博主最近在学习python,结合自己专业课计算方法写下python如何做插值的3个实例。

import matplotlib.pyplot as plt
import numpy as np
#下面是numpy内置的插值函数(分段线性插值）的用法,请仔细观察学习各种画图命令
x=np.linspace(0,2*np.pi,10)
y=np.sin(x)
xvals=np.linspace(0,2*np.pi,20)
yinterp = np.interp(xvals, x, y)
plot1=plt.plot(x, y, 'o',label='original values')
plot2=plt.plot(xvals, yinterp, '-x',label='interped values')
#plot1=plt.plot(x, y, 'o',label=u'真实值')#采用unicode编码
#plot2=plt.plot(xvals, yinterp, '-x',label=u'插值')
plt.xlabel('x axis')
plt.ylabel('y axis')
plt.legend()
plt.show()
plt.savefig('c1.png')
#保存在当前目录文件夹

#自己编写的Lagrange插值函数，纯属闲着蛋疼
#潘海东，2015/1/12
import matplotlib.pyplot as plt
import numpy as np
x=np.linspace(0,2*np.pi,10)
y=np.sin(x)
xvals=np.linspace(0,2*np.pi,20)
def Lagrange(x,y,x0):
    n=len(x)
    m=len(x0)
    s=range(m)
    for k in range(m):
        t=0.0
        for j in range(n):
            u=1.0
            for i in range(n):
                if i!=j:
                    u=u*(x0[k]-x[i])/(x[j]-x[i])
            t=t+u*y[j]
        s[k]=t
    return s
yinterp = Lagrange(x,y,xvals)
plot1=plt.plot(x, y, '*',label='original values')
plot2=plt.plot(xvals, yinterp, 'r',label='interped values')
plt.xlabel('x axis')
plt.ylabel('y axis')
plt.legend()
plt.show()
plt.savefig('c2.png')
#保存在当前目录文件夹



#功能超强的python插值模块interpolate
import scipy.interpolate as itp
#导入插值库，读者可以dir(itp)查看里面有哪些插值函数
import matplotlib.pyplot as plt
import numpy as np
x=np.linspace(0,2*np.pi,10)
y=np.sin(x)
xvals=np.linspace(0,2*np.pi,20)
yinterp = itp.spline(x,y,xvals)#调用样条插值函数
plot1=plt.plot(x, y, 'b*',label='original values')
plot2=plt.plot(xvals, yinterp, 'r-x',label='interped values')
plt.xlabel('x axis')
plt.ylabel('y axis')
plt.legend()
plt.show()
plt.title('Spline')
plt.savefig('c3.png')
#保存在当前目录文件夹