wgddlZddlZddgZejddddZejddddZy) Nedge_betweenness_partition'edge_current_flow_betweenness_partitionweight) edge_attrsrc6|dkrtjd|dk(r t|gS|t|k(r|Dcgc]}|hc}S|t|kDrtjd|j }t tj |}t||krjtj||}t||j}|j|t tj |}t||krj|Scc}w)anPartition created by iteratively removing the highest edge betweenness edge. This algorithm works by calculating the edge betweenness for all edges and removing the edge with the highest value. It is then determined whether the graph has been broken into at least `number_of_sets` connected components. If not the process is repeated. Parameters ---------- G : NetworkX Graph, DiGraph or MultiGraph Graph to be partitioned number_of_sets : int Number of sets in the desired partition of the graph weight : key, optional, default=None The key to use if using weights for edge betweenness calculation Returns ------- C : list of sets Partition of the nodes of G Raises ------ NetworkXError If number_of_sets is <= 0 or if number_of_sets > len(G) Examples -------- >>> G = nx.karate_club_graph() >>> part = nx.community.edge_betweenness_partition(G, 2) >>> {0, 1, 3, 4, 5, 6, 7, 10, 11, 12, 13, 16, 17, 19, 21} in part True >>> { ... 2, ... 8, ... 9, ... 14, ... 15, ... 18, ... 20, ... 22, ... 23, ... 24, ... 25, ... 26, ... 27, ... 28, ... 29, ... 30, ... 31, ... 32, ... 33, ... } in part True See Also -------- edge_current_flow_betweenness_partition Notes ----- This algorithm is fairly slow, as both the calculation of connected components and edge betweenness relies on all pairs shortest path algorithms. They could potentially be combined to cut down on overall computation time. References ---------- .. [1] Santo Fortunato 'Community Detection in Graphs' Physical Reports Volume 486, Issue 3-5 p. 75-174 http://arxiv.org/abs/0906.0612 rnumber_of_sets must be >0 number_of_sets must be <= len(G)rkey) nx NetworkXErrorsetlencopylistconnected_componentsedge_betweenness_centralitymaxget remove_edge)Gnumber_of_setsrnH partitionrankingedges k/home/mcse/projects/flask/flask-venv/lib/python3.12/site-packages/networkx/algorithms/community/divisive.pyrr sZ:;;AxQAABB AR,,Q/0I i.> )006B7 , t0034 i.> )  s Dc(|dkrtjd|dk(r t|gS|t|k(r|Dcgc]}|hc}S|t|kDrtjdt j tj d|}|j}ttj|}t|dkDr-|Dcgc]!}|j|j#}}n|g}i} |D]} | j|| t||krYt| | j} t||D]"\}} | d|vs| j| | | =ttj| } t| dkDrt!| t} | j| j}||}|j#D]\}}|| || vr|n|ddd <|j%| |j%|| j'| |j)| || }|j#D]\}}|| || vr|n|ddd <nt||krY|Scc}wcc}w) a%Partition created by removing the highest edge current flow betweenness edge. This algorithm works by calculating the edge current flow betweenness for all edges and removing the edge with the highest value. It is then determined whether the graph has been broken into at least `number_of_sets` connected components. If not the process is repeated. Parameters ---------- G : NetworkX Graph, DiGraph or MultiGraph Graph to be partitioned number_of_sets : int Number of sets in the desired partition of the graph weight : key, optional (default=None) The edge attribute key to use as weights for edge current flow betweenness calculations Returns ------- C : list of sets Partition of G Raises ------ NetworkXError If number_of_sets is <= 0 or number_of_sets > len(G) Examples -------- >>> G = nx.karate_club_graph() >>> part = nx.community.edge_current_flow_betweenness_partition(G, 2) >>> {0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12, 13, 16, 17, 19, 21} in part True >>> {8, 14, 15, 18, 20, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33} in part True See Also -------- edge_betweenness_partition Notes ----- This algorithm is extremely slow, as the recalculation of the edge current flow betweenness is extremely slow. References ---------- .. [1] Santo Fortunato 'Community Detection in Graphs' Physical Reports Volume 486, Issue 3-5 p. 75-174 http://arxiv.org/abs/0906.0612 rr r r F) normalizedrr N)rrrr functoolspartial(edge_current_flow_betweenness_centralityrrrsubgraphupdaterrziprminitemsappendremove_nodes_fromdifference_update)rrrrrankrrcc Hcc_subgraphsrHccr splitcc_listcc_newHcc_newnewranksers r rrksr:;; 1 Ax 3q6 ! #a& ABB    33f D AR,,Q/0I 9~9BC2B,,.C C G"tCy!" i.> )7 ,9m4 GBAw"}&DM#B$;$;C$@A |$q( 37F!ll62779G#G}H ( 0D1BCQ'\q2w?D$$V,!((1))&1((09$NN,@DAq>?GgA1TrT7;@1  i.> )6 _ Ds J &J)r$networkxr__all__ _dispatchablerrr r>sg!-  X&<@\'\~X&IMl'lr=