braindecode.datautil.create_from_X_y(X, y, drop_last_window, sfreq=None, ch_names=None, window_size_samples=None, window_stride_samples=None)

Create a BaseConcatDataset of WindowsDatasets from X and y to be used for decoding with skorch and braindecode, where X is a list of pre-cut trials and y are corresponding targets.

X: array-like

list of pre-cut trials as n_trials x n_channels x n_times

y: array-like

targets corresponding to the trials

sfreq: common sampling frequency of all trials
ch_names: array-like

channel names of the trials

drop_last_window: bool

whether or not have a last overlapping window, when windows/windows do not equally divide the continuous signal

window_size_samples: int

window size

window_stride_samples: int

stride between windows

windows_datasets: BaseConcatDataset

X and y transformed to a dataset format that is compatible with skorch and braindecode

Examples using braindecode.datautil.create_from_X_y