obob_mne.decoding.GeneralizedTemporalAverage¶

class obob_mne.decoding.GeneralizedTemporalAverage(data_list)[source]¶

Create average instance of Temporal Generalization results.

Given a list of Temporal Generalization Results, this class computes the average of their weights and returns an instance of GeneralizedTemporalArray so you can plot the average scores and weights.

Parameters:	data_list (iterable of `GeneralizedTemporalArray`) – A list (or any other iterable) of `GeneralizedTemporalArray`

__init__(data_list)[source]¶

Methods

`__init__`(data_list)
`diagonal_as_temporal`()	Return the non-generalized results.
`get_temporal_from_training_interval`(tmin, tmax)	Average the scores of a training interval.
`plot_scores`([axes, show, cmap, colorbar, …])	Plot the scores as a Matrix.

Attributes

`chance_level`	float – The chance level of the classifier.
`info`	`Measurement info`
`must_be_equal`
`nave`	int – Number of epochs in the training set.
`nave_testing`	int – Number of epochs in the testing set.
`scores`	`numpy.ndarray` – The scores of the classification
`tmin`	float – tmin
`weights`	`numpy.ndarray` – The classifier weights