API¶
tedana.workflows
: Common workflows¶
tedana.workflows |
|
tedana.workflows.tedana_workflow (data, tes) |
Run the “canonical” TE-Dependent ANAlysis workflow. |
tedana.workflows.t2smap_workflow (data, tes) |
Estimate T2 and S0, and optimally combine data across TEs. |
tedana.model
: Modeling TE-dependence¶
tedana.model |
|
tedana.model.fit_decay (data, tes, mask, masksum) |
Fit voxel-wise monoexponential decay models to data |
tedana.model.fit_decay_ts (data, tes, mask, …) |
Fit voxel- and timepoint-wise monoexponential decay models to data |
tedana.model.fitmodels_direct (catd, mmix, …) |
Fit TE-dependence and -independence models to components. |
tedana.model.make_optcom (data, tes, mask[, …]) |
Optimally combine BOLD data across TEs. |
tedana.model.monoexponential |
Functions to estimate S0 and T2* from multi-echo data. |
tedana.model.fit |
Fit models. |
tedana.model.combine |
Functions to optimally combine data across echoes. |
tedana.decomposition
: Data decomposition¶
tedana.decomposition |
|
tedana.decomposition.tedpca (catd, OCcatd, …) |
Use principal components analysis (PCA) to identify and remove thermal noise from multi-echo data. |
tedana.decomposition.tedica (n_components, …) |
Performs ICA on dd and returns mixing matrix |
tedana.decomposition._utils |
Utility functions for tedana decomposition |
tedana.selection
: Component selection¶
tedana.selection |
|
tedana.selection.selcomps (seldict, mmix, …) |
Labels ICA components to keep or remove from denoised data |
tedana.selection._utils |
Utility functions for tedana.selection |
tedana.utils
: Utility functions¶
tedana.utils |
|
tedana.utils.io |
Functions to handle file input/output |
tedana.utils.utils |
Utilities for tedana package |