问题描述
我似乎在为我的数据拟合函数时遇到问题。也许有人可以帮我这个忙。
数据：
xValues = [65.2,65.4,65.1,65.2,65.6,65.5,65.7,65.9,66.0,66.1,66.3,66.4,66.5,66.6,66.7,66.8,66.9,67.1,67.0,67.2,67.3,67.5,67.6,67.8,67.9,68.0,68.1,68.2,68.3,68.4,68.6,68.7,68.9,68.8,69.0,69.2,69.3,69.4,69.6,69.7,69.8,69.9,70.0,70.1,70.2,70.5,70.6,70.8,71.0,71.2,71.1,71.4,71.5,71.7,71.8,72.0,72.1,72.3,72.5,72.4,72.6,72.7,72.9,73.1,73.0,73.3,73.2,73.4,73.5,73.6,73.7,73.8,74.0,73.9,74.1,74.2,74.3,74.4,74.5,74.6,74.7,74.9,74.9]
yValues = [57.4,57.5,53.2,56.4,47.3,54.3,60.4,59.6,59.2,51.6,53.1,49.5,54.9,54.5,56.0,57.8,54.7,48.8,55.7,59.3,54.6,51.5,43.6,50.2,55.3,55.1,59.9,57.2,60.0,64.0,59.8,63.1,67.4,64.4,58.7,55.6,60.6,63.3,63.0,60.5,57.4,60.1,61.9,62.8,62.0,70.3,70.4,64.9,75.2,63.9,62.1,66.2,72.2,77.5,65.0,77.4,74.8,79.8,84.2,69.5,70.7,77.1,76.2,71.3,75.6,75.5,75.8,75.3,78.9,81.5,80.6,82.9,79.1,84.4,79.7,76.4,80.5,81.2,88.0,80.4,85.3,79.3,79.5,82.4,80.8,80.1,76.3,83.3,78.4,84.8,87.3,86.4,86.7,85.5,78.8,81.1,87.2,87.1,88.4,85.6,86.5,88.8]
功能：＃对于感兴趣的人也称为蠕虫样链模型...
def func(x,L,P):
return (((1.381*10**(-2)) * 295.15)/P) * (1/(4*((1-x/L)**2)) +x/L -1/4)
#Fitting function to data:
#CurveFittingBlackMagic
initialGuess = [50,1.0]
popt,pcov = curve_fit(func,xRange,yRange,initialGuess,maxfev=1000000000)
print(popt)
print(pcov)
xFit = np.arange(0.0,200,0.01)
plt.plot(xFit,func(xFit,*popt),'r',label = 'fit params: L=%5.3f,P=%5.3f'%tuple(popt))
plt.ylim(-20,150) plt.xlim(-20,200)
#Plotting Data plt.plot(xValues,yValues)
plt.show()
这会产生图片中所示的结果，这显然是胡说八道，但我不知道为什么。如果有人可以指出我的错误，那将非常棒;）
解决方法
暂无找到可以解决该程序问题的有效方法，小编努力寻找整理中！
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