python实现回归中的相关系数和决定系数

import  numpy as npy
import cmath
def computecorrelation(x,y):
    x_bar=npy.mean(x)
    y_bar=npy.mean(y)
    SSR=0
    Varx=0
    Vary=0
    for i in range(0,len(x)):
        SSR+=(x[i]-x_bar)*(y[i]-y_bar)
        Varx+=(x[i]-x_bar)**2
        Vary+=(y[i]-y_bar)**2
    SST=cmath.sqrt(Varx*Vary)
    return SSR/SST
def polyfot(x,y,degree):
    result={}
    coef=npy.polyfit(x,y,degree)#算出各个回归系数
    result["polynomial"]=coef.tolist()
    p=npy.poly1d(coef)#拟合一条线
    y_hat=p(x)
    y_bar=npy.mean(y)
    SSR=npy.sum((y_hat-y_bar)**2)
    SST=npy.sum((y-y_bar)**2)
    result["determination"]=SSR/SST
    return result
test_x=[1,3,8,7,9]
test_y=[10,12,24,21,34]
print(polyfot(test_x,test_y,1)["determination"])
print(computecorrelation(test_x,test_y)**2)
print(polyfot(test_x,test_y,1))