问题描述
def run_simulation(nba = 100,maxIter = 10,probI = 0.001,probR = 0.2,probI_init = 0.1,network = nx.erdos_renyi_graph,netParam=0.1,rep=10):
r = []
while len(r) < rep:
init(nba,probI_init,netParam,network)
i = 0
while i < maxIter:
step(probR,probI)
nbI = collect_statistics()
if nbI == 0:
break
i = i + 1
r.append(statS[-1])
print(((nba - sum(r)/len(r))/nba)*100)
这基本上是网络中病毒的模拟。输出是一个随机数,它是模拟结束时受感染代理的百分比。 我需要为 12 种不同的感染概率绘制此输出(即“probI”定义为函数的参数)。这 12 个概率是:
in[]np.logspace(-3,12)
out[]array([0.001,0.00187382,0.00351119,0.00657933,0.01232847,0.0231013,0.04328761,0.08111308,0.15199111,0.28480359,0.53366992,1. ])
我试过了:
但是这不会输入上面数组的每个数字作为 probI 的参数,就像:
run_simulation(probI = np.logspace(-3,12))
如何为每个概率循环我的函数?
提前致谢
解决方法
使用:
x = []
y = []
for probI in np.logspace(-3,12):
x.append(probI)
y.append(run_simulation(probI=probI))
用于绘图:
df = pd.DataFrame({'x': x,'y': y})
df.plot()