import random
import matplotlib.pyplot as pl
import numpy as np
import math

A = 1.
B = 0.5
sigma = 0.3
xmax = 4.
numberOfClassEl = 200
data = []
sumx =0
sumg = 0
sumxg =0
sumxx =0
for rowNum in range(numberOfClassEl):
 X = random.random()*xmax
 sumx = sumx + X
 G = A+B*X+random.gauss(0,sigma)
 sumg = sumg + G
 sumxg = X*G + sumxg
 sumxx = X*X + sumxx
 data.append([X, G])


b = (sumxg/200 - sumx/200*sumg/200)/(sumxx/200 - (sumx/200)**2)
a = -b*sumx/200 + sumx/200
print(a, b)

MSE = 0
i = 0
for i in range(numberOfClassEl):
 MSE += (data[i][1] - (a+ b*data[i][0]))**2
MSE = MSE / 200
i = 0
for i in range(numberOfClassEl):
 MAE = abs(data[i][1] - (a + b*data[i][0]))
MAE = MAE / 200
RMSE = math.sqrt(MSE)
print(MSE, RMSE, MAE)

f = np.linspace(0, 4, 200)
pl.plot(f, a+b*f)

pl.scatter([data[i][0] for i in range(len(data))],[data[i][1] for i in range(len(data))],)
pl.savefig('genLRdata.png')