mne.decoding.EMS

class mne.decoding.EMS[source]

Transformer to compute event-matched spatial filters.

This version of EMS [R78ea2cca2302-1] 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

R78ea2cca2302-1

Aaron Schurger, Sebastien Marti, and Stanislas Dehaene, “Reducing multi-sensor data to a single time course that reveals experimental effects”, BMC Neuroscience 2013, 14:122

Attributes
filters_ndarray, shape (n_channels, n_times)

The set of spatial filters.

classes_ndarray, shape (n_classes,)

The target classes.

Methods

__hash__(self, /)

Return hash(self).

fit(self, X, y)

Fit the spatial filters.

fit_transform(self, X[, y])

Fit to data, then transform it.

get_params(self[, deep])

Get the estimator params.

set_params(self, \*\*params)

Set parameters (mimics sklearn API).

transform(self, X)

Transform the data by the spatial filters.

__hash__(self, /)

Return hash(self).

fit(self, 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:

fit_transform(self, 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.

**fit_paramsdict

Additional fitting parameters passed to self.fit.

Returns
X_newarray, shape (n_samples, n_features_new)

Transformed array.

get_params(self, deep=True)[source]

Get the estimator params.

Parameters
deepbool

Deep.

set_params(self, **params)[source]

Set parameters (mimics sklearn API).

Parameters
**paramsdict

Extra parameters.

Returns
instobject

The instance.

transform(self, 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: