tedana.io.writeresults

writeresults(ts, mask, comptable, mmix, n_vols, fixed_seed, acc, rej, midk, empty, ref_img)[source]

Denoises ts and saves all resulting files to disk

Parameters:
  • ts ((S x T) array_like) – Time series to denoise and save to disk
  • mask ((S,) array_like) – Boolean mask array
  • comptable ((N x 5) array_like) – Array with columns denoting (1) index of component, (2) Kappa score of component, (3) Rho score of component, (4) variance explained by component, and (5) normalized variance explained by component
  • 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
  • n_vols (int) – Number of volumes in original time series
  • fixed_seed (int) – Integer value used in seeding ICA
  • acc (list) – Indices of accepted (BOLD) components in mmix
  • rej (list) – Indices of rejected (non-BOLD) components in mmix
  • midk (list) – Indices of mid-K (questionable) components in mmix
  • empty (list) – Indices of ignored components in mmix
  • ref_img (str or img_like) – Reference image to dictate how outputs are saved to disk

Notes

This function writes out several files:

Filename Content
ts_OC.nii Optimally combined 4D time series.
hik_ts_OC.nii High-Kappa time series. Generated by tedana.utils.io.write_split_ts().
midk_ts_OC.nii Mid-Kappa time series. Generated by tedana.utils.io.write_split_ts().
low_ts_OC.nii Low-Kappa time series. Generated by tedana.utils.io.write_split_ts().
dn_ts_OC.nii Denoised time series. Generated by tedana.utils.io.write_split_ts().
betas_OC.nii Full ICA coefficient feature set.
betas_hik_OC.nii Denoised ICA coefficient feature set.
feats_OC2.nii Z-normalized spatial component maps. Generated by tedana.utils.io.writefeats().
comp_table.txt Component table. Generated by tedana.utils.io.writect().