import neat

xor = neat.NEAT(n_networks = 150,
                input_size = 2,
                output_size = 1,
                bias = True,
                c1 = 1.0, c2 = 1.0, c3 = 0.4,
                distance_threshold = 3.0,
                weight_mutation_rate = 0.8,
                node_mutation_rate = 0.03,
                connection_mutation_rate = 0.05,
                interspecies_mating_rate = 0.001,
                disable_rate = 0.75,
                stegnant_threshold = 15,
                input_activation = neat.steepened_sigmoid,
                hidden_activation = neat.steepened_sigmoid,
                output_activation = neat.steepened_sigmoid)

truth_table = [[0, 1],[1, 0]]
solution_found = False

while True:
    print(f'Generation: {xor.generation}')
    rewards = []
    for genome in xor.population:
        error = 0
        for input_1 in range(len(truth_table)):
            for input_2 in range(len(truth_table[0])):
                output = int(round(genome([input_1, input_2])[0]))
                error += abs(truth_table[input_1][input_2] - output)
        fitness = (4 - error) ** 2
        rewards.append(fitness)
        if fitness == 16:
            solution_found = True
            break
    if solution_found:
        break
    xor.next_generation(rewards)

import matplotlib.pyplot as plt
genome.draw()
plt.show()