7.13. Adding Data Dump Assets

junifer supports dumping nibabel.Nifti1Image and pandas.DataFrame which should cover most fMRI use cases. But, in case you work with other modalities like EEG, you can register your own data dump asset.

7.13.1. How to add a data dump asset

This example shows how to create a data dump asset for mne.io.Raw.

1. Check extending junifer on how to create a junifer extension if you have not done so.

2. Create the data registry in the extension script like so:

   from pathlib import Path
   
   from junifer.api.decorators import register_data_dump_asset
   from junifer.pipeline import BaseDataDumpAsset
   
   import mne
   
   @register_data_dump_asset([mne.io.Raw], [".fif", ".fif.gz"])
   class RawAsset(BaseDataDumpAsset):
       """Class for ``mne.io.Raw`` dumper."""
   
       def dump(self) -> None:
           self.data.save(self.path_without_ext.with_suffix(".raw.fif.gz"))
   
       @classmethod
       def load(cls: "RawAsset", path: Path) -> mne.io.Raw:
           return mne.io.Raw(path)
   

   • register_data_dump_asset() registers a class. The first argument is a list of types that the class is responsible for saving and the second argument is a list of file extensions that the class is responsible for loading.

   • Inheriting from junifer.pipeline.BaseDumpAsset takes care of the class acting as a data dump asset.

   • Method junifer.pipeline.BaseDumpAsset.dump and class method junifer.pipeline.BaseDumpAsset.load need to be implemented.