tedana.io.writeresults

writeresults(data_optcom, mask, component_table, mixing, io_generator, mixing_orig=None)[source]

Denoise ts and save all resulting files to disk.

Parameters:

  • data_optcom ((Mb x T) array_like) – Time series to denoise and save to disk

  • 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 two columns: “component” and “classification”.

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

  • io_generator (tedana.io.OutputGenerator) – Reference image to dictate how outputs are saved to disk

  • mixing_orig ((T x C) array_like or None, optional) – Non-orthogonalized mixing matrix. If defined, it will be used for the component maps, but not for denoising.

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-ICA_stat-z_components.nii.gz

Z-normalized 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.

desc-ICAOrth_components.nii.gz

Spatial component maps for all components from orthogonalized mixing matrix. Only created if tedort and verbose are enabled.