python 计算相关系数、纳什系数和均方根误差

题目描述

编写程序由用户指定维度n，建立向量A，B，并随机赋初值，计算向量A、B的相关系数R，纳什系数NSE、均方根误差RMSE。

#A为实际值，B为预测值
import random
n=int(input("请输入向量维度n："))
A=[]
B=[]
for i in range(1,n+1):
    A.append(random.randint(1,10))
    B.append(random.randint(1,10))
suma=0
import os
sumb=0
for i in range(0,n):
    suma=A[i]+suma
    sumb=B[i]+sumb 
avea=suma/n
aveb=sumb/n

cova=0
covb=0
cova2=0
covb2=0
cov=0
for i in range(0,n):
    cova=(A[i]-avea)
    covb=(B[i]-aveb)
    cov=cova*covb+cov
    cova2=pow(A[i]-avea,2)+cova2
    covb2=pow(B[i]-aveb,2)+covb2
R=(cov)/(pow((cova2),0.5)*pow(covb2,0.5))

up=0
down=0
for i in range(0,n):
    up=pow((A[i]-B[i]),2)+up
    down=pow((A[i]-aveb),2)+down
NSE=1-up/down
RMSE=pow(up/n,0.5)
print("实际值A",A)
print("预测值B",B)
print("相关系数R",R)
print("纳什系数NSE",NSE)
print("均方根误差RMSE",RMSE)

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