import random

class DE:
    def __init__(self, factory, fitness, popsize = 20, F = 0.5, CR = 0.6):
        self.factory = factory
        self.fitness = fitness
        self.popsize = popsize
        self.F = F
        self.CR = CR
        self.pop = [factory() for i in range(popsize)]
        self.fitnesses = [fitness(x) for x in self.pop]
    def iterate(self):
        new = []
        for i in range(self.popsize):
            while True:
                i1, i2, i3 = random.sample(range(self.popsize), 3)
                if all(x != i for x in [i1, i2, i3]):
                    break
            x   = self.pop[i]
            x1 = self.pop[i1]
            x2 = self.pop[i2]
            x3 = self.pop[i3]
            cand = [x1[k] + self.F * (x2[k] - x3[k]) for k in range(len(x))]
            X = [self.crossover(x[k], cand[k]) for k in range(len(x))]
            fit = self.fitness(X)
            if fit > self.fitnesses[i]:
                self.fitnesses[i] = fit
                new.append(X)
            else:
                new.append(x)
        self.pop = new
    def crossover(self, x1, x2):
        if random.random() < self.CR:
            return x1
        else:
            return x2
    def get_best(self):
        return max(zip(self.fitnesses, self.pop))

def fitness(indiv):
    sum = 0
    for i in indiv:
        sum += i * i
    return 1 / sum
def inicializa():
    return [random.uniform(-10, 10) for i in range(9)]

import math
f = math.tanh
def ann(ind, i1, i2):
    w1,w2,w3,w4,w5,w6,b1,b2,b3=ind
    m1 = f(w1*i1+w3*i2+b1)
    m2 = f(w2*i1+w4*i2+b2)
    o = f(m1 * w5 + m2 * w6 + b3)
    return o

def fitann(ind):
    sum = 1e-6 + (
        ( 1 - ann(ind, -1, -1)) ** 2 +
        (-1 - ann(ind, -1,  1)) ** 2 +
        (-1 - ann(ind,  1, -1)) ** 2 +
        ( 1 - ann(ind,  1,  1)) ** 2)
    return 1 / sum
        
de = DE(inicializa, fitann)
de.iterate()

maxit = 100
fitnesses = [de.get_best()[0]]
for i in range(maxit):
    de.iterate()
    fitnesses.append(de.get_best()[0])

import matplotlib.pyplot as plt
plt.plot(range(maxit + 1), fitnesses, '.-')
plt.show()

print('{:e}'.format(de.get_best()[0]))