Mercurial > repos > shellac > sam_consensus_v3
annotate env/lib/python3.9/site-packages/networkx/algorithms/community/kclique.py @ 0:4f3585e2f14b draft default tip
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author | shellac |
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date | Mon, 22 Mar 2021 18:12:50 +0000 |
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1 from collections import defaultdict |
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2 import networkx as nx |
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3 |
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4 __all__ = ["k_clique_communities"] |
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5 |
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6 |
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7 def k_clique_communities(G, k, cliques=None): |
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8 """Find k-clique communities in graph using the percolation method. |
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9 |
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10 A k-clique community is the union of all cliques of size k that |
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11 can be reached through adjacent (sharing k-1 nodes) k-cliques. |
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12 |
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13 Parameters |
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14 ---------- |
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15 G : NetworkX graph |
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16 |
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17 k : int |
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18 Size of smallest clique |
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19 |
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20 cliques: list or generator |
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21 Precomputed cliques (use networkx.find_cliques(G)) |
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22 |
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23 Returns |
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24 ------- |
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25 Yields sets of nodes, one for each k-clique community. |
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26 |
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27 Examples |
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28 -------- |
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29 >>> from networkx.algorithms.community import k_clique_communities |
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30 >>> G = nx.complete_graph(5) |
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31 >>> K5 = nx.convert_node_labels_to_integers(G, first_label=2) |
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32 >>> G.add_edges_from(K5.edges()) |
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33 >>> c = list(k_clique_communities(G, 4)) |
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34 >>> sorted(list(c[0])) |
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35 [0, 1, 2, 3, 4, 5, 6] |
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36 >>> list(k_clique_communities(G, 6)) |
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37 [] |
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38 |
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39 References |
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40 ---------- |
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41 .. [1] Gergely Palla, Imre Derényi, Illés Farkas1, and Tamás Vicsek, |
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42 Uncovering the overlapping community structure of complex networks |
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43 in nature and society Nature 435, 814-818, 2005, |
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44 doi:10.1038/nature03607 |
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45 """ |
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46 if k < 2: |
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47 raise nx.NetworkXError(f"k={k}, k must be greater than 1.") |
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48 if cliques is None: |
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49 cliques = nx.find_cliques(G) |
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50 cliques = [frozenset(c) for c in cliques if len(c) >= k] |
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51 |
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52 # First index which nodes are in which cliques |
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53 membership_dict = defaultdict(list) |
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54 for clique in cliques: |
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55 for node in clique: |
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56 membership_dict[node].append(clique) |
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57 |
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58 # For each clique, see which adjacent cliques percolate |
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59 perc_graph = nx.Graph() |
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60 perc_graph.add_nodes_from(cliques) |
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61 for clique in cliques: |
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62 for adj_clique in _get_adjacent_cliques(clique, membership_dict): |
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63 if len(clique.intersection(adj_clique)) >= (k - 1): |
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64 perc_graph.add_edge(clique, adj_clique) |
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65 |
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66 # Connected components of clique graph with perc edges |
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67 # are the percolated cliques |
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68 for component in nx.connected_components(perc_graph): |
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69 yield (frozenset.union(*component)) |
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70 |
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71 |
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72 def _get_adjacent_cliques(clique, membership_dict): |
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73 adjacent_cliques = set() |
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74 for n in clique: |
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75 for adj_clique in membership_dict[n]: |
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76 if clique != adj_clique: |
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77 adjacent_cliques.add(adj_clique) |
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78 return adjacent_cliques |