import random
import math

class Neuron:
    def __init__(self):
        self.bias = random.uniform(-1.0, 1.0)
        self.in_ = []
        self.out_ = []
        self.value = 0.0

    def connect_in(self, connection):
        self.in_.append(connection)

    def connect_out(self, connection):
        self.out_.append(connection)

    def calc(self, input_val=None):
        if input_val is not None:
            self.value = input_val
        else:
            z = self.bias
            for connection in self.in_:
                z += connection.value * connection.weight
            
            z = max(-500, min(500, z)) 
            self.value = 1.0 / (1.0 + math.exp(-z))

        for connection in self.out_:
            connection.transfer(self.value)

    def adjust(self, error:float, learning_rate:float = 0.1):
        derivative = self.value * (1.0 - self.value)
        
        delta = error * derivative

        self.bias += learning_rate * delta

        for connection in self.in_:
            connection.adjust(delta, learning_rate)