hSrSSKJr SSKrSSKJr SSKJrJ r J r S/r Sr \ "S5\ "S 5\R"S S 9S S j555rg)uBFunctions for computing the Kernighan–Lin bipartition algorithm.)countN) is_partition) BinaryHeapnot_implemented_forpy_random_statekernighan_lin_bisectionc#^^^ # [5[54=up#m [[5TT5H9upEn[U4SjU55nT UR XE(aUOU*5 M; U UU4SjnSn Sn U(aaU(aYUR 5upGU"X$5 UR 5upU"X;5 XU -- n U S- n XXK44v U(a U(aMWgggg7f)z This is a modified form of Kernighan-Lin, which moves single nodes at a time, alternating between sides to keep the bisection balanced. We keep two min-heaps of swap costs to make optimal-next-move selection fast. c3F># UHupTU(aUOU*v M g7f)N).0vwsides ]/var/www/html/env/lib/python3.13/site-packages/networkx/algorithms/community/kernighan_lin.py '_kernighan_lin_sweep..s >gda$q'Qr)g!c>TUHDup#TTUnURU5nUcM#USXLaU*OU-- nURX%S5 MF g)NT)getinsert) costs_xxyrcosts_ycost_ycostsedgesrs r _update_costs+_kernighan_lin_sweep.._update_costssY!HDADGnG[[^F!!W%7rQ??q$/ rN)rziprsumrpop)rrcosts0costs1uside_uedges_ucost_uritotcostr cost_vrs`` @r_kernighan_lin_sweepr/ s (\:<77NFU!%'477>g>> f Q&vg>80 AG VJJL f JJL f F?" Q1&   VV&V&s CC%!C%directedweight) edge_attrsc^[U5n[U5nURU5 [U5VVs0sHupxX_M n nnUcS/US--S/US-S---n OCUup[X U 45(d[ R"S5eS/U-n U H nSXU'M UR5(abUVVVs/sHPnXR5VVs/sH-unnX[U4SjUR5554PM/ snnPMR nnnnOPUVVVs/sH?oUR5VVs/sHunnXURTS54PM snnPMA nnnn[U5HIn[[UU 55n[!U5unnnUS:a OUSUHu nupSX'SX'M MK [#Xj5VVs1sHunnUS:XdMUiM n nn[#Xj5VVs1sHunnUS:XdMUiM n nnX4$s snnf![[ 4an [ R"S5U eSn A ff=fs snnfs snnnfs snnfs snnnfs snnfs snnf)uGPartition a graph into two blocks using the Kernighan–Lin algorithm. This algorithm partitions a network into two sets by iteratively swapping pairs of nodes to reduce the edge cut between the two sets. The pairs are chosen according to a modified form of Kernighan-Lin [1]_, which moves node individually, alternating between sides to keep the bisection balanced. Parameters ---------- G : NetworkX graph Graph must be undirected. partition : tuple Pair of iterables containing an initial partition. If not specified, a random balanced partition is used. max_iter : int Maximum number of times to attempt swaps to find an improvement before giving up. weight : key Edge data key to use as weight. If None, the weights are all set to one. seed : integer, random_state, or None (default) Indicator of random number generation state. See :ref:`Randomness`. Only used if partition is None Returns ------- partition : tuple A pair of sets of nodes representing the bipartition. Raises ------ NetworkXError If partition is not a valid partition of the nodes of the graph. References ---------- .. [1] Kernighan, B. W.; Lin, Shen (1970). "An efficient heuristic procedure for partitioning graphs." *Bell Systems Technical Journal* 49: 291--307. Oxford University Press 2011. Nrrr"zpartition must be two setszpartition invalidc3F># UHoRTS5v M g7f)r"N)r)r er2s rr*kernighan_lin_bisection..usDAuuVQ//r)lenlistshuffle enumerate TypeError ValueErrornx NetworkXErrorr is_multigraphitemsr$valuesrranger/minr#)G partitionmax_iterr2seednlabelsr,r indexrABerrar(drr6rmin_costmin_i_ss ` rrr+sj AA !WFLL'/ 0/daQT/E 0sa1f~A!| 44 JDAA1v&&""#67 7sQwADqN    DJJL (DAq3DDDE(   NT MSdjjl Cldaehfa( )l CV  8_)%67 Z% q= !&5MLAq&1DGDG* 6(3(tq!AF(A36(3(tq!AF(A3 4KQ 1:& J""#?@c I J   D  43seH#HI4I I"I=#I I I&#I&: I, I,I -II  II)N r2N)__doc__ itertoolsrnetworkxr>-networkx.algorithms.community.community_utilsrnetworkx.utilsrrr__all__r/ _dispatchablerr r!rr]s_HFKK $ %!>Z X&]'!]r!