def run_server():
conf = parser.parse_args()
conf.enable_light_sensor = False
conf.output_directory = None
conf.max_lifetime = 999999
conf.initial_age_mu = 500
conf.initial_age_sigma = 500
world = yield From(World.create(conf))
yield From(world.pause(True))
trees, bboxes = yield From(world.generate_population(40))
insert_queue = zip(trees, bboxes)
yield From(world.pause(False))
for tree, bbox in insert_queue[:40]:
fut = yield From(birth(world, tree, bbox, None))
yield From(fut)
yield From(sleep_sim_time(world, 1.0))
print("Inserted all robots")
sim_time_sec = 1.0
while True:
before = time.time()
yield From(sleep_sim_time(world, sim_time_sec))
after = time.time()
diff = after - before
print(sim_time_sec / diff)
def main():
conf = parser.parse_args()
brain_spec = get_brain_spec(conf)
print "READING FILES!!!!!!!!!!!!!!!!!!!"
with open(conf.genotype_file_1, 'r') as gen_file1:
gen_yaml1 = gen_file1.read()
with open(conf.genotype_file_2, 'r') as gen_file2:
gen_yaml2 = gen_file2.read()
print "CONVERTING!!!!!!!!!"
genotype1 = yaml_to_genotype(gen_yaml1,
brain_spec,
keep_historical_marks=True)
genotype2 = yaml_to_genotype(gen_yaml2,
brain_spec,
keep_historical_marks=True)
print "genotype 1:"
print genotype1.debug_string()
print "genotype 2:"
print genotype2.debug_string()
print "CALCULATING SIMILARITY!!!!!!!!!!!!!!!!!!"
dissimilarity = GeneticEncoding.get_dissimilarity(genotype1, genotype2)
print "DISSIMILARITY = {0}".format(dissimilarity)
def run_server():
conf = parser.parse_args()
conf.enable_light_sensor = False
conf.output_directory = None
conf.max_lifetime = 999999
conf.initial_age_mu = 500
conf.initial_age_sigma = 500
world = yield From(World.create(conf))
yield From(world.pause(True))
trees, bboxes = yield From(world.generate_population(40))
insert_queue = zip(trees, bboxes)
yield From(world.pause(False))
for tree, bbox in insert_queue[:40]:
fut = yield From(birth(world, tree, bbox, None))
yield From(fut)
yield From(sleep_sim_time(world, 1.0))
print("Inserted all robots")
sim_time_sec = 1.0
while True:
before = time.time()
yield From(sleep_sim_time(world, sim_time_sec))
after = time.time()
diff = after - before
print(sim_time_sec / diff)
def run():
"""
:return:
"""
conf = parser.parse_args()
world = yield From(OfflineEvoManager.create(conf))
yield From(world.run())
def main():
print "START"
conf = parser.parse_args()
conf.pose_update_frequency = 5
def handler(loop, context):
exc = context['exception']
if isinstance(exc, DisconnectError) or isinstance(
exc, ConnectionResetError):
print("Got disconnect / connection reset - shutting down.")
sys.exit(1)
raise context['exception']
try:
loop = trollius.get_event_loop()
loop.set_debug(enabled=True)
# logging.basicConfig(level=logging.DEBUG)
loop.set_exception_handler(handler)
loop.run_until_complete(run(conf))
print "FINISH"
except KeyboardInterrupt:
print("Got Ctrl+C, shutting down.")
except ConnectionRefusedError:
print("Connection refused, are the world and the analyzer loaded?")
def main():
conf = parser.parse_args()
in_path = conf.file_name
out_path = os.path.join(os.path.dirname(in_path), conf.output)
with open(in_path, 'r') as yamlfile:
yaml_bot = yamlfile.read()
body_spec = get_body_spec(conf)
brain_spec = get_extended_brain_spec(conf)
print "converting to protobuf..."
pb_bot = yaml_to_robot(body_spec, brain_spec, yaml_bot)
cpg_factory = CPG_Factory(body_spec=body_spec, brain_spec=brain_spec)
loopback = conf.loopback
print "Loopback: {0}".format(loopback)
coupling = conf.coupling
print "Coupling: {0}".format(coupling)
cpg_factory.add_CPGs(pb_bot, loopback, coupling)
print "converting to yaml..."
yaml_bot = robot_to_yaml(body_spec, brain_spec, pb_bot)
with open(out_path, 'w') as out_file:
out_file.write(yaml_bot)
print "done"
def main():
conf = parser.parse_args()
in_path = conf.file_name
out_path = os.path.join(os.path.dirname(in_path), conf.output)
with open(in_path, 'r') as yamlfile:
yaml_bot = yamlfile.read()
body_spec = get_body_spec(conf)
brain_spec = get_brain_spec(conf)
print "converting to protobuf..."
