`nimare.transforms`.ImageTransformer

class ImageTransformer(target, overwrite=False)[source]

Bases: NiMAREBase

A class to create new images from existing ones within a Dataset.

This class is a light wrapper around transform_images().

New in version 0.0.9.

Parameters:

target ({'z', 'p', 'beta', 'varcope'} or list) – Target image type. Multiple target types may be specified as a list.
overwrite (bool, optional) – Whether to overwrite existing files or not. Default is False.

See also

nimare.transforms.transform_images: The function called by this class.

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.
`transform`(dataset)	Generate images of the target type from other image types in a Dataset.

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.

Return type:: self

transform(dataset)[source]

Generate images of the target type from other image types in a Dataset.

Parameters:: dataset (Dataset) – A Dataset containing images and relevant metadata.
Returns:: new_dataset – A copy of the input Dataset, with new images added to its images attribute.
Return type:: Dataset