当教室突然安静——扰动，突变与回复

import math  import numpy as np  #迭代方程  def A(x,y):  	k=math.log1p(x)/math.log(2)*0.5*(1+math.tanh(5*(y+1.5)))  	return k  #随机函数  def a(t):  	c=1+math.tanh(7*(math.sin((math.sqrt(3))*0.7*t)+math.sin((math.sqrt(5))*0.7*t)+0.332*math.sin((math.sqrt(16))*0.7*t)+math.sin((math.sqrt(14))*0.7*t)+1.02*math.sin((math.sqrt(2.5803)*0.7*t))))  	return c    def b(t):  	d=(a(t)+a(t+10)+a(t+20)+a(t+30)+a(t+40)+a(t+50)+a(t+60)+a(t+70)+a(t+80)+a(t+90))/10  	return d    def g(t):  	e=(b(t)+b(t+100)+b(t+200)+b(t+300))/4  	return e  #时间步长    step=round(0.05,5)	    #F 在 t 为 0 前取值的初始化  dict={}#迭代数据暂存  hhh=-1  while hhh<=0:  	dict[hhh]=g(hhh)  	hhh=round(hhh+step,5)    #记录突变时间	  timelist=[]	  count=0	  realcount=0  #用于绘图记录数据  datadict={}#响度记录  gdata={}#发言意愿记录  #迭代循环	  t=0  while t<=360000:      fl=(dict[round(t-0.05,5)]+dict[round(t-0.1,5)]+dict[round(t-0.15,5)]+dict[round(t-0.2,5)]+dict[round(t-0.25,5)]+dict[round(t-0.3,5)])/6      fv=(((dict[round(t-0.05,5)]+dict[round(t-0.1,5)]+dict[round(t-0.15,5)]+dict[round(t-0.2,5)]+dict[round(t-0.25,5)])/5)-((dict[round(t-0.55,5)]+    dict[round(t-0.6,5)]+dict[round(t-0.65,5)]+dict[round(t-0.7,5)]+dict[round(t-0.75,5)])/5))*2	      dict[t]=g(t)*A(fl,fv)+0.001*g(t)      datadict[t]=dict[t]      gdata[t]=g(t)      del dict[round(t-0.8,5)]      #以上递推模拟      last=count      if (dict[round(t-0.05,5)]+dict[round(t-0.1,5)]+dict[round(t-0.15,5)]+dict[round(t-0.2,5)]+dict[round(t-0.25,5)])/5>=0.1:      	count=0      else:      	count=1      	      if last-count<=-1:      	realcount=realcount+1      	timelist.append(t)  #以上突变计录  	           t=round(t+step,5)     	      #1.75，50h，0     1.6 43    1.5 187(100h410 个)     1.4 约 475     1.3 约 1250     1.2 约 2550        1.1 约 5075    1 约 9200  #以下突变绘制  import matplotlib.pyplot as plt  #绘图循环  n=1  databar={}  kkk=-5  tmd=0.5  while kkk<=5:  	databar[kkk]=0  	kkk=round(kkk+0.05,5)#平均值初始化  while n<=realcount:      ctime=timelist[(n-1)]      x_values = list(np.arange(ctime-5, ctime+5,0.05))      y_values = [datadict[round(x,5)] for x in x_values]     # g_values= [gdata[round(x,5)] for x in x_values]            x_values=list(np.arange(-5,5,0.05))      if datadict[round(ctime,5)]>=0.06:      	tmd=0.7      else:      	tmd=0.01      plt.plot(x_values, y_values,alpha=tmd)        #    plt.plot(x_values,g_values,"c-")       n=round(n+1,2)  T=-5  while T<=5: #求均值循环      for m in timelist:  	    databar[T]=databar[T]+(datadict[round(m+T,5)])/realcount      T=round(T+0.05,5)  data_values = [databar[round(x,5)] for x in x_values]  plt.plot(x_values, data_values,"c-")  plt.axis([-5, 5, 0, 2])  plt.show()