Commit 2b91a915 authored by Laurette Chardon's avatar Laurette Chardon
Browse files

Modifications qui seront validées : 

	modifié :         Clusterisation2D_RevueSyntSem21.py
	nouveau fichier : adjustedrand.png
	nouveau fichier : nmi.png
	nouveau fichier : rand.png
	nouveau fichier : split.png
	nouveau fichier : vi.png
parent 88e552d2

Clusterisation2D_RevueSyntSem21.py

+86 −22
Changes for Clusterisation2D_RevueSyntSem21.py: 86 added lines, 22 removed lines.
Original line number Diff line number Diff line
@@ -8,7 +8,7 @@ 


import igraph 

import numpy as np

from LectureSyno_paires_CreationMatAdj import lecture, lecture_listemots

import matplotlib.pyplot as plt



listemots=[]

G=igraph.Graph()
@@ -122,7 +122,6 @@ comms7 = G.community_leading_eigenvector(clusters=6) 
comms8 = G.community_optimal_modularity() # très long ... 





comms9=G.community_label_propagation()



# ---------------

# initialisation des paramètres d'affichage
@@ -149,7 +148,7 @@ visual_style3["legend"] = "Mot : "+ mot.upper() 


# ----------------------------------

# Création des images résultat

'''



igraph.plot(comms1,  mot+"-multilevelNoMarkGroups.svg", **visual_style3)



igraph.plot(comms2,  mot+"-infomapNoMarkGroups.svg", mark_groups = False, **visual_style3)
@@ -166,7 +165,7 @@ igraph.plot(comms7, mot+"-leading-eigenvector.svg", mark_groups = True, **visua 
igraph.plot(comms8,  mot+"-optimal_modularity.svg", mark_groups = True, **visual_style3)



igraph.plot(comms9,  mot+"-label_propagation.svg", mark_groups = True, **visual_style3)

'''



# ---------------

# comparaisons
@@ -183,43 +182,108 @@ comms6b=comms6.as_clustering(n=6) 
igraph.plot(comms6b,  mot+"-edge_betweenness2.svg", mark_groups = True, **visual_style3)





com=[comms1,comms2,comms3b,comms4b,comms5,comms6b,comms7,comms8,comms9]

com=[comms1,comms2,comms3b,comms4b,comms5,comms6b,comms7,comms8]



labels=['multilevel','infomap','fastgreedy','walktrap','spinglass','edge_betweeness','eigenvector','optimal_modularity','label_propagation']

communautes=[comms1]

labels=['multilevel','infomap','fastgreedy','walktrap','spinglass','edge_betweeness','eigenvector','optimal_modularity']



x=[]

y=[]

vi=[]

print("VI")

for i in range(9):

for i in range(8):

	print(labels[i],':')

	for j in range(9):

	for j in range(8):

			r= igraph.compare_communities(com[i],com[j],method='vi', remove_none=False)

			print('\t',labels[j],'-',round(r,2))





			x.append(i)

			y.append(j)

			vi.append(round(r,2))



plt.figure(dpi=300, figsize=(12,8))

plt.scatter(x, y, c=vi, s=150, cmap=plt.get_cmap('viridis') )

plt.xlabel(labels,fontsize=12)

plt.grid(True,alpha=0.5)

plt.colorbar(orientation="horizontal", shrink=0.5).set_label("Indice de variation de la métrique de l'information")

plt.savefig('vi.png')

plt.clf()



x=[]

y=[]

nmi=[]

print("\nNMI")

for i in range(9):

for i in range(8):

	print(labels[i],':')

	for j in range(9):

	for j in range(8):

	   r= igraph.compare_communities(com[i],com[j],method='nmi', remove_none=False)

	   print('\t',labels[j],'-',round(r,2))



	   x.append(i)

	   y.append(j)

	   nmi.append(round(r,2))



plt.figure(dpi=300, figsize=(12,8))

plt.scatter(x, y, c=nmi, s=150,cmap=plt.get_cmap('viridis') )

plt.xlabel(labels,fontsize=12)

plt.grid(True,alpha=0.5)

c=plt.colorbar(orientation="horizontal", shrink=0.5).set_label("Indice information mutuelle")

plt.savefig('nmi.png')

plt.clf()



x=[]

y=[]

split=[]

print("\nSPLIT-JOIN")

for i in range(9):

for i in range(8):

	print(labels[i],':')

	for j in range(9):

	for j in range(8):

			r= igraph.compare_communities(com[i],com[j],method='split-join', remove_none=False)

			print('\t',labels[j],'-',round(r,2))



			x.append(i)

			y.append(j)

			split.append(r)

plt.figure(dpi=300, figsize=(12,8))

plt.scatter(x, y, c=split, s=150,cmap=plt.get_cmap('viridis') )

plt.xlabel(labels,fontsize=12)

plt.grid(True,alpha=0.5)

c=plt.colorbar(orientation="horizontal", shrink=0.5).set_label("Indice split-join")

plt.savefig('split.png')

plt.clf()



x=[]

y=[]

rand=[]

print("\nRAND")

for i in range(9):

for i in range(8):

	print(labels[i],':')

	for j in range(9):

	for j in range(8):

			r= igraph.compare_communities(com[i],com[j],method='rand', remove_none=False)

			print('\t',labels[j],'-',round(r,2))



			x.append(i)

			y.append(j)

			rand.append(r)

plt.figure(dpi=300, figsize=(12,8))

plt.scatter(x, y, c=rand, s=150,cmap=plt.get_cmap('viridis') )

plt.xlabel(labels,fontsize=12)

plt.grid(True,alpha=0.5)

c=plt.colorbar(orientation="horizontal", shrink=0.5).set_label("Indice rand")

plt.savefig('rand.png')

plt.clf()



x=[]

y=[]

adjustedrand=[]

print("\nADJUSTED_RAND")

for i in range(9):

for i in range(8):

	print(labels[i],':')

	for j in range(9):

	for j in range(8):

			r= igraph.compare_communities(com[i],com[j],method='adjusted_rand', remove_none=False)

			print('\t',labels[j],'-',round(r,2))

			x.append(i)

			y.append(j)

			adjustedrand.append(r)

plt.figure(dpi=300, figsize=(12,8))

plt.scatter(x, y, c=adjustedrand, s=150,cmap=plt.get_cmap('viridis') )

plt.xlabel(labels,fontsize=12)

plt.grid(True,alpha=0.5)

c=plt.colorbar(orientation="horizontal", shrink=0.5).set_label("Indice adjusted rand")

plt.savefig('adjustedrand.png')

plt.clf()
 
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adjustedrand.png

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nmi.png

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rand.png

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split.png

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