nimare.parcellate.cbp.ImCBP

class ImCBP(dataset, ids)[source]

Image-based coactivation-based parcellation

Warning

This method is not yet implemented.

fit(target_mask, n_parcels=2)[source]
Parameters

  • target_mask (img_like) – Image with binary mask for region of interest to be parcellated.

  • n_parcels (int or array_like of int, optional) – Number of parcels to generate for ROI. If array_like, each parcel number will be evaluated and results for all will be returned. Default is 2.

  • n_iters (int, optional) – Number of iterations to run for each parcel number. Default is 10000.

  • n_cores (int, optional) – Number of cores to use for model fitting.

Returns

results

get_params(deep=True)[source]

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)[source]

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)[source]

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)[source]

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