`nimare.base`.NiMAREBase

class NiMAREBase[source]

Bases: CacheMixin

Base class for NiMARE.

This class contains a few features that are useful throughout the library:

Custom __repr__ method for printing the object.
get_params from scikit-learn, with which parameters provided at __init__ can be viewed.
set_params from scikit-learn, with which parameters provided at __init__ can be overwritten. I’m not sure that this is actually used or useable in NiMARE.
save to save the object to a Pickle file.
load to load an instance of the object from a Pickle file.

TODO: Actually write/refactor class methods. They mostly come directly from sklearn https://github.com/scikit-learn/scikit-learn/blob/ 2a1e9686eeb203f5fddf44fd06414db8ab6a554a/sklearn/base.py#L141

Methods

`get_params`([deep])	Get parameters for this estimator.
`load`(filename[, compressed])	Load a pickled class instance from file.
`save`(filename[, compress])	Pickle the class instance to the provided file.
`set_params`(**params)	Set the parameters of this estimator.

get_params(deep=True)[source]

Get parameters for this estimator.

Parameters:: deep (bool, default=True) – If True, will return the parameters for this estimator and contained subobjects that are estimators.
Returns:: params – Parameter names mapped to their values.
Return type:: dict

classmethod load(filename, compressed=True)[source]

Load a pickled class instance from file.

Parameters:

filename (str) – Name of file containing object.
compressed (bool, default=True) – 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 – Loaded class object.

Return type:

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.