pb_bot = yaml_to_robot(body_spec, brain_spec, yaml_bot)
cpg_factory = CPG_Factory(body_spec=body_spec, brain_spec=brain_spec)
cpg_factory.add_CPGs(pb_bot, conf.type)
print "converting to yaml..."
yaml_bot = robot_to_yaml(body_spec, brain_spec, pb_bot)
with open(out_path, 'w') as out_file:
out_file.write(yaml_bot)
print "done"
def run():
"""
:return:
"""
conf = parser.parse_args()
world = yield From(OfflineEvoManager.create(conf))
yield From(world.run())
def run_server():
conf = parser.parse_args()
conf.analyzer_address = None
world = yield From(World.create(conf))
yield From(world.pause(True))
with open("/home/elte/mt/tol/scripts/starfish.yaml", "rb") as f:
robot_yaml = f.read()
body_spec = world.builder.body_builder.spec
brain_spec = world.builder.brain_builder.spec
bot = yaml_to_robot(body_spec, brain_spec, robot_yaml)
fname = conf.output_directory+"/revolve_benchmark.csv"
exists = os.path.exists(fname)
if exists:
f = open(fname, 'ab', buffering=1)
else:
f = open(fname, 'wb', buffering=1)
output = csv.writer(f, delimiter=',')
if not exists:
output.writerow(['run', 'population_size', 'step_size',
'sim_time', 'real_time', 'factor'])
n_bots = [5, 10, 15, 20, 25, 30, 35, 40, 45, 50]
sim_time = 5.0
runs = 20
yield From(world.pause(False))
for n in n_bots:
poses = get_poses(n)
trees = [Tree.from_body_brain(bot.body, bot.brain, body_spec) for _ in range(n)]
for i in range(runs):
yield From(wait_for(world.insert_population(trees, poses)))
while world.last_time is None:
yield From(trollius.sleep(0.1))
sim_before = world.last_time
before = time.time()
while float(world.last_time - sim_before) < sim_time:
yield From(trollius.sleep(0.1))
sim_diff = float(world.last_time - sim_before)
diff = time.time() - before
output.writerow((i, n, conf.world_step_size, sim_diff,
diff, sim_diff / diff))
yield From(wait_for(world.delete_all_robots()))
yield From(trollius.sleep(0.3))
def run():
"""
The main coroutine, which is started below.
"""
# Parse command line / file input arguments
conf = parser.parse_args()
# Adding brain configuration
with open(conf.brain_conf_path, 'r') as f:
s = f.read()
brain_conf = ast.literal_eval(s)
if conf.load_controller != "None":
brain_conf["policy_load_path"] = conf.load_controller
conf.brain_conf = brain_conf
# This disables the analyzer; enable it if you want to generate valid robots
# Can also do this using arguments of course, just pass an empty string
# conf.analyzer_address = None
with open("{}.yaml".format(conf.robot_name), 'r') as yamlfile:
bot_yaml = yamlfile.read()
# Create the world, this connects to the Gazebo world
world = yield From(World.create(conf))
# These are useful when working with YAML
body_spec = world.builder.body_builder.spec
brain_spec = world.builder.brain_builder.spec
# Create a robot from YAML
robot = yaml_to_robot(body_spec, brain_spec, bot_yaml)
# Create a revolve.angle `Tree` representation from the robot, which
# is what is used in the world manager.
robot_tree = Tree.from_body_brain(robot.body, robot.brain, body_spec)
# Insert the robot into the world. `insert_robot` resolves when the insert
# request is sent, the future it returns resolves when the robot insert
# is actually confirmed and a robot manager object has been created
pose = Pose(position=Vector3(0, 0, 0.05))
future = yield From(world.insert_robot(robot_tree, pose, "{}-{}".format(conf.robot_name, conf.experiment_round)))
robot_manager = yield From(future)
