from nnnar import *
from knn import *
import matplotlib.pyplot as plt
from random import *

knn = Knn()
nnnar = Nnnar(1, 0, 1000, 10)

def getRandomParam():
    return [random()*10-5, random()*10-5,random()*10-5]

def applyFunction(x,param):
    return pow(x*param[0],2) + x*param[1] + param[2]

param = getRandomParam()
nbPoints = 100
minx = 0
maxx = 1000
x = []
y = []

for i in [minx + (maxx-minx)*i/nbPoints for i in range(nbPoints)]:
    x.append(i)
    y.append(applyFunction(i,param))
    knn.addPoint(np.array([i]),np.array([y[-1]]))
    nnnar.addPoint(np.array([i]),np.array([y[-1]]))

error = 0
nbInfer = 20
for i in range(nbInfer):
    xt = random()*maxx
    yt = nnnar.getValueOfPoint(np.array([xt]),2)
    yr = applyFunction(xt,param)
    error += abs(yt[0]-yr)
    ytk = knn.getValueOfPoint(np.array([xt]),2)
    plt.plot(xt,yt[0],'xr')
    plt.plot(xt,ytk[0],'xg')

print("Error: ",(error/nbInfer)/applyFunction(maxx,param))

plt.plot(x,y)
plt.title("f(x) = "+str(param[0])+"*x^2 + "+str(param[1])+"*x + "+str(param[2]))
plt.xlabel("X")
plt.ylabel("Y")
plt.show()