray, shape (n_good_channels)

The indices of the non-flat channels.

__init__(*args, **kwargs)

fit(X, y=None)

Find flat channels.

Parameters:

Xndarray, shape (n_matrices, n_channels, n_times)

Multi-channel time-series.

yNone

Not used, here for compatibility with sklearn API.

Returns:

Xndarray, shape (n_matrices, n_good_channels, n_times)

Multi-channel time-series without flat channels.

fit_transform(X, y=None)

Find and remove flat channels.

Parameters:

Xndarray, shape (n_matrices, n_channels, n_times)

Multi-channel time-series.

yNone

Not used, here for compatibility with sklearn API.

Returns:

Xndarray, shape (n_matrices, n_good_channels, n_times)

Multi-channel time-series without flat channels.

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 sphx_glr_auto_examples_miscellaneous_plot_set_output.py for an example on how to use the API.

Parameters:

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

Configure output of transform and fit_transform.

• “default”: Default output format of a transformer

• “pandas”: DataFrame output

• None: Transform configuration is unchanged

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:

**paramsdict

Estimator parameters.

Returns:

selfestimator instance

Estimator instance.

transform(X)

Remove flat channels.

Parameters:

Xndarray, shape (n_matrices, n_channels, n_times)

Multi-channel time-series.

Returns:

Xndarray, shape (n_matrices, n_good_channels, n_times)

Multi-channel time-series without flat channels.