# I usually start the world paused, un-pause it here. Note that
# pause again returns a future for when the request is sent,
# that future in turn resolves when a response has been received.
# This is the general convention for all message actions in the
# world manager. `wait_for` saves the hassle of grabbing the
# intermediary future in this case.
yield From(wait_for(world.pause(True)))
# Start a run loop to do some stuff
while True:
# Print robot fitness every second
print("Robot fitness: %f" % robot_manager.fitness())
yield From(trollius.sleep(1.0))
def run_server():
conf = parser.parse_args()
conf.enable_light_sensor = False
conf.output_directory = None
conf.max_lifetime = 999999
conf.initial_age_mu = 500
conf.initial_age_sigma = 500
world = yield From(World.create(conf))
yield From(world.pause(False))
trees, bboxes = yield From(world.generate_population(30))
insert_queue = zip(trees, bboxes)
for tree, bbox in insert_queue[:15]:
fut = yield From(birth(world, tree, bbox, None))
yield From(fut)
yield From(sleep_sim_time(world, 1.0))
sim_time_sec = 5.0
while True:
bots = []
for tree, bbox in insert_queue[15:]:
fut = yield From(birth(world, tree, bbox, None))
bot = yield From(fut)
bots.append(bot)
yield From(sleep_sim_time(world, 1.0))
print("Inserted all robots")
before = time.time()
yield From(sleep_sim_time(world, sim_time_sec))
after = time.time()
diff = after - before
print(sim_time_sec / diff)
futs = []
for robot in bots:
fut = yield From(world.delete_robot(robot))
futs.append(fut)
yield From(multi_future(futs))
yield From(trollius.sleep(0.1))
print("Deleted all robots")
def run_server():
conf = parser.parse_args()
conf.enable_light_sensor = False
conf.output_directory = None
conf.max_lifetime = 999999
conf.initial_age_mu = 500
conf.initial_age_sigma = 500
world = yield From(World.create(conf))
yield From(world.pause(False))
trees, bboxes = yield From(world.generate_population(30))
insert_queue = zip(trees, bboxes)
for tree, bbox in insert_queue[:15]:
fut = yield From(birth(world, tree, bbox, None))
yield From(fut)
yield From(sleep_sim_time(world, 1.0))
sim_time_sec = 5.0
while True:
bots = []
for tree, bbox in insert_queue[15:]:
fut = yield From(birth(world, tree, bbox, None))
bot = yield From(fut)
bots.append(bot)
yield From(sleep_sim_time(world, 1.0))
print("Inserted all robots")
before = time.time()
yield From(sleep_sim_time(world, sim_time_sec))
after = time.time()
diff = after - before
print(sim_time_sec / diff)
futs = []
for robot in bots:
fut = yield From(world.delete_robot(robot))
futs.append(fut)
yield From(multi_future(futs))
yield From(trollius.sleep(0.1))
print("Deleted all robots")
def main():
args = parser.parse_args()
def handler(loop, context):
exc = context['exception']
if isinstance(exc, DisconnectError) or isinstance(
exc, ConnectionResetError):
print("Got disconnect / connection reset - shutting down.")
sys.exit(0)
raise context['exception']
try:
loop = trollius.get_event_loop()
loop.set_debug(enabled=True)
logging.basicConfig(level=logging.DEBUG)
loop.set_exception_handler(handler)
loop.run_until_complete(run_server(args))
except KeyboardInterrupt:
print("Got Ctrl+C, shutting down.")
def main():
args = parser.parse_args()
seed = random.randint(1, 1000000) if args.seed < 0 else args.seed
random.seed(seed)
print("Seed: %d" % seed)
def handler(loop, context):
exc = context['exception']
if isinstance(exc, DisconnectError) or isinstance(exc, ConnectionResetError):
print("Got disconnect / connection reset - shutting down.")
sys.exit(0)
raise context['exception']
try:
loop = trollius.get_event_loop()
loop.set_exception_handler(handler)
loop.run_until_complete(run_server(args))
except KeyboardInterrupt:
print("Got Ctrl+C, shutting down.")
except ConnectionRefusedError:
print("Connection refused, are the world and the analyzer loaded?")
def main():
args = parser.parse_args()
# brain_spec = get_brain_spec(args)
# body_spec = get_body_spec(args)
brain_parser = NeuralNetworkParser(brain_spec)
pb_robot = yaml_to_robot(body_spec, brain_spec, yaml_robot)
print "yaml converted to pb"
mutator = Mutator()
genotype = brain_parser.robot_to_genotype(pb_robot, mutator)
print "pb converted to genotype"
print ""
print "neurons:"
neurons, connections = genotype.to_lists()
for neuron in neurons:
print neuron
print ""
print "connections:"
for connection in connections:
print connection
def main():
try:
loop = trollius.get_event_loop()
loop.run_until_complete(run(parser.parse_args()))
except KeyboardInterrupt:
print("Got Ctrl+C, shutting down.")
