import random

class Perceptron:
    def __init__(self, n):
        self.weights = [random.randint(-1, 1) for _ in range(0, n)]
        self.lr = 0.1

    @staticmethod
    def sign(output):
        if output >= 0:
            return 1
        else:
            return -1

    def guess(self, inputs):
        s = 0
        for i, inp in enumerate(inputs):
            s += inp * self.weights[i]

        return Perceptron.sign(s)
    
    def guessY(self, x):
        w0 = self.weights[0]
        w1 = self.weights[1]
        w2 = self.weights[2]
        
        return -(w2 / w1) - (w0 / w1) * x

    def train(self, inputs, target):
        error = target - self.guess(inputs)
        for i, w in enumerate(self.weights):
            self.weights[i] += error * inputs[i] * self.lr