通过func返回数组（1）与Python中的大小不匹配

我是python的新手，所以请多多包涵。我正在使用python中的odeint函数解决一个模型，该模型中出现错误。func （1）返回的数组的大小与y0（2）的大小不匹配。。也许我在重新使用odeint函数中的args时犯了一个错误，但是我已经看到与odeint LINK相关的关于桩溢出的帖子，并且可以与返回参数一起正常工作。我不知道这是什么问题，或者我可能是错误的方向。如果我错了，请纠正我。

from scipy import *
from scipy.integrate import odeint
from operator import itemgetter
import matplotlib
matplotlib.use('Agg')
from matplotlib.ticker import FormatStrFormatter
from pylab import *

import sys

ExpData = [1.0 , 1.1660520579009868 , 1.3688685188071037 , 1.6165891026469563 ,
           1.9191557810726714 ]

t_range = arange(0.0,20.0,0.1)

y0 = [1,0.5]
VarList = ["a","b"]
ParaList = ["k1","k2"]
k1 = 1
k2 = 2


def func(Y,t,modelID,t1,t2):
    return GenModel(Y,modelID,t1,t2)

def GenModel(Y,modelID,t1,t2):
    RetY = [None]
    if modelID == 1:
        RetY = Y[0] + Y[1]
    elif modelID == 2:
        RetY = t1*Y[0] + Y[1]
    elif modelID == 3:
        RetY = Y[0] + t1*Y[1]
# code reduced from here

    if Y[0] == 0 or Y[1] == 0:
        if modelID == 27:
            RetY = 0
        elif modelID == 28:
            RetY = 0
    if Y[0] != 0 and Y[1] != 0:
        if modelID == 27:
            RetY = Y[0]*Y[1]
        elif modelID ==28:
            RetY = t1*Y[0]*Y[1]
        elif modelID == 29:
            RetY = t2*Y[0]*Y[1]
           # code reduced from here as well
    return RetY

def EvalModelFitness(Stofloat,ExpData):
    Sum = 0.0
    for i in range(len(Stofloat)):
        Sum += (Stofloat[i]-ExpData[i])**2
    print Sum/len(Stofloat)

if y0[0] == 0 or y0[1] == 0:
    NumModels = 28
else:
    NumModels = 39

for j in range(1,NumModels+1):
    S = odeint(func, y0,t_range,args=(j,k1,k2))
    Stofloat = S[:,0].astype(type('float',(float,),{}))
    EvalModelFitness(Stofloat,ExpData)