# Morris-Lecar model Methods Chapter
wiener nn
dv/dt = ( I - gca*minf(V)*(V-Vca)-gk*w*(V-VK)-gl*(V-Vl))/c+sig*nn
dw/dt = phi*(winf(V)-w)/tauw(V)
v(0)=-16
w(0)=0.014915
minf(v)=.5*(1+tanh((v-v1)/v2))
winf(v)=.5*(1+tanh((v-v3)/v4))
tauw(v)=1/cosh((v-v3)/(2*v4))
param vk=-84,vl=-60,vca=120
param i=90,sig=1,gk=8,gl=2,c=20
param v1=-1.2,v2=18
# Uncomment the ones you like!!
par1-3 v3=2,v4=30,phi=.04,gca=4.4
#par4-6 v3=12,v4=17.4,phi=.06666667,gca=4
#par7-8 v3=12,v4=17.4,phi=.23,gca=4
@ total=500000,dt=.25,xlo=-75,xhi=75,ylo=-.25,yhi=.5,xp=v,yp=w,meth=euler
@ maxstor=10000000,trans=10000
done
1. Numerics Poincare Period
   variable:w
   section:0.4
   direction: 1
   stop on sect: N
  
  click OK
  and then Esc

2. Initial Conds Go
   you will have about 4000 data points 
   to use excel or something, open the Data viewer and click on write
to save the data  in ascii format. The first column contains the ISIs

3. In XPP, click on Numerics stochastic histogram
  NBINS: 100
  Low:0
  Hi:1000
  Variable: t
  Condition: <Enter>

Esc to main meneu; then plot V vs t

you can change total time to get more points if you want