U ƒ±Ëh&ã@s<ddlZddlZddlmZddlmZdd„Zdd„Z dS) éN)Úsparseé)Ú_ncut_cycCs:tj|dd}|jdd}tj|df|jd ¡}||fS)aÀReturns the diagonal and weight matrices of a graph. Parameters ---------- graph : RAG A Region Adjacency Graph. Returns ------- D : csc_matrix The diagonal matrix of the graph. ``D[i, i]`` is the sum of weights of all edges incident on `i`. All other entries are `0`. W : csc_matrix The weight matrix of the graph. ``W[i, j]`` is the weight of the edge joining `i` to `j`. Zcsc)Úformatr)Zaxis)Úshape)ÚnxZto_scipy_sparse_arrayÚsumrZ dia_matrixrZtocsc)ÚgraphÚWÚentriesÚD©r ú7/tmp/pip-unpacked-wheel-gtraehzf/skimage/graph/_ncut.pyÚ DW_matricess rcCsXt |¡}tj||j|j|j|jdd}|j| ¡}|j| ¡}||||S)a~Returns the N-cut cost of a bi-partition of a graph. Parameters ---------- cut : ndarray The mask for the nodes in the graph. Nodes corresponding to a `True` value are in one set. D : csc_matrix The diagonal matrix of the graph. W : csc_matrix The weight matrix of the graph. Returns ------- cost : float The cost of performing the N-cut. References ---------- .. [1] Normalized Cuts and Image Segmentation, Jianbo Shi and Jitendra Malik, IEEE Transactions on Pattern Analysis and Machine Intelligence, Page 889, Equation 2. r)Znum_cols) ÚnpÚarrayrÚcut_costÚdataÚindicesZindptrrr)Zcutr r rZassoc_aZassoc_br r rÚ ncut_cost s   r) ZnetworkxrZnumpyrZscipyrÚrrrr r r rÚs