modifié : README.md

	for e in G.get_edgelist():

	    SizeLine.append(G.edge_connectivity(e[0],e[1]))

L’algorithme multilevel

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	# les paramètres d'affichage

	visual_style3 = {}

	visual_style3["vertex_label"] = labels

	visual_style3["margin"] = 40

	#visual_style3["vertex_color"]="#33FFF3"

	#visual_style3["vertex_color"]='red'

	visual_style3["vertex_label_size"]=12

	visual_style3["vertex_size"]= [i*2 for i in SizeMarkers]

	visual_style3["vertex_label_dist"]=1

	#visual_style3["vertex_label_color"]="red"

	visual_style3["bbox"] = (1000, 1000)

	visual_style3["edge_color"]="gray" # couleurs prédéfinies : brown, gray ... cf http://www.proftnj.com/RGB3.htm

	visual_style3["edge_width"] = [i/8 for i in SizeLine]

	visual_style3["title"] = "Mot : "+ mot.upper()

	visual_style3["legend"] = "Mot : "+ mot.upper()

Les différents algorithmes 

--------------------------

	comms = G.community_multilevel()

	igraph.plot(comms,  mot+"-multilevelNoMarkGroups.svg", **visual_style3)

	comms = G.community_infomap()

	igraph.plot(comms,  mot+"-infomapNoMarkGroups.svg", mark_groups = False, **visual_style3)

	comms = G.community_fastgreedy()

	visual_style3["vertex_size"] = 2*igraph.degree(G3)

	igraph.plot(comms,  mot+"-fastgreedy.svg", mark_groups = True, **visual_style3)

	comms = G.community_leading_eigenvector(clusters=6)

	igraph.plot(comms,  mot+"-leading-eigenvector.svg", mark_groups = True, **visual_style3)

L’algorithme InfoMap

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