import numpy as np
import matplotlib.pyplot as plt
N = 20
lam=20
t = np.random.exponential(scale=1/lam![1.png](https://img.haomeiwen.com/i11516617/523f1ffcb6bdfcb1.png?imageMogr2/auto-orient/strip%7CimageView2/2/w/1240)
![2.png](https://img.haomeiwen.com/i11516617/cf281136e8a2d9da.png?imageMogr2/auto-orient/strip%7CimageView2/2/w/1240)
, size=N) #提取服从指数分数的随机数
Sn = np.zeros(N)
Nt = [i for i in range(N)]
for i in range(0, N):
Sn[i] = sum(t[:i+1]) #第i次跳跃发生时间
plt.figure()
plt.grid()
plt.xlabel('t')
plt.ylabel('N(t)')
plt.title('one path of a Poisson process')
for i in range(N-1):
plt.plot((Sn[i], Sn[i+1]), (Nt[i], Nt[i]), color='r')
Qt = np.zeros(N)
#提取服从均匀分布的随机数,分布区间[0, 3]
y = np.random.uniform(low=0.0, high=5.0, size=N)
for i in range(0, N):
Qt[i] = sum(y[:i+1])
plt.figure()
plt.grid()
plt.xlabel('t')
plt.ylabel('Q(t)')
plt.title('one path of a compound Poisson process')
for i in range(N-1):
plt.plot((Sn[i], Sn[i+1]), (Qt[i], Qt[i]), color='r')
1.png
2.png
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