Variables
	bn = LGBayesianNetwork(skel, teacher_nd)

	data = bn.randomsample(200)

	dpath = os.path.join(PKG_PATH, "test", "graph-test.txt")

	edges

	gs = LinearGaussianGraphState()

	nodes

	param_estimate = rospy.ServiceProxy("pgm_learner/linear_gaussian/parameter_estimation", LinearGaussianParameterEstimation)

	PKG_PATH = rospkg.RosPack().get_path("pgm_learner")

	PP = pprint.PrettyPrinter(indent=2)

	req = LinearGaussianParameterEstimationRequest()

	skel = GraphSkeleton()

	teacher_nd = NodeData()

	tpath = os.path.join(PKG_PATH, "test", "graph-lg-test.txt")

Variable Documentation

◆ bn

linear_gaussian_bayesian_parameter_estimation_sample.bn = LGBayesianNetwork(skel, teacher_nd)

Definition at line 39 of file linear_gaussian_bayesian_parameter_estimation_sample.py.

◆ data

linear_gaussian_bayesian_parameter_estimation_sample.data = bn.randomsample(200)

Definition at line 40 of file linear_gaussian_bayesian_parameter_estimation_sample.py.

◆ dpath

linear_gaussian_bayesian_parameter_estimation_sample.dpath = os.path.join(PKG_PATH, "test", "graph-test.txt")

Definition at line 26 of file linear_gaussian_bayesian_parameter_estimation_sample.py.

◆ edges

linear_gaussian_bayesian_parameter_estimation_sample.edges

Definition at line 33 of file linear_gaussian_bayesian_parameter_estimation_sample.py.

◆ gs

linear_gaussian_bayesian_parameter_estimation_sample.gs = LinearGaussianGraphState()

Definition at line 43 of file linear_gaussian_bayesian_parameter_estimation_sample.py.

◆ nodes

linear_gaussian_bayesian_parameter_estimation_sample.nodes

Definition at line 32 of file linear_gaussian_bayesian_parameter_estimation_sample.py.

◆ param_estimate

linear_gaussian_bayesian_parameter_estimation_sample.param_estimate = rospy.ServiceProxy("pgm_learner/linear_gaussian/parameter_estimation", LinearGaussianParameterEstimation)

Definition at line 22 of file linear_gaussian_bayesian_parameter_estimation_sample.py.