def from_dict(self, d):
m1 = BeamNGMember.from_dict(d['m1'])
m2 = BeamNGMember.from_dict(d['m2'])
ind = BeamNGIndividual(m1, m2, None, None)
ind.members_distance = d['members_distance']
ind.name = d['name']
return ind
def generate(self, visualise=False) -> BeamNGMember:
control_nodes = self.generate_control_nodes(visualise)
sample_nodes = catmull_rom(control_nodes, self.num_spline_nodes)
road = BeamNGMember(control_nodes, sample_nodes, self.num_spline_nodes,
self.road_bbox)
while not road.is_valid():
control_nodes = self.generate_control_nodes(visualise)
sample_nodes = catmull_rom(control_nodes, self.num_spline_nodes)
road = BeamNGMember(control_nodes, sample_nodes,
self.num_spline_nodes, self.road_bbox)
return road
def main():
storage = SeedStorage('short')
for i in range(1, 100):
member_filepath = storage.get_path_by_index(i)
if not member_filepath.exists():
continue
member = BeamNGMember.from_dict(storage.load_json_by_index(i))
sample_nodes = member.sample_nodes
road_imagery = BeamNGRoadImagery.from_sample_nodes(sample_nodes)
for extension in ['.jpg', '.svg']:
image_filename = member_filepath.with_suffix(extension)
print('saving', image_filename)
road_imagery.save(image_filename)
try:
if self.config.beamng_close_at_iteration:
self._close()
else:
if self.brewer:
self.brewer.beamng.stop_scenario()
except Exception as ex:
log.debug('end_iteration() failed:')
traceback.print_exception(type(ex), ex, ex.__traceback__)
def _close(self):
if self.brewer:
try:
self.brewer.beamng.close()
except Exception as ex:
log.debug('beamng.close() failed:')
traceback.print_exception(type(ex), ex, ex.__traceback__)
self.brewer = None
if __name__ == '__main__':
config = BeamNGConfig()
inst = BeamNGNvidiaOob(config)
while True:
seed_storage = SeedStorage('basic5')
for i in range(1, 11):
member = BeamNGMember.from_dict(seed_storage.load_json_by_index(i))
member.clear_evaluation()
inst.evaluate([member])
log.info(member)
def initial_population_generator(path, config, problem):
all_roads = [
filename
for filename in glob.glob(str(path) + "\*.json", recursive=True)
]
type = config.Feature_Combination
shuffle(all_roads)
roads = all_roads
original_set = list()
individuals = []
popsize = config.POPSIZE
for road in roads:
with open(road) as json_file:
data = json.load(json_file)
sample_nodes = data["road"]["nodes"]
for node in sample_nodes:
node[2] = -28.0
sample_nodes = np.array(sample_nodes)
records = data["records"]
bbox_size = (-250.0, 0.0, 250.0, 500.0)
road_bbox = RoadBoundingBox(bbox_size)
member = BeamNGMember(data["control_nodes"],
[tuple(t) for t in sample_nodes], 20, road_bbox)
member.config = config
member.problem = problem
simulation_id = time.strftime('%Y-%m-%d--%H-%M-%S', time.localtime())
sim_name = member.config.simulation_name.replace(
'$(id)', simulation_id)
simulation_data = SimulationData(sim_name)
states = []
for record in records:
state = VehicleState(timer=record["timer"],
pos=record["pos"],
dir=record["dir"],
vel=record["vel"],
steering=record["steering"],
steering_input=record["steering_input"],
brake=record["brake"],
brake_input=record["brake_input"],
throttle=record["throttle"],
throttle_input=record["throttle_input"],
wheelspeed=record["wheelspeed"],
vel_kmh=record["vel_kmh"])
sim_data_record = SimulationDataRecord(
**state._asdict(),
is_oob=record["is_oob"],
oob_counter=record["oob_counter"],
max_oob_percentage=record["max_oob_percentage"],
oob_distance=record["oob_distance"])
states.append(sim_data_record)
simulation_data.params = SimulationParams(
beamng_steps=data["params"]["beamng_steps"],
delay_msec=int(data["params"]["delay_msec"]))
simulation_data.road = DecalRoad.from_dict(data["road"])
simulation_data.info = SimulationInfo()
simulation_data.info.start_time = data["info"]["start_time"]
simulation_data.info.end_time = data["info"]["end_time"]
simulation_data.info.elapsed_time = data["info"]["elapsed_time"]
simulation_data.info.success = data["info"]["success"]
