本文整理汇总了Python中individual.Individual类的典型用法代码示例。如果您正苦于以下问题：Python Individual类的具体用法？Python Individual怎么用？Python Individual使用的例子？那么, 这里精选的类代码示例或许可以为您提供帮助。
在下文中一共展示了Individual类的15个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: __init__
def __init__(self, size, initialize=False):
self.individuals = []
if initialize:
for i in range(0, size):
individual = Individual()
individual.generate_individual()
self.individuals.append(individual)示例2: test_fight
def test_fight(self):
ind1 = Individual("01101110")
ind2 = Individual("00111000")
fight1 = ind2.fight(ind1)
self.assertEqual(ind1.fitness, 1)
self.assertEqual(ind2.fitness, 0)
fight2 = ind1.fight(ind2)
self.assertEqual(fight1, False)
self.assertEqual(fight2, False)示例3: crossover_pt
def crossover_pt(self, individual_1, individual_2):
crossover_individual = Individual()
uniform_rate = uniform(3, 7) * .1
crossover_point = int(uniform_rate * len(crossover_individual.genes))
crossover_individual.genes = individual_1.genes[0:crossover_point]
crossover_individual.genes += individual_2.genes[crossover_point:]
return crossover_individual示例4: setup
class TestEvaluateAgainst:
def setup(self):
self.individual_a = Individual('0123456789')
def test_identical(self):
chars = self.individual_a.chars
assert_true(self.individual_a.evaluate_against(chars) == len(chars))
def test_no_similarity(self):
assert_true(self.individual_a.evaluate_against('a tallship') == 0)示例5: crossover_random
def crossover_random(self, individual_1, individual_2):
crossover_individual = Individual()
for i in range(0, len(crossover_individual.genes)):
# crossover
if random() <= self.uniform_rate:
crossover_individual.genes[i] = individual_1.genes[i]
else:
crossover_individual.genes[i] = individual_2.genes[i]
return crossover_individual示例6: run_once
def run_once(self):
newpop = []
# Elitism, keep the best chromosome to the next generation
newpop = self.population[:3]
for i in range(3, self.popsize):
tmpchrom = Individual(mother=self.__my_choice(), father=self.__my_choice())
tmpchrom.mutate()
newpop.append(tmpchrom)
self.population = newpop
self.evaluate_all()
self.randomize_duplicates()
self.apply_max()
self.evaluate_all()
self.population.sort(key=attrgetter("fitness"), reverse=True)
self.inc_mutation_rate(MUTATION_RATE_INC)示例7: init_children_test
def init_children_test(self, num_children):
self.clear_test_state()
player1 = Individual()
testee = player1.get_robot()
testee.location = constants.testee_loc
self.robots = [testee]
self.gamestate.add_robot(testee.location, testee.player_id)
# Force the prime rule to be the move rule so direction is returned
while testee.eval_order[0].action != 'move':
random.shuffle(testee.eval_order)
rule = self.robots[0].eval_order[0]
rule.insert_random_parent()
for x in range(num_children):
self.insert_random_root_child(rule)示例8: setUp
def setUp(self):
self.indi = Individual()
self.indi.addID('@[email protected]')
self.indi.addName('John Rivas')
self.indi.addSex('M')
self.indi.addBirt('9 MAY 1978')
self.indi.addDeat('12 APR 2013')
self.indi.addFams('@[email protected]')
self.indi.addFamc('@[email protected]')示例9: __init__
def __init__(self, size):
self.size = size
self.pop = []
self.selected = []
self.selected_indexes = []
self.fitness_table = []
Individual.mutation_factor = 5
for i in xrange(size):
self.pop.append(Individual.random_ind())示例10: make_json_record
def make_json_record(case_name=CASE_NAME, seed=0, lineage=0, age=0):
input_filepath = os.path.join(RESULT_DIR, case_name)
output_file = os.path.join(
ensure_exists(os.path.join(ANALYSIS_DIR, case_name, "seed-{}".format(seed))), "game.json"
)
params = load("params", input_filepath, seed)
