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().

Added 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

Examples using nimare.transforms.ImageTransformer

The NiMARE Dataset object

The NiMARE Dataset object

Use NeuroVault statistical maps in NiMARE

Use NeuroVault statistical maps in NiMARE

Transform images into coordinates

Transform images into coordinates

Image-based meta-analysis algorithms

Image-based meta-analysis algorithms

Compare image and coordinate based meta-analyses

Compare image and coordinate based meta-analyses