mne.decoding.EMS#

class mne.decoding.EMS[source]#

Transformer to compute event-matched spatial filters.

This version of EMS [1] operates on the entire time course. No time window needs to be specified. The result is a spatial filter at each time point and a corresponding time course. Intuitively, the result gives the similarity between the filter at each time point and the data vector (sensors) at that time point.

Note

EMS only works for binary classification.

References

Attributes:

filters_ndarray, shape (n_channels, n_times)

The set of spatial filters.

classes_ndarray, shape (n_classes,)

The target classes.

Methods

fit(X, y)	Fit the spatial filters.
fit_transform(X[, y])	Fit to data, then transform it.
get_params([deep])	Get the estimator params.
set_params(**params)	Set parameters (mimics sklearn API).
transform(X)	Transform the data by the spatial filters.

fit(X, y)[source]#

Fit the spatial filters.

Parameters:

Xarray, shape (n_epochs, n_channels, n_times)

The training data.

yarray of int, shape (n_epochs)

The target classes.

Returns:

selfinstance of EMS

Returns self.

Examples using fit:

Compute effect-matched-spatial filtering (EMS)

Compute effect-matched-spatial filtering (EMS)

fit_transform(X, y=None, **fit_params)[source]#

Fit to data, then transform it.

Fits transformer to X and y with optional parameters fit_params, and returns a transformed version of X.

Parameters:

Xarray, shape (n_samples, n_features)

Training set.

yarray, shape (n_samples,)

Target values or class labels.

**fit_paramsdict

Additional fitting parameters passed to the fit method..

Returns:

X_newarray, shape (n_samples, n_features_new)

Transformed array.

get_params(deep=True)[source]#

Get the estimator params.

Parameters:

deepbool

Deep.

set_params(**params)[source]#

Set parameters (mimics sklearn API).

Parameters:

**paramsdict

Extra parameters.

Returns:

instobject

The instance.

transform(X)[source]#

Transform the data by the spatial filters.

Parameters:

Xarray, shape (n_epochs, n_channels, n_times)

The input data.

Returns:

Xarray, shape (n_epochs, n_times)

The input data transformed by the spatial filters.

Examples using transform:

Compute effect-matched-spatial filtering (EMS)

Compute effect-matched-spatial filtering (EMS)

Examples using mne.decoding.EMS#

Decoding (MVPA)

Decoding (MVPA)

Compute effect-matched-spatial filtering (EMS)

Compute effect-matched-spatial filtering (EMS)