2016-11-05 50 views
0

我有一些Python代码用于创建随机游走的情节。步行将反映[-a,a]的障碍。序列中的随后的值是由如何绘制matplotlib中一组点周围的恒定斜率的虚线“圆锥体”?

r[n] = r[n-1] + Uni[-R, R] 

,然后将其反映为必要生成。我想要做的是绘制每个点周围的“不确定性锥”,[-R, R]

这里是Python代码到目前为止我有:

import matplotlib.pyplot as plt 
import random 

uni = random.uniform 

t = [] 
r = [] 

r0 = .15 # Seed for our random walk. Can be between -a and a 
a = .2 # Distance of barriers from 0. Should be in (0, 1] 
R = .04 # Height of half-cone in r-direction 
dt = 20 # Sample period 
N = 20 # Number of samples 

cone_ls = ':' 
cone_clr = 'blue'#[0, .5, .5] 

for i in range(N): 
    t.append(i*dt) 
    if i == 0: 
     r.append(r0) 
    else: 
     ''' 
     When our cone of uncertainty outpaces out barriers, 
     simply sample uniformly inside the barriers. 
     ''' 
     if(R > 2*a): 
      r.append(uni(-a, a)) 
      continue 
     rn = r[i - 1] + uni(-R, R) 
     ''' 
     If the sampled value comes above the upper barrier, 
     reflect it back below. 
     ''' 
     if(rn > a): 
      r.append(2*a - rn) 
      continue 
     ''' 
     If the sampled value comes below the lower barrier, 
     reflect it back above. 
     ''' 
     if(rn < -a): 
      r.append(-2*a - rn) 
      continue 
     ''' 
     Otherwise just append the sampled value. 
     ''' 
     r.append(rn) 
# Plot cones 
for i, pt in enumerate(r): 
    plt.plot([t[i], t[i] + dt], [pt, pt + R], linestyle=cone_ls, color=cone_clr, linewidth=2) 
    plt.plot([t[i], t[i] + dt], [pt, pt - R], linestyle=cone_ls, color=cone_clr, linewidth=2) 

plt.plot(t, r, 'ro') 
plt.plot(t, [a]*N) 
plt.plot(t, [-a]*N) 
plt.axis([min(t), max(t), -2*a, 2*a]) 
plt.xlabel('Time (min)') 
plt.ylabel('Relative Difference, r') 
plt.show() 

我想情节看起来像这样添加锥后:

random walk with cones

我也将包括在一个文件中,所以任何美化技巧值得赞赏。

编辑:解决,实现我只需要绘制锥形部分单独。

回答

1

你可以只绘制两条线锥组成的每一个点在你的数据

for i in range(N): 
    plt.plot([t[i]+dt,t[i],t[i]+dt],[r[i]-R,r[i],r[i]+R], color="#808080") 

最后,你还需要设置x限制max(t)+dt
plt.axis([min(t), max(t)+dt, -2*a, 2*a])

enter image description here

+0

在我意识到和你一样意识到这只是另一组情节之后,我最终做了一些稍微复杂的事情。这一行很简洁,谢谢! – ijustlovemath