Polynomial interpolation fitting (III)

Third order polynomial interpolation （ Cubic interpolation ）：

fx=ax^3+bx^2+cx+d

interp1d(x,y,kind='cubic') 'cubic' Cubic interpolation 

import numpy as np
from scipy.interpolate import interp1d,interp2d
import pylab as pl

x=np.array([1,2,3,4,5])
y=np.array([1,4,2,4,1]) #Y=x^3+x^2+x+1

fc=interp1d(x,y,kind='cubic')
xint=np.linspace(x.min(),x.max(),20)
print(xint)
print(fc(xint))

pl.scatter(xint,fc(xint),c='r',marker='o')
pl.plot(xint,fc(xint),color='blue',label='Cubic-10')
pl.show()

Interpolation point ：

xint [1.         1.21052632 1.42105263 1.63157895 1.84210526 2.05263158
 2.26315789 2.47368421 2.68421053 2.89473684 3.10526316 3.31578947
 3.52631579 3.73684211 3.94736842 4.15789474 4.36842105 4.57894737
 4.78947368 5.        ]
y: [1.         2.71628517 3.73859163 4.19288526 4.20513194 3.90129757
 3.40734801 2.84924916 2.3529669  2.04446712 2.04446712 2.3529669
 2.84924916 3.40734801 3.90129757 4.20513194 4.19288526 3.73859163
 2.71628517 1.        ]