delimiter=",",
skiprows=1)
G = GA(bnl, individuals=INDIVIDUALS, mutation_rate=MUPB)
G.DATASET = DATASET
debug_file += "_dataset" + str(DATASET)
IND_SIZE = G.BN.nodes**2
# use independent scores (NSGA-2)
G.SCRIPT_SCORE = "MAIN_return_the_score_nobic.R"
# let's generate almost empty individuals
for i, individual in enumerate(pop_deap):
new_individual = G.generate_individual(mutations=1)
new_individual_list = list(
new_individual.adjacency_matrix.reshape((1, IND_SIZE))[0])
#print (individual)
#print (new_individual_list)
#exit()
for j in range(IND_SIZE):
individual[j] = new_individual_list[j]
# first evaluation of the fitness of all individuals
fitnesses = evaluate_all(pop_deap, None, nodes=bnl.nodes)
for ind, fit in zip(pop_deap, fitnesses):
ind.fitness.values = fit[0], fit[1]
#print ind.fitness.values
