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Handle single sample output from FeatureFunctionTransformer to support scikit-learn 1.7.2 and later #97

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Merged
jbschiratti merged 1 commit into from
Oct 17, 2025
Merged

Handle single sample output from FeatureFunctionTransformer to support scikit-learn 1.7.2 and later #97

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4 changes: 3 additions & 1 deletion mne_features/feature_extraction.py
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Original file line number Diff line number Diff line change
Expand Up @@ -62,7 +62,7 @@ def transform(self, X):

Returns
-------
X_out : ndarray, shape (n_output_func,)
X_out : ndarray, shape (1, n_output_func)
Usually, ``n_output_func`` will be equal to ``n_channels`` for most
univariate feature functions and to
``(n_channels * (n_channels + 1)) // 2`` for most bivariate feature
Expand All @@ -71,6 +71,8 @@ def transform(self, X):
"""
X_out = super(FeatureFunctionTransformer, self).transform(X)
self.output_shape_ = X_out.shape[0]
if X_out.ndim == 1:
X_out = X_out[np.newaxis, :]
if not hasattr(self, 'feature_names_'):
func_name = _get_func_name(self.func).replace('compute_', '')
if (func_name in get_univariate_func_names() and
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