def createPop(self, popsize):
params = self.params
random = self.random
import createInd
pop = []
## template individual
#tree_genome = self.params['template']
#new_ind = DocplanIndividual(self.random, None, genome=tree_genome)
#self.decodePlan(new_ind)
#new_ind.rank = 1
#new_ind.crowded_distance = 100
#pop.append(new_ind)
import math
color_len = int(math.ceil(math.log(len(self.colors), 2)))
self.scale_len = int(math.ceil(math.log(params['num_scale'], 2)))
for i in xrange(popsize):
tree_genome = createInd.createIndividual(random, params['maxDepth'], params['maxRoom'], params['minRoom'])
color_genome = [random.randint(0, 1) for i in xrange(color_len)]
new_ind = DocplanIndividual(random, None, genome={'tree': tree_genome, 'color': color_genome})
self.initDecode(new_ind)
pop.append(new_ind)
return pop
def createPop(self, popsize):
params = self.params
random = self.random
import createInd, math
pop = []
color_len = int(math.ceil(math.log(len(self.colors), 2)))
self.scale_len = int(math.ceil(math.log(params["num_scale"], 2)))
for i in xrange(popsize):
tree_genome = createInd.createIndividual(random, params["maxDepth"], params["maxRoom"], params["minRoom"])
color_genome = [random.randint(0, 1) for i in xrange(color_len)]
new_ind = DocplanIndividual(random, None, genome={"tree": tree_genome, "color": color_genome})
self.initDecode(new_ind)
# evaluate this new individual based on obj criteria only
self.fitness(new_ind, None)
pop.append(new_ind)
# sort population by obj score, and set rank proportional to fitness
pop.sort(lambda a, b: cmp(a.fitness, b.fitness))
for i in xrange(len(pop)):
pop[i].rank = i
return pop
def createPop(self, popsize):
params = self.params
random = self.random
import createInd
pop = []
## template individual
#tree_genome = self.params['template']
#new_ind = DocplanIndividual(self.random, None, genome=tree_genome)
#self.decodePlan(new_ind)
#new_ind.rank = 1
#new_ind.crowded_distance = 100
#pop.append(new_ind)
for i in xrange(popsize):
tree_genome = createInd.createIndividual(random, params['maxDepth'], params['maxRoom'], params['minRoom'], params['num_shapes'])
new_ind = DocplanIndividual(random, None, genome=tree_genome)
self.decodePlan(new_ind)
pop.append(new_ind)
return pop
def createPop(self, popsize):
import createInd
pop = []
# template individual
tree_genome = self.params["template"]
new_ind = FloorplanIndividual(self.random, None, genome=tree_genome)
self.decodePlan(new_ind)
new_ind.rank = 1
new_ind.crowded_distance = 100
pop.append(new_ind)
for i in xrange(popsize - 1):
tree_genome = createInd.createIndividual(
self.params["maxDepth"], self.params["maxRoom"], self.params["minRoom"]
)
new_ind = FloorplanIndividual(self.random, None, genome=tree_genome)
self.decodePlan(new_ind)
pop.append(new_ind)
return pop
