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1 {-| Module : Gargantext.Viz.Graph.MaxClique
2 Description : MaxCliques function
3 Copyright : (c) CNRS, 2017-Present
4 License : AGPL + CECILL v3
5 Maintainer : team@gargantext.org
6 Stability : experimental
7 Portability : POSIX
8
9 - First written by Bruno Gaume in Python (see below for details)
10 - Then written by Alexandre Delanoë in Haskell (see below for details)
11
12 # By Bruno Gaume:
13 def fast_maximal_cliques(g):
14
15 def rec_maximal_cliques(g, subv):
16 mc = []
17 if subv == []: # stop condition
18 return [[]]
19 else :
20 for i in range(len(subv)):
21 newsubv = [j for j in subv[i+1:len(subv)]
22 if (j in g.neighbors(subv[i]))]
23 mci = rec_maximal_cliques(g, newsubv)
24 for x in mci:
25 x.append(subv[i])
26 mc.append(x)
27 return mc
28
29 def purge(clust):
30 clustset = [set(x) for x in clust]
31 new_clust = []
32 for i in range(len(clustset)):
33 ok = True
34 for j in range(len(clustset)):
35 if clustset[i].issubset(clustset[j]) and (not (len(clustset[i]) == len(clustset[j])) ):
36 ok = False
37 if ok and (not (clustset[i] in new_clust)):
38 new_clust.append(clustset[i])
39 return [list(x) for x in new_clust]
40
41 # to optimize : rank the vertices on the degrees
42 subv = [(v.index, v.degree()) for v in g.vs()]
43 subv.sort(key = lambda z:z[1])
44 subv = [x for (x, y) in subv]
45 return purge(rec_maximal_cliques(g, subv))
46
47 -}
48
49
50 {-# LANGUAGE NoImplicitPrelude #-}
51
52 module Gargantext.Viz.Graph.MaxClique
53 where
54
55 import Gargantext.Prelude
56 import Data.List (sortOn, nub, concat, length)
57 import Data.Set (Set)
58 import Data.Set (fromList, toList, isSubsetOf)
59 import Data.Graph.Inductive hiding (Graph, neighbors, subgraph, (&))
60 import Gargantext.Viz.Graph.FGL (Graph_Undirected, degree, neighbors, mkGraphUfromEdges)
61
62
63 type Graph = Graph_Undirected
64 type Neighbor = Node
65
66 {-
67 -- prefiltre
68 -- Texte -> Ngrams
69 -- Map Terms
70 -- pré-filtre: spécifiques
71 -- soit conditionnelle, matrice spécifiques
72 -- combien de voisins maximum avant le calcul de cliques (les génériques)
73 -- calcul maxcliques
74 -- calcul de densité/inclusion si graph gros
75 --
76 -- FIS: ensemble de termes un niveau du document
77 -- maxclique: ensemble de termes au niveau de l'ensemble du document
78
79 type Density = Double
80 maxCliques' :: [[Text]] -> Map (Set Ngrams) Density
81 maxCliques' = undefined
82 -}
83
84
85 maxCliques :: Graph -> [[Node]]
86 maxCliques g = map (\n -> subMaxCliques g (n:ns)) ns & concat & takeMax
87 where
88 ns :: [Node]
89 ns = sortOn (degree g) $ nodes g
90
91 subMaxCliques :: Graph -> [Node] -> [[Node]]
92 subMaxCliques _ [] = [[]]
93 subMaxCliques g' (x:xs) = add x $ subMaxCliques g' ns'
94 where
95 ns' = [n | n <- xs, elem n $ neighborsOut g' x]
96
97 add :: Node -> [[Node]] -> [[Node]]
98 add n [] = [[n]]
99 add n (m:ms) = [n:m] <> add n ms
100 -- | Note, it is same as :
101 -- add n ns = map (\m -> n : m) ns
102 -- -- (but using pattern matching and recursivity)
103 -- -- (map is redefined in fact)
104
105 -- | To be sure self is not in neighbors of self
106 -- (out to exclude the self)
107 neighborsOut :: Graph -> Node -> [Node]
108 neighborsOut g'' n = filter (/= n) $ neighbors g'' n
109
110
111 takeMax :: [[Node]] -> [[Node]]
112 takeMax = map toList
113 . purge
114 . map fromList
115 . sortOn length
116 . nub
117 where
118 purge :: [Set Node] -> [Set Node]
119 purge [] = []
120 purge (x:xs) = x' <> purge xs
121 where
122 x' = if all (== False) (map (isSubsetOf x) xs)
123 then [x]
124 else []
125
126
127 ------------------------------------------------------------------------
128 test_graph :: Graph
129 -- test_graph = mkGraphUfromEdges [(1,1), (2,2), (3,3)]
130 test_graph = mkGraphUfromEdges [(1,2), (3,3)]
131
132 test_graph' :: Graph
133 test_graph' = mkGraphUfromEdges [(1,2), (3,3), (3,2)]
134
135 test_graph'' :: Graph
136 test_graph'' = mkGraphUfromEdges [(1,2), (2,3), (1,3)]
137
138 test_graph''' :: Graph
139 test_graph''' = mkGraphUfromEdges [ (4,1)
140 , (4,2)
141 , (3,1)
142 , (3,2)
143 , (2,1)
144 ]