'''
	Nome: Gabriel Gomes Cruz da Rocha
	Matricula: 201407708
	Atividade_-_Adaline
'''

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

def ufunction(X, w, b, i):

	U = 0

	for j in range(0,2):
		U = U + (w[j] * X[i][j])
	U = U + b

	return U

def activation(U):

	return math.tanh(U)

def updatew(w, a, e, X, i):

	for j in range(0,2):
		w[j] = w[j] + (a * e[i] * X[i][j])

def erro( X, w, b, d):

    aux = 0
    Y1 = np.zeros(4)
    e1 = np.zeros(4)

    for i in range(4):
        Y1[i] = activation(ufunction(X, w, b, i))
        e1[i] = d[i] - Y1[i]
        aux = aux + pow(e1[i], 2)

    return aux/4

def plotar(w1, w2, bias, title):

    xvals = np.arange(-1, 3, 0.01)
    newyvals = (((xvals * w2) * - 1) - bias) / w1
    plt.plot(xvals, newyvals, 'r-')
    plt.title(title)
    plt.xlabel('X1')
    plt.ylabel('X2')
    plt.axis([-1,2,-1,2])
    plt.plot([0,1,0],[0,0,1], 'b^')
    plt.plot([1],[1], 'go')
    plt.xticks([0,1])
    plt.yticks([0,1])
    plt.show()

def perceptron(max_int, E, a, X, d):

	w = [random.random(), random.random()]
	b = random.random()
	t = 1
	print("Valores Iniciais:	W1 = %.4f"  %w[0] ,"W2 = %.4f" %w[1] ,"bias = %.4f" %b)

	Y = np.zeros(4)
	e = np.zeros(4)
	deltaMSE = 1

	while(t < max_int and deltaMSE > E):
		MSEinicial = erro( X, w, b, d)

		for i in range(0,4):
			Y[i] = activation(ufunction(X, w, b, i))
			e[i] = d[i] - Y[i]
			updatew(w, a, e, X, i)
			b = b + (a * e[i])

		MSEfinal = erro(X, w, b, d)
		deltaMSE = MSEfinal - MSEinicial
		t = t + 1

	print("Valores Finais:		W1 = %.4f"  %w[0] ,"W2 = %.4f" %w[1] ,"bias = %.4f" %b)

	return(w, b)

def main():

 	max_int = 100
 	E = 0.0000001
 	alpha = 0.1
 	X = [[0,0],[0,1],[1,0],[1,1]]
 	d = [-1, -1, -1, 1]

 	w, b = perceptron(max_int, E, alpha, X, d)

 	plotar(w[0], w[1], b, "Porta lógica AND com Adaline")

if __name__ == "__main__":
    main()