nimare.annotate.text2brain.Text2BrainModel

class Text2BrainModel(text_df, coordinates_df)

Generate a Text2Brain vector model.

Warning

This method is not yet implemented.

References

• Dockès, Jérôme, et al. “Text to brain: predicting the spatial distribution of neuroimaging observations from text reports.” International Conference on Medical Image Computing and Computer-Assisted Intervention. Springer, Cham, 2018. https://doi.org/10.1007/978-3-030-00931-1_67

get_params(deep=True)

Get parameters for this estimator.

Parameters

deep (boolean, optional) – If True, will return the parameters for this estimator and contained subobjects that are estimators.

Returns

params (mapping of string to any) – Parameter names mapped to their values.

classmethod load(filename, compressed=True)

Load a pickled class instance from file.

Parameters

• filename (str) – Name of file containing object.

• compressed (bool, optional) – If True, the file is assumed to be compressed and gzip will be used to load it. Otherwise, it will assume that the file is not compressed. Default = True.

Returns

obj (class object) – Loaded class object.

save(filename, compress=True)

Pickle the class instance to the provided file.

Parameters

• filename (str) – File to which object will be saved.

• compress (bool, optional) – If True, the file will be compressed with gzip. Otherwise, the uncompressed version will be saved. Default = True.

set_params(**params)

Set the parameters of this estimator.

The method works on simple estimators as well as on nested objects (such as pipelines). The latter have parameters of the form <component>__<parameter> so that it’s possible to update each component of a nested object.

Returns

self