def main(): target_x = 15 target_y = 8 selection_rate = .05 crossover_rate = .7 mutation_rate = .01 blocks = [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,0,0,0,1,1,1,0,0,0,1,8,0,0,0,0,0,0,0,1,1,1,0,0,0,1,1,0,0,0,1,1,1,0,0,1,0,0,0,0,1,1,0,0,0,1,1,1,0,0,0,0,0,1,0,1,1,1,0,0,1,1,1,0,0,0,0,0,1,0,1,1,0,0,0,0,1,0,0,0,0,1,1,1,0,1,1,0,1,1,0,0,0,1,0,0,0,0,0,0,5,1,0,1,1,0,0,0,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1] [blocks, width, height] = fixBlocks(blocks) ga = GA(blocks, (target_x, target_y, height, width, selection_rate, crossover_rate, mutation_rate)) sample = individual(50) # pop = population(100, 40) # test = [] # for i in range(200): # a_fitness = ga.averageFitness(pop) # pop = ga.evolve(pop) # test.append((a_fitness, pop)) # test = sorted(test) # sample = test[-1][1] # test2 = [] # for individual in sample: # test2.append((ga.fitness(individual), individual)) # test2 = sorted(test2) # sample2 = test2[-1][1] # print sample2 ga.visualize(sample)
elif i == 11:
start = start + np.array([-20, 0, -20, 0])
def individual(length):
individual = [randint(0, 1) for x in range(length)]
return ''.join(str(e) for e in individual)
def population(num_people, length):
return [individual(length) for x in range(num_people)]
target_x = 15
target_y = 8
selection_rate = .05
crossover_rate = .7
mutation_rate = .001
blocks = [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,0,0,0,1,1,1,0,0,0,1,8,0,0,0,0,0,0,0,1,1,1,0,0,0,1,1,0,0,0,1,1,1,0,0,1,0,0,0,0,1,1,0,0,0,1,1,1,0,0,0,0,0,1,0,1,1,1,0,0,1,1,1,0,0,0,0,0,1,0,1,1,0,0,0,0,1,0,0,0,0,1,1,1,0,1,1,0,1,1,0,0,0,1,0,0,0,0,0,0,5,1,0,1,1,0,0,0,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1]
[blocks, width, height] = fixBlocks(blocks)
ga = GA(blocks, (target_x, target_y, height, width, selection_rate, crossover_rate, mutation_rate))
pop = population(100, 70)
test = []
for individual in pop:
test.append((ga.fitness(individual), individual))
test = sorted(test)
print test[1][-1]
ga.visualize(test[1][-1])
