nimare.results.MetaResult

class MetaResult(estimator, mask, maps=None)

Bases: object

Base class for meta-analytic results.

Parameters

• estimator (nimare.base.Estimator) – The Estimator used to generate the maps in the MetaResult.

• mask (Niimg-like or nilearn.input_data.base_masker.BaseMasker) – Mask for converting maps between arrays and images.

• maps (dict or None, optional) – Maps to store in the object. Default is None.

Variables

• estimator (nimare.base.Estimator) – The Estimator used to generate the maps in the MetaResult.

• masker (nilearn.input_data.NiftiMasker or similar) – Masker object.

• maps (dict) – Keys are map names and values are arrays.

copy()

Return copy of result object.

get_map(name, return_type='image')

Get stored map as image or array.

Parameters

• name (str) – Name of the map. Used to index self.maps.

• return_type ({‘image’, ‘array’}, optional) – Whether to return a niimg (‘image’) or a numpy array. Default is ‘image’.

save_maps(output_dir='.', prefix='', prefix_sep='_', names=None)

Save results to files.

Parameters

• output_dir (str, optional) – Output directory in which to save results. If the directory doesn’t exist, it will be created. Default is current directory.

• prefix (str, optional) – Prefix to prepend to output file names. Default is None.

• prefix_sep (str, optional) – Separator to add between prefix and default file names. Default is _.

• names (None or list of str, optional) – Names of specific maps to write out. If None, save all maps. Default is None.

Examples using nimare.results.MetaResult

Using Neurovault Statistical Maps in NiMARE

Run coordinate-based subtraction and conjunction analyses

Run image-based meta-analyses on 21 pain studies

Run coordinate-based meta-analyses on 21 pain studies

Simulate data for coordinate based meta-analysis (CBMA)

Test combinations of kernels and estimators for coordinate-based meta-analyses.