nimare.decode.continuous.CorrelationDistributionDecoder

class CorrelationDistributionDecoder(feature_group=None, features=None, frequency_threshold=0.001, target_image='z')

Decode an unthresholded image by correlating the image with images from all studies labeled with specific features.

Parameters

• feature_group (str) – Feature group

• features (list) – Features

• frequency_threshold (float) – Frequency threshold

• target_image ({‘z’, ‘con’}) – Name of meta-analysis results image to use for decoding

Warning

Coefficients from correlating two maps have very large degrees of freedom, so almost all results will be statistically significant. Do not attempt to evaluate results based on significance.

fit(dataset)

Fit Estimator to Dataset.

Parameters

dataset (nimare.dataset.Dataset) – Dataset object to analyze.

Returns

nimare.results.MetaResult – Results of Estimator fitting.

Notes

The fit method is a light wrapper that runs input validation and preprocessing before fitting the actual model. Estimators’ individual “fitting” methods are implemented as _fit, although users should call fit.

get_params(deep=True)

Get parameters for this estimator.

Parameters

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

Returns

params (mapping of string to any) – Parameter names mapped to their values.

classmethod load(filename, compressed=True)

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)

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)

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(img)

Correlate target image with each map associated with each feature.

Parameters

img (nibabel.nifti1.Nifti1Image) – Image to decode. Must be in same space as dataset.

Returns

out_df (pandas.DataFrame) – DataFrame with one row for each feature and two columns: “feature” and “r”.