nimare.meta.kernel.Peaks2MapsKernel

class Peaks2MapsKernel(model_dir='auto')[source]

Bases: nimare.meta.kernel.KernelTransformer

Generate peaks2maps modeled activation images from coordinates.

Parameters

resample_to_mask (bool, optional) – If True, will resample the MA maps to the mask’s header. Default is True.

Warning

Peaks2MapsKernel is not intended for serious research. We strongly recommend against using it for any meaningful analyses.

get_params(deep=True)[source]

Get parameters for this estimator.

Parameters

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

Returns

params (dict) – 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

transform(dataset, masker=None, return_type='image')[source]

Generate modeled activation images for each Contrast in dataset.

Parameters

  • dataset (nimare.dataset.Dataset or pandas.DataFrame) – Dataset for which to make images. Can be a DataFrame if necessary.

  • masker (img_like, optional) – Only used if dataset is a DataFrame.

  • return_type ({‘array’, ‘image’, ‘dataset’}, optional) – Whether to return a numpy array (‘array’), a list of niimgs (‘image’), or a Dataset with MA images saved as files (‘dataset’). Default is ‘dataset’.

Returns

imgs ((C x V) numpy.ndarray or list of) – nibabel.Nifti1Image or nimare.dataset.Dataset If return_type is ‘array’, a 2D numpy array (C x V), where C is contrast and V is voxel. If return_type is ‘image’, a list of modeled activation images (one for each of the Contrasts in the input dataset). If return_type is ‘dataset’, a new Dataset object with modeled activation images saved to files and referenced in the Dataset.images attribute.

Variables

  • filename_pattern (str) – Filename pattern for MA maps that will be saved by the transformer.

  • image_type (str) – Name of the corresponding column in the Dataset.images DataFrame.

Examples using nimare.meta.kernel.Peaks2MapsKernel