This documentation is for development version 0.18.dev0.

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.

References

[1](1, 2) 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__($self, /) Return hash(self).
fit(X, y) Fit the spatial filters.
fit_transform(X[, y]) Fit to data, then transform it.
get_params([deep]) Get the estimator params.
set_params(**params) Set parameters (mimics sklearn API).
transform(X) Transform the data by the spatial filters.
__hash__($self, /)

Return hash(self).

fit(X, y)[source]

Fit the spatial filters.

Parameters:
X : array, shape (n_epochs, n_channels, n_times)

The training data.

y : array of int, shape (n_epochs)

The target classes.

Returns:
self : instance of EMS

Returns self.

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:
X : array, shape (n_samples, n_features)

Training set.

y : array, shape (n_samples,)

Target values.

Returns:
X_new : array, shape (n_samples, n_features_new)

Transformed array.

get_params(deep=True)[source]

Get the estimator params.

Parameters:
deep : bool

Deep.

set_params(**params)[source]

Set parameters (mimics sklearn API).

transform(X)[source]

Transform the data by the spatial filters.

Parameters:
X : array, shape (n_epochs, n_channels, n_times)

The input data.

Returns:
X : array, shape (n_epochs, n_times)

The input data transformed by the spatial filters.