simulation_data.info.computer_name = data["info"]["computer_name"]
simulation_data.info.id = data["info"]["id"]
simulation_data.states = states
if len(states) > 0:
member.distance_to_boundary = simulation_data.min_oob_distance()
member.simulation = simulation_data
individual: BeamNGIndividual = BeamNGIndividual(member, config)
#individual.evaluate()
b = tuple()
feature_dimensions = generate_feature_dimension(type)
for ft in feature_dimensions:
i = feature_simulator(ft.feature_simulator, individual)
b = b + (i, )
individuals.append([b, road, individual])
starting_point = choice(individuals)
original_set.append(starting_point)
i = 0
best_ind = individuals[0]
while i < popsize - 1:
max_dist = 0
for ind in individuals:
dist = get_min_distance_from_set(ind, original_set)
if dist > max_dist:
max_dist = dist
best_ind = ind
original_set.append(best_ind)
i += 1
base = config.initial_population_folder
storage = SeedStorage(base)
for index, road in enumerate(original_set):
dst = storage.get_path_by_index(index + 1)
ind = road[2]
#copy(road[1], dst)
with open(road[1]) as ff:
json_file = json.load(ff)
with open(dst, 'w') as f:
f.write(
json.dumps({
"control_nodes":
json_file["control_nodes"],
ind.m.simulation.f_params:
ind.m.simulation.params._asdict(),
ind.m.simulation.f_info:
ind.m.simulation.info.__dict__,
ind.m.simulation.f_road:
ind.m.simulation.road.to_dict(),
ind.m.simulation.f_records:
[r._asdict() for r in ind.m.simulation.states]
}))
def from_dict(self, d):
m = BeamNGMember.from_dict(d['m'])
ind = BeamNGIndividual(m, None)
ind.name = d['name']
return ind
def generate_random_solution_without_sim(self):
"""
To ease the bootstrap of the algorithm, we can generate
the first solutions in the feature space, so that we start
filling the bins
"""
# "Generate random solution"
path = self.problem._seed_pool_strategy.get_seed()
with open(path) as json_file:
data = json.load(json_file)
sample_nodes = data["road"]["nodes"]
for node in sample_nodes:
node[2] = -28.0
sample_nodes = np.array(sample_nodes)
records = data["records"]
bbox_size = (-250.0, 0.0, 250.0, 500.0)
road_bbox = RoadBoundingBox(bbox_size)
member = BeamNGMember(data["control_nodes"],
[tuple(t) for t in sample_nodes],
len(data["control_nodes"]), road_bbox)
member.config = self.config
member.problem = self.problem
simulation_id = time.strftime('%Y-%m-%d--%H-%M-%S', time.localtime())
sim_name = member.config.simulation_name.replace(
'$(id)', simulation_id)
simulation_data = SimulationData(sim_name)
states = []
for record in records:
state = VehicleState(timer=record["timer"],
pos=record["pos"],
dir=record["dir"],
vel=record["vel"],
steering=record["steering"],
steering_input=record["steering_input"],
brake=record["brake"],
brake_input=record["brake_input"],
throttle=record["throttle"],
throttle_input=record["throttle_input"],
wheelspeed=record["wheelspeed"],
vel_kmh=record["vel_kmh"])
sim_data_record = SimulationDataRecord(
**state._asdict(),
is_oob=record["is_oob"],
oob_counter=record["oob_counter"],
max_oob_percentage=record["max_oob_percentage"],
oob_distance=record["oob_distance"])
states.append(sim_data_record)
simulation_data.params = SimulationParams(
beamng_steps=data["params"]["beamng_steps"],
delay_msec=int(data["params"]["delay_msec"]))
simulation_data.road = DecalRoad.from_dict(data["road"])
simulation_data.info = SimulationInfo()
simulation_data.info.start_time = data["info"]["start_time"]
simulation_data.info.end_time = data["info"]["end_time"]
simulation_data.info.elapsed_time = data["info"]["elapsed_time"]
simulation_data.info.success = data["info"]["success"]
simulation_data.info.computer_name = data["info"]["computer_name"]
simulation_data.info.id = data["info"]["id"]
simulation_data.states = states
if len(states) > 0:
member.distance_to_boundary = simulation_data.min_oob_distance()
member.simulation = simulation_data
individual: BeamNGIndividual = BeamNGIndividual(
member, self.config)
individual.seed = path
else:
print("*********Bug************")
return individual