o tBhW @sDdZddlZddlmZddlmZddlmZGdddeZ dS) zY Feature agglomeration. Base classes and functions for performing feature agglomeration. N)TransformerMixin)check_is_fitted)issparsec@s eZdZdZddZddZdS)AgglomerationTransformzH A class for feature agglomeration via the transform interface. cstjddjtjkr2ts2tjjd}t fddt |D}|Sfddt jD}t |j }|S)a Transform a new matrix using the built clustering. Parameters ---------- X : array-like of shape (n_samples, n_features) or (n_samples, n_samples) A M by N array of M observations in N dimensions or a length M array of M one-dimensional observations. Returns ------- Y : ndarray of shape (n_samples, n_clusters) or (n_clusters,) The pooled values for each feature cluster. F)resetrc s*g|]}tj|ddfqS)N)npbincountlabels_).0iXselfsize}/var/www/html/riverr-enterprise-integrations-main/venv/lib/python3.10/site-packages/sklearn/cluster/_feature_agglomeration.py /s*z4AgglomerationTransform.transform..cs,g|]}jddj|kfddqS)N)axis) pooling_funcr )r l)rrrrr2s) r_validate_datarrmeanrr r shapearrayrangeuniqueT)rr n_samplesnXrr r transforms    z AgglomerationTransform.transformcCs(t|tj|jdd\}}|d|fS)a Inverse the transformation and return a vector of size `n_features`. Parameters ---------- Xred : array-like of shape (n_samples, n_clusters) or (n_clusters,) The values to be assigned to each cluster of samples. Returns ------- X : ndarray of shape (n_samples, n_features) or (n_features,) A vector of size `n_samples` with the values of `Xred` assigned to each of the cluster of samples. T)return_inverse.)rrrr )rXredunilinverserrrinverse_transform9s z(AgglomerationTransform.inverse_transformN)__name__ __module__ __qualname____doc__r!r&rrrrrs "r) r*numpyrbaserutils.validationr scipy.sparserrrrrrs