def test_glouton(nmax, p):
x = []
y = []
xl = []
yl = []
N = nmax * (np.arange(10) + 1) / 10
if (nmax > 1):
for i in (N):
i = int(i) + 1
x.append(i)
xl.append(math.log(i))
tcumul = 0
for j in range(10):
g = imp.gen_graphe(i, p)
while (imp.is_empty(g)):
g = imp.gen_graphe(i, p)
start_time = time.time()
c = imp.glouton(g)
end_time = time.time()
t = (end_time - start_time)
tcumul += t
y.append(tcumul / 10)
yl.append(math.log(tcumul / 10))
return x, y, xl, yl
else:
print('nmax doit etre supérieur à 1')
return None
def test_branch_born_brut(nmax, p):
x = []
y = []
xl = []
yl = []
N = nmax * (np.arange(10) + 1) / 10
if (nmax > 1):
for i in (N):
print(i)
i = int(i) + 1
x.append(i)
xl.append(math.log(i))
tcumul = 0
for j in range(10):
g = imp.gen_graphe(i, p)
while (imp.is_empty(g)):
g = imp.gen_graphe(i, p)
t, b, nb_n = imp.branch_born_brut(g)
tcumul += t
y.append(tcumul / 10)
yl.append(math.log(tcumul / 10))
return x, y, xl, yl
else:
print('nmax doit etre supérieur à 1')
return None
def rapport_approxim(nmax, p):
x = []
y1 = []
y2 = []
N = nmax * (np.arange(10) + 1) / 10
if (nmax > 1):
for i in (N):
print(i)
i = int(i) + 1
x.append(i)
rcumul1 = 0
rcumul2 = 0
for j in range(10):
g = imp.gen_graphe(i, p)
while (imp.is_empty(g)):
g = imp.gen_graphe(i, p)
t, C, nb_n = imp.branch_born_ameliore1(g)
c1 = len(C)
c2 = len(imp.couplage(g))
c3 = len(imp.glouton(g))
rcumul1 += c2 / c1
rcumul2 += c3 / c1
y1.append(rcumul1 / 10)
y2.append(rcumul2 / 10)
return x, y1, y2
else:
print('nmax doit etre supérieur à 1')
return None
def compare_couplage_glouton(nmax, p):
x = []
y1 = []
y2 = []
N = nmax * (np.arange(10) + 1) / 10
if (nmax > 1):
for i in (N):
i = int(i) + 1
x.append(i)
cumul1 = 0
cumul2 = 0
for j in range(20):
g = imp.gen_graphe(i, p)
while (imp.is_empty(g)):
g = imp.gen_graphe(i, p)
c2 = len(imp.glouton(g))
c1 = len(imp.couplage(g))
if (c1 < c2):
cumul1 += 1
else:
if (c2 < c1):
cumul2 += 1
else:
cumul2 += 1
cumul1 += 1
y1.append(cumul1)
y2.append(cumul2)
return x, y1, y2
else:
print('nmax doit etre supérieur à 1')
return None
def ecart_couplage_glouton(nmax, p):
x = []
y = []
N = nmax * (np.arange(10) + 1) / 10
if (nmax > 1):
for i in (N):
i = int(i) + 1
x.append(i)
ecumul = 0
for j in range(20):
g = imp.gen_graphe(i, p)
while (imp.is_empty(g)):
g = imp.gen_graphe(i, p)
c2 = len(imp.glouton(g))
c1 = len(imp.couplage(g))
ecumul += abs(c2 - c1)
y.append(ecumul / 20)
return x, y
else:
print('nmax doit etre supérieur à 1')
return None
def Comparaison_branch_born(nmax, p):
x = []
xl = []
yl1 = []
y1 = []
yl2 = []
y2 = []
yl3 = []
y3 = []
N = nmax * (np.arange(10) + 1) / 10
if (nmax > 1):
for i in (N):
print(i)
i = int(i) + 1
x.append(i)
xl.append(math.log(i))
tcumul1 = 0
tcumul2 = 0
tcumul3 = 0
nbSommet1 = 0
nbSommet2 = 0
nbSommet3 = 0
for j in range(10):
g = imp.gen_graphe(i, p)
while (imp.is_empty(g)):
g = imp.gen_graphe(i, p)
t, b, nb_n = imp.branch_born(g)
tcumul1 += t
nbSommet1 += nb_n
t, b, nb_n = imp.branch_born_glouton(g)
tcumul2 += t
nbSommet2 += nb_n
t, b, nb_n = imp.branch_born_brut(g)
tcumul3 += t
nbSommet3 += nb_n
y1.append(nbSommet1 / 10)
y2.append(nbSommet2 / 10)
y3.append(nbSommet3 / 10)
yl1.append(math.log(tcumul1 / 10))
yl2.append(math.log(tcumul2 / 10))
yl3.append(math.log(tcumul3 / 10))
#comparaison du log (temps)
plt.xlabel('Log de la taille d' 'instance: N')
plt.ylabel('Log du temps de calcul')
plt.title("comparaison du log (temps)")
plt.plot(xl, yl1, label="branch-born")
plt.plot(xl, yl2, label="branch-born_glouton")
plt.plot(xl, yl3, label="branch-born_brut")
plt.legend()
plt.show()
#comparaison du nombre de noeuds créé
plt.xlabel('Taille d' 'instance: N')
plt.ylabel('Nombre de noeuds')
plt.title("comparaison du nombre de noeuds créés")
plt.plot(x, y1, label="branch-born")
plt.plot(x, y2, label="branch-born_glouton")
plt.plot(x, y3, label="branch-born_brut")
plt.legend()
plt.show()
