为了满足对函数光滑性的需要，我们可以使用一种有弹性的长条（称之为样条），强迫它弯曲通过样本点。
import numpy as np
import matplotlib.pylab as pl
from scipy import interpolate
x = np.linspace(0, 10, 11)
y = np.sin(x)
pl.figure(figsize=(12, 9))
pl.plot(x, y, 'ro')
x_new = np.linspace(0, 10, 101)
for kind in ['nearest', 'zero', 'linear', 'quadratic', 5]: #零阶，零阶，一阶，三阶，五阶
f = interpolate.interp1d(x, y, kind=kind)
y_new = f(x_new)
pl.plot(x_new, y_new, label=str(kind))
pl.xticks(fontsize=20)
pl.yticks(fontsize=20)
#标签坐落于右下方
pl.legend(loc='lower right')
pl.show()
分开画图
import numpy as np
import matplotlib.pylab as pl
from scipy import interpolate x = np.linspace(0, 10, 11)
y = np.sin(x) pl.figure(figsize=(12, 9))
pl.plot(x, y, 'ro')
x_new = np.linspace(0, 10, 101) f = interpolate.interp1d(x,y,kind = 5)
y_new = f(x_new)
pl.plot(x_new,y_new,label = '5') pl.xticks(fontsize=20)
pl.yticks(fontsize=20)
#标签坐落于右下方
pl.legend(loc='lower right')
pl.show()
