def main(self):
rospy.init_node('servo_demo', disable_signals=True)
self.info('Started.')
contracts.disable_all()
boot_root = rospy.get_param('~boot_root')
boot_root = expand_environment(boot_root)
config_dir = rospy.get_param('~config_dir')
id_robot_learned = rospy.get_param('~id_robot_learn')
self.info('loading %r' % config_dir)
GlobalConfig.global_load_dir(config_dir)
id_agent = rospy.get_param('~id_agent')
self.id_robot = rospy.get_param('~id_robot')
self.sleep = rospy.get_param('~sleep', 0.005)
self.info('sleep: %s' % self.sleep)
self.error_threshold = float(rospy.get_param('~error_threshold'))
raise_if_no_state = rospy.get_param('~raise_if_no_state', True)
data_central = DataCentral(boot_root)
ag_st = load_agent_state(data_central,
id_agent,
id_robot_learned,
reset_state=False,
raise_if_no_state=raise_if_no_state)
self.agent, state = ag_st
self.info('Loaded state: %s' % state)
self.servo_agent = self.agent.get_servo()
bo_config = get_boot_config()
self.robot = bo_config.robots.instance(self.id_robot)
self.boot_spec = self.robot.get_spec()
self.publish_info_init()
self.y = None
self.y_goal = None
self.started_now = False
self.stopped_now = False
self.e0 = 1
self.e = 1
self.last_boot_data = None
self.state = STATE_WAIT
self.info('Defining services')
rospy.Service('set_goal', Empty, self.srv_set_goal)
rospy.Service('start_servo', Empty, self.srv_start_servo)
rospy.Service('stop_servo', Empty, self.srv_stop_servo)
self.info('Finished initialization')
self.count = 0
self.go()
def main(self):
rospy.init_node('servo_demo', disable_signals=True)
self.info('Started.')
contracts.disable_all()
boot_root = rospy.get_param('~boot_root')
boot_root = expand_environment(boot_root)
config_dir = rospy.get_param('~config_dir')
id_robot_learned = rospy.get_param('~id_robot_learn')
self.info('loading %r' % config_dir)
GlobalConfig.global_load_dir(config_dir)
id_agent = rospy.get_param('~id_agent')
self.id_robot = rospy.get_param('~id_robot')
self.sleep = rospy.get_param('~sleep', 0.005)
self.info('sleep: %s' % self.sleep)
self.error_threshold = float(rospy.get_param('~error_threshold'))
raise_if_no_state = rospy.get_param('~raise_if_no_state', True)
data_central = DataCentral(boot_root)
ag_st = load_agent_state(data_central, id_agent, id_robot_learned,
reset_state=False,
raise_if_no_state=raise_if_no_state)
self.agent, state = ag_st
self.info('Loaded state: %s' % state)
self.servo_agent = self.agent.get_servo()
bo_config = get_boot_config()
self.robot = bo_config.robots.instance(self.id_robot)
self.boot_spec = self.robot.get_spec()
self.publish_info_init()
self.y = None
self.y_goal = None
self.started_now = False
self.stopped_now = False
self.e0 = 1
self.e = 1
self.last_boot_data = None
self.state = STATE_WAIT
self.info('Defining services')
rospy.Service('set_goal', Empty, self.srv_set_goal)
rospy.Service('start_servo', Empty, self.srv_start_servo)
rospy.Service('stop_servo', Empty, self.srv_stop_servo)
self.info('Finished initialization')
self.count = 0
self.go()
def report_prediction2(data_central, id_agent, id_robot, exp=myexp):
set_boot_config(data_central.get_bo_config())
agent, state = load_agent_state(data_central, id_agent, id_robot,
reset_state=False, raise_if_no_state=True)
model = agent.estimator.get_model()
warnings.warn('does not work anymore')
slt = BDSEServoLongTerm()
slt.set_model(model)
return slt.report()
def report_prediction(data_central, id_agent, id_robot, exp=myexp):
set_boot_config(data_central.get_bo_config())
agent, state = load_agent_state(data_central, id_agent, id_robot,
reset_state=False, raise_if_no_state=True)
r = Report('report-pred')
f = r.figure()
model = agent.estimator.get_model()
# R = agent.estimator.y_stats.get_correlation()
M = model.M
N, _, K = M.shape
# W = np.eye(N)
W = np.zeros((N, N))
for i, j in itertools.product(range(N), range(N)):
if np.abs(i - j) == 1:
W[i, j] = 1
# W = R * R * R * R * R
f.data('W', W).display('posneg').add_to(f, caption='W')
times = [0.25, 0.5, 1, 2, 4, 8, 16]
for k in range(K):
A = M[:, :, k]
# AW = A * W
# AW = (AW - AW.T) / 2
report_exp(r, 'k=%d' % k, A, times, exp=exp)
report_exp(r, 'k=%dneg' % k, -A, times, exp=exp)
for k1, k2 in itertools.product(range(K), range(K)):
A = M[:, :, k1] + M[:, :, k2]
report_exp(r, 'k1=%d,k2=%d' % (k1, k2), A, times, exp=exp)
# D1 = np.zeros((N, N))
# for i, j in itertools.product(range(N), range(N)):
# if i == j + 2:
# D1[i, j] = 1
# if i == j + 1:
# D1[i, j] = 2
# if i == j - 1:
# D1[i, j] = -2
# if i == j - 2:
# D1[i, j] = -1
#
# report_exp(r, 'D1', D1, times, exp=exp)
return r