import uuid
from revolve.spec.msgs import Robot
import os
import sys
sys.path.append(os.path.dirname(os.path.abspath(__file__))+'/../')
from tol.spec import get_body_spec
from tol.config import parser, make_revolve_config
from sdfbuilder.math import Vector3
conf = make_revolve_config(parser.parse_args())
body_spec = get_body_spec(conf)
print("exp,run,robot_id,gene_id,origin_id,type,r,g,b")
def find_part_uuid(type, vec, parent_parts):
for pid, ptype, pvec, porigin in parent_parts:
if ptype == type and abs(vec - pvec) < 1e-8:
return pid, porigin
return None, None
def process_parts(robot_id, part, parent_parts, cur=None):
# Last three parameters are always color
type, vec = part.type, Vector3(*[p.value for p in part.param[-3:]])
pid, porigin = find_part_uuid(type, vec, parent_parts)
if pid is None:
pid, porigin = uuid.uuid4(), robot_id
import uuid
from revolve.spec.msgs import Robot
import os
import sys
sys.path.append(os.path.dirname(os.path.abspath(__file__)) + '/../')
from tol.spec import get_body_spec
from tol.config import parser, make_revolve_config
from sdfbuilder.math import Vector3
conf = make_revolve_config(parser.parse_args())
body_spec = get_body_spec(conf)
print("exp,run,robot_id,gene_id,origin_id,type,r,g,b")
def find_part_uuid(type, vec, parent_parts):
for pid, ptype, pvec, porigin in parent_parts:
if ptype == type and abs(vec - pvec) < 1e-8:
return pid, porigin
return None, None
def process_parts(robot_id, part, parent_parts, cur=None):
# Last three parameters are always color
type, vec = part.type, Vector3(*[p.value for p in part.param[-3:]])
pid, porigin = find_part_uuid(type, vec, parent_parts)
if pid is None:
pid, porigin = uuid.uuid4(), robot_id
def run_server():
conf = parser.parse_args()
conf.analyzer_address = None
world = yield From(World.create(conf))
yield From(world.pause(True))
with open("/home/elte/mt/tol/scripts/starfish.yaml", "rb") as f:
robot_yaml = f.read()
body_spec = world.builder.body_builder.spec
brain_spec = world.builder.brain_builder.spec
bot = yaml_to_robot(body_spec, brain_spec, robot_yaml)
fname = conf.output_directory + "/revolve_benchmark.csv"
exists = os.path.exists(fname)
if exists:
f = open(fname, 'ab', buffering=1)
else:
f = open(fname, 'wb', buffering=1)
output = csv.writer(f, delimiter=',')
if not exists:
output.writerow([
'run', 'population_size', 'step_size', 'sim_time', 'real_time',
'factor'
])
n_bots = [5, 10, 15, 20, 25, 30, 35, 40, 45, 50]
sim_time = 5.0
runs = 20
yield From(world.pause(False))
for n in n_bots:
poses = get_poses(n)
trees = [
Tree.from_body_brain(bot.body, bot.brain, body_spec)
for _ in range(n)
]
for i in range(runs):
yield From(wait_for(world.insert_population(trees, poses)))
while world.last_time is None:
yield From(trollius.sleep(0.1))
sim_before = world.last_time
before = time.time()
while float(world.last_time - sim_before) < sim_time:
yield From(trollius.sleep(0.1))
sim_diff = float(world.last_time - sim_before)
diff = time.time() - before
output.writerow(
(i, n, conf.world_step_size, sim_diff, diff, sim_diff / diff))
yield From(wait_for(world.delete_all_robots()))
yield From(trollius.sleep(0.3))
import sys
import os
import glob
sys.path.append(os.path.dirname(os.path.abspath(__file__))+'/../')
from revolve.angle.representation import Tree
from revolve.spec import Robot
from tol.spec import get_body_spec
from tol.config import parser, make_revolve_config
from tol.util.analyze import list_extremities, count_joints, count_motors
conf = parser.parse_args([])
make_revolve_config(conf)
body_spec = get_body_spec(conf)
input_dirs = sys.argv[1:]
for input_dir in input_dirs:
input_dir = os.path.abspath(input_dir)
print("Processing %s..." % input_dir)
files = glob.glob(os.path.join(input_dir, "*.pb"))
with open(os.path.join(input_dir, "robot_details.csv"), 'w') as o:
o.write("robot_id,size,extremity_id,extremity_size,joint_count,motor_count\n")
for filename in files:
robot = Robot()
with open(filename, "rb") as f:
robot.ParseFromString(f.read())
import sys
import os
import glob
sys.path.append(os.path.dirname(os.path.abspath(__file__)) + '/../')
from revolve.angle.representation import Tree
from revolve.spec import Robot
from tol.spec import get_body_spec
from tol.config import parser, make_revolve_config
from tol.util.analyze import list_extremities, count_joints, count_motors
conf = parser.parse_args([])
make_revolve_config(conf)
body_spec = get_body_spec(conf)
input_dirs = sys.argv[1:]
for input_dir in input_dirs:
input_dir = os.path.abspath(input_dir)
print("Processing %s..." % input_dir)
files = glob.glob(os.path.join(input_dir, "*.pb"))
with open(os.path.join(input_dir, "robot_details.csv"), 'w') as o:
o.write(
"robot_id,size,extremity_id,extremity_size,joint_count,motor_count\n"
)
for filename in files:
robot = Robot()
with open(filename, "rb") as f:
robot.ParseFromString(f.read())
async def run():
conf = parser.parse_args()
