tedana.io
.writeresults
- writeresults(ts, mask, comptable, mmix, io_generator)[source]
Denoise ts and save 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 ((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”.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
ref_img (
str
or img_like) – Reference image to dictate how outputs are saved to disk
See also
tedana.io.write_split_ts
Writes out time series files
Generated Files
Filename
Content
desc-denoised_bold.nii.gz
Denoised time series.
desc-optcomAccepted_bold.nii.gz
High-Kappa time series. (only with verbose)
desc-optcomRejected_bold.nii.gz
Low-Kappa time series. (only with verbose)
desc-ICA_components.nii.gz
Spatial component maps for all components.
desc-ICAAccepted_components.nii.gz
Spatial component maps for accepted components.
desc-ICAAccepted_stat-z_components.nii.gz
Z-normalized spatial component maps for accepted components.