tedana.decomposition.tedica

tedica(n_components, dd, fixed_seed)[source]

Performs ICA on dd and returns mixing matrix

Parameters:
  • n_components (int) – Number of components retained from PCA decomposition
  • dd ((S x T) numpy.ndarray) – Dimensionally reduced optimally combined functional data, where S is samples and T is time
  • fixed_seed (int) – Seed for ensuring reproducibility of ICA results
Returns:

mmix – Mixing matrix for converting input data to component space, where C is components and T is the same as in dd
Return type:

(C x T) numpy.ndarray

Notes

Uses sklearn implementation of FastICA for decomposition