numpy多项式拟合函数polyfit的使用方法代码

import numpy as np
def fit(x,y,m,w):
    if len(x)<=m:
        return False
    xishu = np.polyfit(x,y,m,w=w)
    p = np.poly1d(xishu) # 构造多项式
    yfit = p(x) # 拟合的y值
    yresid = y - yfit # 残差
    SSresid = sum(pow(yresid, 2)) # 残差平方和
    SStotal = len(y) * np.var(y) # 总体平均方差
    if SStotal==0:#水平线
        r2=1
    else:
        r2 = 1 - SSresid/SStotal # 拟合优度    
    return (xishu,r2,yfit)
if __name__=="__main__":
    x = np.arange(0,5,0.1)
    z = [2+3*x+4*x**2 for x in x]
    y = np.array([np.random.normal(z,3) for z in z])
    weight=[1 for one in x]
    print(fit(x,y,2,weight))

if must00:
    x=np.append(x,0)#.append(0)
    y=np.append(y,0)#y.append(0)
    w=np.append(w,100000000)#.append(10000)
fit_r=fit(x,y,m,w)
if fit_r:
    (xishu,r,y_fitted)=fit_r
else:
    #fit error
    xishu=[0,1,0]
    y_fitted=x 
    r=0