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    �ù»jš  ã                   @   s`   d Z ddlZddlmZ ddlmZ ddlmZ ddl	m
Z
 ddlmZmZ G d	d
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eƒZdS )zY
Feature agglomeration. Base classes and functions for performing feature
agglomeration.
é    N)Úissparseé   )ÚTransformerMixin)Úmetadata_routing)Ú"_deprecate_Xt_in_inverse_transform)Úcheck_is_fittedÚvalidate_datac                   @   s2   e Zd ZdZdejiZdd„ Zd	ddœdd„ZdS )
ÚAgglomerationTransformzH
    A class for feature agglomeration via the transform interface.
    ÚXtc                    sŽ   t ˆƒ tˆˆ dd�‰ ˆjtjkrbtˆ ƒsbt ˆj¡‰ˆ jd }t 	‡ ‡‡fdd„t
|ƒD ƒ¡}n(‡ ‡fdd„t ˆj¡D ƒ}t 	|¡j}|S )aì  
        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)Úresetr   c              	      s*   g | ]"}t  ˆjˆ |d d …f ¡ˆ ‘qS )N)ÚnpÚbincountÚlabels_)Ú.0Úi©ÚXÚselfÚsize© úLE:\soccer\ml_env\Lib\site-packages\sklearn/cluster/_feature_agglomeration.pyÚ
<listcomp>8   ó    z4AgglomerationTransform.transform.<locals>.<listcomp>c                    s,   g | ]$}ˆj ˆ d d …ˆj|kf dd�‘qS )Né   )Zaxis)Úpooling_funcr   )r   Úl)r   r   r   r   r   ;   s   ÿ)r   r   r   r   Úmeanr   r   r   ÚshapeÚarrayÚrangeÚuniqueÚT)r   r   Z	n_samplesZnXr   r   r   Ú	transform    s    
ÿ
þz AgglomerationTransform.transformN)r
   c                C   s2   t ||ƒ}t| ƒ tj| jdd�\}}|d|f S )að  
        Inverse the transformation and return a vector of size `n_features`.

        Parameters
        ----------
        X : array-like of shape (n_samples, n_clusters) or (n_clusters,)
            The values to be assigned to each cluster of samples.

        Xt : array-like of shape (n_samples, n_clusters) or (n_clusters,)
            The values to be assigned to each cluster of samples.

            .. deprecated:: 1.5
                `Xt` was deprecated in 1.5 and will be removed in 1.7. Use `X` instead.

        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)Zreturn_inverse.)r   r   r   r    r   )r   r   r
   ZunilZinverser   r   r   Úinverse_transformB   s    
z(AgglomerationTransform.inverse_transform)N)	Ú__name__Ú
__module__Ú__qualname__Ú__doc__r   ZUNUSEDZ<_AgglomerationTransform__metadata_request__inverse_transformr"   r#   r   r   r   r   r	      s   
"r	   )r'   Únumpyr   Zscipy.sparser   Úbaser   Úutilsr   Zutils.deprecationr   Zutils.validationr   r   r	   r   r   r   r   Ú<module>   s   	