U ?h&@s<ddlZddlZddlmZddlmZddZddZ dS) N)sparse)_ncut_cycCs:tj|dd}|jdd}tj|df|jd}||fS)aReturns 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)formatr)Zaxis)shape)nxZto_scipy_sparse_arraysumrZ dia_matrixrZtocsc)graphWentriesDr E/var/www/html/venv/lib/python3.8/site-packages/skimage/graph/_ncut.py 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) nparrayrcut_costdataindicesZindptrrr)cutr r rZassoc_aZassoc_br r r ncut_cost s   r) ZnetworkxrnumpyrZscipyrrrrr r r rs