obob_mne.decoding.GeneralizedTemporalFromCollection¶
-
class
obob_mne.decoding.
GeneralizedTemporalFromCollection
(data_list, raw_scores, weights)[source]¶ Base class for Temporal Generalization data from multiple subjects.
The individual elements must match in number of classes, times etc.
Parameters: - data_list (iterable of
GeneralizedTemporalArray
) – A list (or any other iterable) ofGeneralizedTemporalArray
- raw_scores (
numpy.ndarray
shape (n_channels, n_times) or (n_folds, n_channels, n_times)) – The already processed (i.e., averaged, statistically tested) scores. - weights (
numpy.ndarray
shape (n_channels, n_times)) – The already processed (i.e., averaged, statistically tested) weights.
Methods
__init__
(data_list, raw_scores, weights)diagonal_as_temporal
()Return the non-generalized results. drop_channels
(chs)Drop the channels from the weights. 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
The chance level of the classifier. info
Measurement info
must_be_equal
nave
Number of epochs in the training set. nave_testing
Number of epochs in the testing set. scores
The scores of the classification tmin
tmin weights
The classifier weights - data_list (iterable of