|h!8ddlZddlZddlmZddlmZdZdZ y)N)sparse)_ncut_cyctj|d}|jd}tj|df|j j }||fS)aReturns the diagonal and weight matrices of a graph. Parameters ---------- graph : RAG A Region Adjacency Graph. Returns ------- D : csc_array 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_array The weight matrix of the graph. ``W[i, j]`` is the weight of the edge joining `i` to `j`. csc)formatr)axis)shape)nxto_scipy_sparse_arraysumr dia_arrayr tocsc)graphWentriesDs R/var/www/html/test/engine/venv/lib/python3.12/site-packages/skimage/graph/_ncut.py DW_matricesrsQ$   u5AeeemG'1QWW5;;=A a4KcBtj|}tj||j|j |j |jd}|j|j}|j|j}||z ||z zS)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_array The diagonal matrix of the graph. W : csc_array 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)num_cols) nparrayrcut_costdataindicesindptrr r )cutrrrassoc_aassoc_bs r ncut_costr" s0 ((3-C  affaiiAGGTUJWHffSkooGffcTl G w 8g#5 66r) networkxr numpyrscipyrrrr"rrr(s2 7r