def func(n):
while True :
lmbda = random.uniform(Integer(20),Integer(50))
mu = [random.uniform(Integer(2),Integer(5)),random.uniform(Integer(2),Integer(5))]
c = [random.randint(Integer(2),Integer(4)),random.randint(Integer(2),Integer(4))]
skip = [random.uniform(RealNumber('0.5'),RealNumber('0.8')),random.uniform(RealNumber('0.5'),RealNumber('0.8'))]
print lmbda
print mu
print c
print skip
static_pol = StaticPolicy.find_opt(lmbda,mu,c,skip)[Integer(0)]
State = Simm.Func(lmbda,mu,c,skip,Integer(100),static_pol,False,Integer(500000),True,Integer(3600))[Integer(0)]
outfile = open('./Static/MDP/Comparisons/out/Ndata/Ndata(%.02f,%s,%s,%s).csv' %(lmbda,mu,c,skip),'ab')
output = csv.writer(outfile)
outrow = []
outrow.append(lmbda)
outrow.append(mu[Integer(0)])
outrow.append(mu[Integer(1)])
outrow.append(c[Integer(0)])
outrow.append(c[Integer(1)])
outrow.append(skip[Integer(0)])
outrow.append(skip[Integer(1)])
output.writerow(outrow)
for i in range(Integer(20)):
for e in range(Integer(20)):
outrow = [e,i,State['%s,%s' %(e,i)].expectedi2]
output.writerow(outrow)
outfile.close()
def __init__(self,lmbda,mu,c,beta,run_time = _sage_const_600 ):
self.lmbda = lmbda
self.mu = mu
self.c = c
self.beta = beta
self.run_time = run_time
self.Di = {}
self.indexpol = {}
self.static_policy,self.longrun = StaticPolicy.find_opt(self.lmbda,self.mu,self.c,self.beta)
self.lmbda_list = [max(_sage_const_0 ,lmbda*self.static_policy[_sage_const_0 ]),max(_sage_const_0 ,lmbda*(self.static_policy[_sage_const_0 ] + self.static_policy[_sage_const_1 ]))]
self.rho = [(self.lmbda_list[e])/(mu[e]*c[e]) for e in range(_sage_const_2 )]
self.p0 = self.find_P0(self.static_policy)
def calcN2(lmbda, mu, c, skip, n1, n2):
static_pol = StaticPolicy.find_opt(lmbda, mu, c, skip)[_sage_const_0]
Lambda = [static_pol[_sage_const_0] * lmbda, (static_pol[_sage_const_0] + static_pol[_sage_const_1]) * lmbda]
plot_data = {}
a = Queue(Lambda, mu, c, skip, static_pol)
p0 = a.find_P0()[_sage_const_0]
value = _sage_const_0
a.tdict = {}
for t in range(_sage_const_1, _sage_const_100):
a.tdict[t] = probtime1stqueue(t, n1, Lambda[_sage_const_0], c[_sage_const_0], mu[_sage_const_0])
cumprob = _sage_const_0
t = _sage_const_0
while cumprob < _sage_const_0p999:
t += _sage_const_1
for j in range(c[_sage_const_0] + _sage_const_1):
if j == _sage_const_0:
value += (
a.interpolate(t)
* p0
* matrixform(
_sage_const_0 + lmbda * static_pol[_sage_const_1], mu[_sage_const_1], c[_sage_const_1], t, n2
)
)
elif j < c:
value += (
a.interpolate(t)
* (p0 * ((Lambda[_sage_const_0] / mu[_sage_const_0]) ** (j)) * (_sage_const_1 / math.factorial(j)))
* matrixform(
j * mu[_sage_const_0] + lmbda * static_pol[_sage_const_1],
mu[_sage_const_1],
c[_sage_const_1],
t,
n2,
)
)
else:
value += (
a.interpolate(t)
* (
_sage_const_1
- sum(
[
((Lambda[_sage_const_0] / mu[_sage_const_0]) ** (j))
* (_sage_const_1 / math.factorial(j))
for j in range(_sage_const_1, c)
]
)
- p0
)
* matrixform(
c[_sage_const_0] * mu[_sage_const_0] + lmbda * static_pol[_sage_const_1],
mu[_sage_const_1],
c[_sage_const_1],
t,
n2,
)
)
cumprob += a.tdict[t]
print cumprob
return int(value + _sage_const_0p5)