conf.evaluation_time_sigma = 2.0
conf.weight_mutation_probability = 0.8
conf.weight_mutation_sigma = 5.0
conf.param_mutation_probability = 0.8
conf.param_mutation_sigma = 0.25
# this is the world state update frequency in simulation Hz
conf.pose_update_frequency = 5 # in simulation Hz
# update frequency of sensors in simulation Hz (default 10Hz)
# conf.sensor_update_rate = 10.
# # these are irrelevant parameters but we need to set them anyway,
# # otherwise it won't work
# conf.min_parts = 1
# conf.max_parts = 3
# conf.arena_size = (3, 3)
# conf.max_lifetime = 99999
# conf.initial_age_mu = 99999
# conf.initial_age_sigma = 1
# conf.age_cutoff = 99999
# create the learning manager
world = await LearningManager.create(conf)
await world.pause(True)
path_to_log_dir = os.path.join(world.path_to_log_dir, "learner1")
body_spec = get_body_spec(conf)
brain_spec = get_extended_brain_spec(conf)
# mutation spec contains info about what parameters of neurons can be mutated
mut_spec = get_extended_mutation_spec(conf.param_mutation_sigma,
conf.weight_mutation_sigma)
# what types of neurons can be added to the network
# allowed_types = ["Simple", "Sigmoid", "DifferentialCPG"]
# allowed_types = ["Simple", "Sigmoid"]
allowed_types = ["Simple"]
mutator = Mutator(mut_spec, allowed_neuron_types=allowed_types)
# if we are not restoring a saved state:
if not world.do_restore:
with open(conf.test_bot, 'r') as yamlfile:
bot_yaml = yamlfile.read()
pose = Pose(position=Vector3(0, 0, 0.2))
bot = yaml_to_robot(body_spec, brain_spec, bot_yaml)
tree = Tree.from_body_brain(bot.body, bot.brain, body_spec)
robot = await world.insert_robot(tree, pose)
learner = RobotLearner(world=world,
robot=robot,
brain_spec=brain_spec,
mutator=mutator,
conf=conf)
gen_files = []
init_brain_list = None
if (os.path.isdir(path_to_log_dir)):
gen_files = list(fname for fname in os.listdir(path_to_log_dir) if \
fnmatch.fnmatch(fname, "gen_*_genotypes.log"))
# if we are reading an initial population from a file:
if len(gen_files) > 0:
gen_files = sorted(gen_files,
key=lambda item: int(item.split('_')[1]))
last_gen_file = gen_files[-1]
num_generations = int(last_gen_file.split('_')[1]) # + 1
num_brains_evaluated = conf.population_size * num_generations
print("last generation file = {0}".format(last_gen_file))
# get list of brains from the last generation log file:
init_brain_list, min_mark, max_mark = \
get_brains_from_file(os.path.join(path_to_log_dir, last_gen_file), brain_spec)
print("Max historical mark = {0}".format(max_mark))
# set mutator's innovation number according to the max historical mark:
mutator.innovation_number = max_mark + 1
learner.total_brains_evaluated = num_brains_evaluated
learner.generation_number = num_generations
# initialize learner with initial list of brains:
await world.add_learner(learner, "learner1", init_brain_list)
print(learner.parameter_string())
# log experiment parameter values:
create_param_log_file(conf, learner.generation_number,
os.path.join(path_to_log_dir, "parameters.log"))
# copy the robot body file:
shutil.copy(conf.test_bot, path_to_log_dir)
# if we are restoring a saved state:
else:
print("WORLD RESTORED FROM {0}".format(world.world_snapshot_filename))
print("STATE RESTORED FROM {0}".format(world.snapshot_filename))
print("WORLD CREATED")
await world.run()
def main():
try:
loop = trollius.get_event_loop()
loop.run_until_complete(run(parser.parse_args()))
except KeyboardInterrupt:
print("Got Ctrl+C, shutting down.")
