alphacsc.utils.split_signal#
- alphacsc.utils.split_signal(X, n_splits=1, apply_window=True)#
Split the signal in
n_splitschunks for faster training.This function can be used to accelerate the dictionary learning algorithm by creating independent chunks that can be processed in parallel. This can bias the estimation and can create border artifacts so the number of chunks should be kept as small as possible (e.g. equal to
n_jobs).Also, it is advised to not use the result of this function to call the
DictionaryLearning.transformmethod, as it would return an approximate reduction of the original signal in the sparse basis.Note that this is a lossy operation, as all chunks will have length
n_times // n_splitsand the lastn_times % n_splitssamples are discarded.- Parameters
- Xndarray, shape (n_channels, n_times) or (1, n_channels, n_times)
Signal to be split. It should be a single signal.
- n_splitsint (default: 1)
Number of splits to create from the original signal. Default is 1.
- apply_windowbool (default: True)
If set to True (default), a tukey window is applied to each split to reduce the border artifacts by reducing the weights of the chunk borders.