h/SrSSKJr SSKrSSKJr SSKJr SSK J r J r J r S/r \ "S5\ "S 5\ "S 5\RS S j5555rg) zAAsynchronous Fluid Communities algorithm for community detection.)CounterN) is_connected) NetworkXError)groupsnot_implemented_forpy_random_state asyn_fluidcdirected multigraphc0[U[5(d [S5eUS:d [S5e[U5(d [S5e[ U5U:a [S5eSn[ U5nUR U5 [USU5VVs0sHupgXv_M nnn0n 0n UHn SXU 'XIX'M Sn S n U (GaZS n U S- n [ U5nUR U5 UGH n [5nURXXU 05 X HnURXXU05 M S n[ UR55S:dMp[UR55nUR5VVs/sHunnUU- S :dMUPM nnnXU;aXnUS :XdMS n URU5nXU ==S-ss'XJX- XU 'UX'XU ==S- ss'XJX- XU 'GM# X:aO U (aGMZ[![#U5R55$s snnf![a GNAf=f![a GMOf=fs snnf![a Nf=f![a Nf=f) u[Returns communities in `G` as detected by Fluid Communities algorithm. The asynchronous fluid communities algorithm is described in [1]_. The algorithm is based on the simple idea of fluids interacting in an environment, expanding and pushing each other. Its initialization is random, so found communities may vary on different executions. The algorithm proceeds as follows. First each of the initial k communities is initialized in a random vertex in the graph. Then the algorithm iterates over all vertices in a random order, updating the community of each vertex based on its own community and the communities of its neighbors. This process is performed several times until convergence. At all times, each community has a total density of 1, which is equally distributed among the vertices it contains. If a vertex changes of community, vertex densities of affected communities are adjusted immediately. When a complete iteration over all vertices is done, such that no vertex changes the community it belongs to, the algorithm has converged and returns. This is the original version of the algorithm described in [1]_. Unfortunately, it does not support weighted graphs yet. Parameters ---------- G : NetworkX graph Graph must be simple and undirected. k : integer The number of communities to be found. max_iter : integer The number of maximum iterations allowed. By default 100. seed : integer, random_state, or None (default) Indicator of random number generation state. See :ref:`Randomness`. Returns ------- communities : iterable Iterable of communities given as sets of nodes. Notes ----- k variable is not an optional argument. References ---------- .. [1] Parés F., Garcia-Gasulla D. et al. "Fluid Communities: A Competitive and Highly Scalable Community Detection Algorithm". [https://arxiv.org/pdf/1703.09307.pdf]. zk must be an integer.rzk must be greater than 0.z+Fluid Communities require connected Graphs.z,k cannot be bigger than the number of nodes.g?NTFg-C6?) isinstanceintrrlenlistshuffle enumeraterupdateKeyErrorkeysmaxvaluesitemschoiceiterr)Gkmax_iterseed max_densityverticesin communitiesdensitycom_to_numverticesvertex iter_countcont com_countervnew_commax_freqcomfreqbest_communitiess Z/var/www/html/env/lib/python3.13/site-packages/networkx/algorithms/community/asyn_fluid.pyr r st a  344 q5788 ??IJJ 1vzJKKKAwHLL$-hrl$;<$;DA14$;K<G23v./'2 #$J D a 7 XF!)K ""K$7VAT9U#VWY&& A8O'PQ G;##%&*{1134&1%6%6%8$%8 T 461%8!$ "*.>>"-"5b=D"kk*:;G*v+>?1D?'[=P*QQ F 34 +2K'&6':;q@;#9L&MM/0]d  s $v {#**, --I=*     $ $sZI I#I I2"I2, I8J II I/.I/8 JJ JJ)dN)__doc__ collectionsrnetworkxnxnetworkx.algorithms.componentsrnetworkx.exceptionrnetworkx.utilsrrr__all__ _dispatchabler r3r@sdG7,GG /Z \"F.#!F.r?