TASKS = [(task[0], int(task[1][::-1], 2)) for task in params["TASKS"]]
hit_multipliers, patterns = zip(*TASKS)
lineages = load("lineages", input_filepath, seed)
def i2s(i):
return tuple((i >> n) & 1 for n in range(params["NUM_NODES"]))
ind = Individual(lineages[lineage][age].genome)
transitions = ind.play_game(hit_multipliers, patterns)
states = [
ps[: params["NUM_SENSORS"]] + cs[params["NUM_SENSORS"] :]
for ps, cs in zip(map(i2s, transitions[0]), map(i2s, transitions[1]))
]
trial_length = params["WORLD_HEIGHT"]
block_sizes = []
for pattern in patterns:
block_sizes += [sum(i2s(pattern))] * int(params["NUM_TRIALS"] / len(patterns))
json_dict = {
"generation": params["NGEN"] - age,
"connectivityMatrix": ind.cm.T.tolist(),
"nodeTypes": {"sensors": [0, 1], "hidden": [2, 3, 4, 5], "motors": [6, 7]},
"blockSize": block_sizes,
"Trial": [
{"trialNum": i, "lifeTable": states[(i * trial_length) : ((i + 1) * trial_length)]}
for i in range(params["NUM_TRIALS"])
],
}
with open(output_file, "w") as f:
json.dump(json_dict, f)
print("Saved game representation to `{}`.".format(output_file))
return json_dict示例11: __init__
def __init__(
self, data, expected_result, popsize=50, mut_rate=20, GA_printers=None
):
Individual.expected_result = {"rowdata": expected_result}
Individual.mutation_rate = mut_rate
Individual.data = data
self.popsize = popsize
self.population = []
for i in range(0, popsize):
c = Individual()
c.randomize()
self.population.append(c)
self.population.sort(key=attrgetter("fitness"), reverse=True)
self.GA_printers = GA_printers
self.generation = 0
self.wheel_size = sum(range(1, popsize + 1))
self.wheel = []
self.__init_wheel()
self.test = [0 for i in range(0, self.popsize)]示例12: test_addSex
def test_addSex(self):
indi = Individual()
value = "M"
indi.addSex(value)
self.assertEqual(indi.getSex(), value)
value = "F"
indi.addSex(value)
self.assertEqual(indi.getSex(), value) 示例13: mutate
def mutate(indiv: individual.Individual):
# for i in range(individual.Individual.gene_length):
# if elitism and i == 0:
# continue
# if random.random() <= mutation_rate:
# indiv.genes[i // 8] ^= 1 << (i % 8)
for i, _ in enumerate(indiv.genes):
# if elitism and i == 0:
# continue
if random.random() <= mutation_rate:
indiv.genes[i] = random.randint(0, 255)示例14: init_node_type_test
def init_node_type_test(self):
"""Puts Test in known state for Node type tests."""
self.clear_test_state()
player1 = Individual()
player2 = Individual()
testee = player1.get_robot()
testee.location = constants.testee_loc
ally = player1.get_robot()
ally.location = constants.ally_loc
enemy = player2.get_robot()
enemy.location = constants.enemy_loc
enemy.player_id = 1
self.robots = [testee, ally, enemy]
for bot in self.robots:
self.gamestate.add_robot(bot.location, bot.player_id)
# I use the default 'guard' action to determine when a rule evaluates
# False, so the test rule must not be the guard rule
while testee.eval_order[0].action == 'guard':
random.shuffle(testee.eval_order)
testee.eval_order[0].insert_random_parent()示例15: setUp
def setUp(self):
self.indi = Individual()
self.indi.addID('@[email protected]')
self.indi.addName('John Rivas')
self.indi.addSex('M')
self.indi.addBirt('9 MAY 1978')
self.indi.addDeat('12 APR 2013')
self.indi.addFams('@[email protected]')
self.indi.addFamc('@[email protected]')
self.fam1 = Family()
self.fam1.addFamID('@[email protected]')
self.fam1.addHusb('@[email protected]')
self.fam1.addWife('@[email protected]')
self.fam1.addChil('@[email protected]')
self.fam1.addChil('@[email protected]')
self.individuals = dict()
self.individuals["one"] = self.indi
self.families = dict()
self.families["one"] = self.fam1