def __init__(self, genes=None, x=0.0, y=0.0, predator=False):
R = funcs.gene2color(genes[-1])
G = funcs.gene2color(genes[-2])
B = funcs.gene2color(genes[-3])
if predator:
R, G, B = 0.9, 0.1, 0.1
super(Creature, self).__init__([x, y],
radius_multiplier=0.5,
color=(R, G, B),
energy=Creature.health)
self.predator = predator
self.cod = None
self.rotation = random.random()
self.speed = 0.0
self.num_detections = 1
self.distance = 0.0
self.rotated = 0.0
self.consumed_energy = 1
self.life_length = 1
self.antennae_length = self.radius_multiplier * self.G_MAXIMUM_RADIUS * 5
self.brain = eval(Creature.brain_type)(genes)
def __init__(self, genes=None, x=0.0, y=0.0, predator=False): R = funcs.gene2color(genes[-1]) G = funcs.gene2color(genes[-2]) B = funcs.gene2color(genes[-3]) if predator: R,G,B = 0.9, 0.1, 0.1 super(Creature, self).__init__([x,y], radius_multiplier=0.5, color=(R,G,B), energy=Creature.health) self.predator = predator self.cod = None self.rotation = random.random() self.speed = 0.0 self.num_detections = 1 self.distance = 0.0 self.rotated = 0.0 self.consumed_energy = 1 self.life_length = 1 self.antennae_length = self.radius_multiplier * self.G_MAXIMUM_RADIUS * 5 self.brain = eval(Creature.brain_type)(genes)
def printStatsCreatures(self,pop,gen,dba,dbb,dbp):
fits = [ind.fitness.values[0] for ind in pop]
mean = sum(fits) / len(pop)
reds = [funcs.gene2color(genome[-1]) for genome in pop]
greens = [funcs.gene2color(genome[-2]) for genome in pop]
blues = [funcs.gene2color(genome[-3]) for genome in pop]
stats.add("creature_fitness.avg",mean)
stats.add("creature_fitness.min",min(fits))
stats.add("creature_fitness.max",max(fits))
stats.add("creature.death_by_bush_procent",dbb*1.0/(dbb+dba+dbp))
stats.add("creature.death_by_predator_procent",dbp*1.0/(dbb+dba+dbp))
stats.add("creature_color.red", sum(reds)/len(reds))
stats.add("creature_color.blue", sum(blues)/len(blues))
stats.add("creature_color.green", sum(greens)/len(greens))
return ("(%3i): Max: %6.2f, Avg: %6.2f, Min: %5.2f, DBBP: %.2f" % (gen, max(fits), mean, min(fits),dbb*1.0/(dbb+dbp+dba)))
def printStatsCreatures(self, pop, gen, dba, dbb, dbp):
fits = [ind.fitness.values[0] for ind in pop]
mean = sum(fits) / len(pop)
reds = [funcs.gene2color(genome[-1]) for genome in pop]
greens = [funcs.gene2color(genome[-2]) for genome in pop]
blues = [funcs.gene2color(genome[-3]) for genome in pop]
stats.add("creature_fitness.avg", mean)
stats.add("creature_fitness.min", min(fits))
stats.add("creature_fitness.max", max(fits))
stats.add("creature.death_by_bush_procent",
dbb * 1.0 / (dbb + dba + dbp))
stats.add("creature.death_by_predator_procent",
dbp * 1.0 / (dbb + dba + dbp))
stats.add("creature_color.red", sum(reds) / len(reds))
stats.add("creature_color.blue", sum(blues) / len(blues))
stats.add("creature_color.green", sum(greens) / len(greens))
return ("(%3i): Max: %6.2f, Avg: %6.2f, Min: %5.2f, DBBP: %.2f" %
(gen, max(fits), mean, min(fits), dbb * 1.0 /
(dbb + dbp + dba)))
