Handle single sample output from FeatureFunctionTransformer to support scikit-learn 1.7.2 and later#97
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jbschiratti merged 1 commit intomne-tools:masterfrom Oct 17, 2025
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…t scikit-learn 1.7.2 and later
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LGTM, thank you @rcmdnk for fixing this! Feel free to merge it
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…t scikit-learn 1.7.2 and later (mne-tools#97)
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From scikit-learn 1.7.2, transformers used within FeatureUnion are required to return 2-dimensional outputs instead of 1-dimensional ones.
See the release notes:
https://scikit-learn.org/stable/whats_new/v1.7.html#sklearn-pipeline
Since all
compute_functions return 1-D arrays,extract_featuresnow raises an error such as:This PR fixes the output dimension of FeatureFunctionTransformer.transform to always be 2-D, rather than modifying each compute_ function.
This approach allows users to keep their custom feature-extraction functions unchanged.