types=['nearest','zero','slinear'] #插值的方法
t=np.array([0.25,0.5,0.75,1,3,5])
t_new=np.array([0.25,0.5,0.75,1,2,3,4,5])
rates=np.array([0.2733,0.2789,0.2838,0.2883,0.3041,0.3176])
for i in types:
f=interpolate.interp1d(x=t,y=rates,kind=i)
rates_new=f(t_new)
print(i,rates_new)
目的是实现插值法,补上2年、4年的收益率