import gpib_instrument
import numpy as np
import pylab as plt
from scipy.optimize import curve_fit

scope = gpib_instrument.Gpib_Instrument(pad=3)
def ask(s):
    scope.write(s)
    r = ""
    while '\x00' not in r:
	r+=scope.read()
    return r[:r.find('\x00')]

def getxinfo():
    r = ask("WFMP?")
    r2=r.split(",",10000)
    d={c.split(":")[0]:c.split(":")[1] for c in r2}
    xincr = float(d["XINCR"])
    ymult = float(d["YMULT"])
    return xincr, ymult

def askcurv():
    d = ask("CURV?")
    d2=d.split(",",1000000)
    d3 = [int(q) for q in d2 if q.isdigit()]
    xincr,ymult = getxinfo()
    return np.arange(len(d3))*xincr, np.array(d3)*ymult

def model(x,p):
    # model the turn on as an exponential
    p[0]+p[1]*np.exp((x-p[2])/p[3])*np.greater(x,p[2])

t,y = askcurv()

useind = np.arange(100)
plt.plot(t,y)