tedana.io.split_ts

split_ts(data, mmix, mask, comptable)

Splits data time series into accepted component time series and remainder

Parameters:

• data ((S x T) array_like) – Input data, where S is samples and T is time
• mmix ((T x C) array_like) – Mixing matrix for converting input data to component space, where C is components and T is the same as in data
• mask ((S,) array_like) – Boolean mask array
• comptable ((C x X) pandas.DataFrame) – Component metric table. One row for each component, with a column for each metric. Requires at least two columns: “component” and “classification”.

Returns:

• hikts ((S x T) numpy.ndarray) – Time series reconstructed using only components in acc
• rest ((S x T) numpy.ndarray) – Original data with hikts removed