如何matlab或者python实现多元函数的非线性拟合。
问题描述：
比如z=f（x，y），给出（x，y，z）的多个数据点，然后怎么拟合出f函数，给出源码就更好了
答
matlab
x1 = [1 2 3 4 5 6]';
x2 = [.2 .4 .8 .9 1.1 2.1]';
X = [x1 x2];
f = [ 3.3079 6.6358 10.3143 13.6492 17.2755 23.6271]';
objfcn = @(A,X)A(1)*x1 + x2.^(A(2));
x0=1;
x0=(1)*[1;1];
[vestimated,resnorm] = lsqcurvefit(objfcn,x0,X,f)
答
Python多项式拟合：
import matplotlib.pyplot as plt
import numpy as np
x = np.arange(1, 22, 1)
y = np.array([176.55823623919866, 175.82629227599108, 174.6682288122686, 174.1676016833001, 173.18851142144007, 171.50626507572986, 171.30220775004557, 171.36967661238003, 171.28415302420305, 171.28824729828153, 171.57034121168718, 172.33094464950744, 173.23238914855358, 173.55613816498442, 174.3453315452684, 175.8405706931801, 176.55279402689868, 176.61370282973544, 176.81582616485196, 177.02915557477107, 176.8786448208988])
z1 = np.polyfit(x, y, 100) # 用3次多项式拟合
p1 = np.poly1d(z1)
print(p1) # 在屏幕上打印拟合多项式
yvals=p1(x) # 也可以使用yvals=np.polyval(z1,x)
plot1=plt.plot(x, y, '*',label='original values')
plot2=plt.plot(x, yvals, 'r',label='polyfit values')
plt.xlabel('x axis')
plt.ylabel('y axis')
plt.legend(loc=4) # 指定legend的位置,读者可以自己help它的用法
plt.title('polyfitting')
plt.show()
plt.savefig('p1.png')