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_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_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.