tedana.io
.denoise_ts
- denoise_ts(data, mmix, mask, comptable)[source]
Apply component classifications to data for denoising.
- Parameters
data ((S x T) array_like) – Input time series
mmix ((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 ((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 one column: “classification”.
- Returns
dnts ((S x T) array_like) – Denoised data (i.e., data with rejected components removed).
hikts ((S x T) array_like) – High-Kappa data (i.e., data composed only of accepted components).
lowkts ((S x T) array_like) – Low-Kappa data (i.e., data composed only of rejected components).