test_two_state_estimation Namespace Reference

Functions
void	addMeasurement (HybridBayesNet &hbn, Key z_key, Key x_key, double sigma)
std::pair< double, double >	approximateDiscreteMarginal (const HybridBayesNet &hbn, const HybridGaussianConditional::shared_ptr &hybridMotionModel, const VectorValues &given, size_t N=100000)
	Approximate the discrete marginal P(m1) using importance sampling. More...
HybridBayesNet	CreateBayesNet (const HybridGaussianConditional::shared_ptr &hybridMotionModel, bool add_second_measurement=false)
	Create two state Bayes network with 1 or two measurement models. More...
static HybridGaussianConditional::shared_ptr	CreateHybridMotionModel (double mu0, double mu1, double sigma0, double sigma1)
	Create hybrid motion model p(x1 | x0, m1) More...
DiscreteKey	m1 (M(1), 2)

Function Documentation

addMeasurement()

void test_two_state_estimation::addMeasurement	(	HybridBayesNet &	hbn,
		Key	z_key,
		Key	x_key,
		double	sigma
	)

Definition at line 379 of file testHybridGaussianFactor.cpp.

approximateDiscreteMarginal()

std::pair<double, double> test_two_state_estimation::approximateDiscreteMarginal	(	const HybridBayesNet &	hbn,
		const HybridGaussianConditional::shared_ptr &	hybridMotionModel,
		const VectorValues &	given,
		size_t	N = 100000
	)

Approximate the discrete marginal P(m1) using importance sampling.

Create importance sampling network q(x0,x1,m) = p(x1|x0,m1) q(x0) P(m1), using q(x0) = N(z0, sigmaQ) to sample x0.

Definition at line 425 of file testHybridGaussianFactor.cpp.

CreateBayesNet()

HybridBayesNet test_two_state_estimation::CreateBayesNet	(	const HybridGaussianConditional::shared_ptr &	hybridMotionModel,
		bool	add_second_measurement = false
	)

Create two state Bayes network with 1 or two measurement models.

Definition at line 402 of file testHybridGaussianFactor.cpp.

CreateHybridMotionModel()

static HybridGaussianConditional::shared_ptr test_two_state_estimation::CreateHybridMotionModel ( double  mu0, double  mu1, double  sigma0, double  sigma1  )

static

Create hybrid motion model p(x1 | x0, m1)

Definition at line 386 of file testHybridGaussianFactor.cpp.

m1()

DiscreteKey test_two_state_estimation::m1	(	M(1)	,
		2
	)