def netrate(network, cascades, T, type_diffusion):
#True data
A, nbre_noeuds = create_adj_matrix(network)
C, nbre_infections = create_cascade(cascades)
#OEstimated data given cascades
A_est = estimate_network(A, C, nbre_noeuds, T, type_diffusion, nbre_infections, 0.001)
return A_est, A
def MultiNetRate(nbre,file):
os.chdir("../donnees")
generation_SIS(nbre)
A,nbre_noeuds = create_adj_matrix(file)
file_SI = 'c'+str(nbre//100)+'.txt'
L,Delta = create_cascade(file_SI)
file_SIS = 'cnr'+str(nbre//100)+'.txt'
C,nbre_infections = create_cascade_NetRate(file_SIS)
#MultiNetRate estimation
(Beta,(accuracy,MAE,MAS)) = estimate_network(A,nbre_noeuds,L,Delta,nbre*20,'exp')
#NetRate estimation
(Alpha) = estimate_network_NetRate(A,C,nbre_noeuds,20,'exp',nbre_infections,0.00001)
#We compare the two solutions.
diff0 = norm_matrix(Alpha-Beta,0)
diff2 = norm_matrix(Alpha-Beta,2)
#We write down the result so that we can use them in the futur.
sdiff0 = str(diff0)
position_point = 0
for i,elt in enumerate(sdiff0):
if elt == '.':
position_point = i
with open('diff0.txt','a') as fichier1:
fichier1.write(str(k)+',')
fichier1.write(sdiff0[0:position_point]+','+sdiff0[(position_point+1):])
fichier1.write('\n')
sdiff2 = str(diff2)
position_point = 0
for i,elt in enumerate(sdiff2):
if elt == '.':
position_point = i
with open('diff1.txt','a') as fichier2:
fichier2.write(str(k)+',')
fichier2.write(sdiff2[0:position_point]+','+sdiff2[(position_point+1):])
fichier2.write('\n')
with open('indic_NetRate.txt','a') as fichier3:
fichier3.write(str(k))
fichier3.write(str(accuracy))
fichier3.write(str(MAE))
fichier3.write(str(MAS))
