def bobo(N, n, b, c, delta, mu, alpha, beta, pmig):
pA = 0.0
it = gera_simulacao(N,n,pA,b,c,delta,mu,alpha,beta,pmig,max_it)
if it < max_it:
return 1, it
it = gera_simulacao(N,n,1.0,b,c,delta,mu,alpha,beta,pmig,max_it)
if it < max_it:
logger.info("pA=1 => 0")
return 0, max_it
nc = mp.cpu_count() -1
l_its = Parallel(n_jobs=nc)(delayed(sim)(N, n, b, c, delta, mu, alpha, beta, pA, pmig, i)\
for i in xrange(10))
# Mostra quantas simulacoes acabaram antes do maximo e a media de iteracoes que elas levaram
v = np.array(l_its)<max_it
if np.count_nonzero(v)>0:
w = np.take(l_its, np.nonzero(v)[0])
n_geracoes = sum(w)/len(w)
else:
n_geracoes = max_it
return np.count_nonzero(v), n_geracoes
def bobo(b, c, m_c, pmig):
pA = 1. if pmig > m_c else 0.
l_its = [gera_simulacao(N, n, pA, b, c, delta, mu, alpha, beta, pmig) for i in xrange(5)]
# Mostra quantas simulacoes acabaram antes do maximo e a media de iteracoes que elas levaram
v = np.array(l_its)<5000
if np.count_nonzero(v)>0:
w = np.take(l_its, np.nonzero(v)[0])
n_geracoes = sum(w)/len(w)
else:
n_geracoes = 0
return b, c, pmig, np.count_nonzero(v), n_geracoes, l_its[0], l_its[1], l_its[2], l_its[3], l_its[4]
def bobo(b, c, m_c, pmig):
pA = 1. if pmig > m_c else 0.
l_its = [
gera_simulacao(N, n, pA, b, c, delta, mu, alpha, beta, pmig)
for i in xrange(5)
]
# Mostra quantas simulacoes acabaram antes do maximo e a media de iteracoes que elas levaram
v = np.array(l_its) < 5000
if np.count_nonzero(v) > 0:
w = np.take(l_its, np.nonzero(v)[0])
n_geracoes = sum(w) / len(w)
else:
n_geracoes = 0
return b, c, pmig, np.count_nonzero(
v), n_geracoes, l_its[0], l_its[1], l_its[2], l_its[3], l_its[4]
def sim(N, n, b, c, delta, mu, alpha, beta, pA, pmig, i):
return gera_simulacao(N, n, pA, b, c, delta, mu, alpha, beta, pmig, max_it)