import os
import sys
parent_dir_name = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
sys.path.append(parent_dir_name + "/3nar/code")

from nnnar import *

import matplotlib.pyplot as plt
import numpy as np
from time import time



maxVal = 1_000
nbTest = 1000
nbPts = 10
nbModel = 10
nbMaxSubDiv = 100

# Création des données d'entrainement
train = []
test = []
for i in range(maxVal):
    x = np.random.rand()
    y = np.random.rand()
    train.append([x,y])
for i in range(nbTest):
    x = np.random.rand()
    test.append(x)
train = np.array(train)
test = np.array(test)

def testModel(model, train ,test):
    model.reset()
    t = time()
    # Entrainement du modèle
    for i in range(len(train)):
        model.addPoint(np.array([train[i,0]]), np.array([train[i,1]]))
    # Test du modèles
    for i in range(len(test)):
        model.getValueOfPoint(np.array([test[i]]), 5)[0]
    return time() - t


for i in range(1,nbModel):
    nbSub = round(i*nbMaxSubDiv/nbModel)
    print(nbSub)
    model = Nnnar(1,0,1,nbSub)
    res = []
    idxs = []
    for i in range(1,nbPts):
        idx = round((i*nbTest)/nbPts)
        idxs.append(idx)
        res.append(testModel(model, train, test[:idx]))
    plt.plot(res,label='NNNAR('+str(nbSub)+')')

plt.xlabel('Number of points infered')
plt.ylabel('Time (s)')
plt.xticks(range(len(idxs)), idxs)
plt.legend()
plt.show()