tedana.io.denoise_ts

denoise_ts(data, mixing, mask, component_table)[source]

Apply component classifications to data for denoising.

Parameters:

  • data ((Mb x T) array_like) – Input time series

  • mixing ((C x T) array_like) – Mixing matrix for converting input data to component space, where C is components and T is the same as in data

  • mask ((Mb,) array_like) – Boolean mask array

  • component_table ((C x X) pandas.DataFrame) – Component metric table. One row for each component, with a column for each metric. Requires at least one column: “classification”.

Returns:

  • dnts ((Mb x T) array_like) – Denoised data (i.e., data with rejected components removed).

  • hikts ((Mb x T) array_like) – High-Kappa data (i.e., data composed only of accepted components).

  • lowkts ((Mb x T) array_like) – Low-Kappa data (i.e., data composed only of rejected components).