gtsam::tiny Namespace Reference

Functions
HybridBayesNet	createHybridBayesNet (size_t num_measurements=1, bool manyModes=false)
HybridGaussianFactorGraph	createHybridGaussianFactorGraph (size_t num_measurements=1, std::optional< VectorValues > measurements={}, bool manyModes=false)

Variables
const DiscreteKey	mode {M(0), 2}

Function Documentation

createHybridBayesNet()

HybridBayesNet gtsam::tiny::createHybridBayesNet ( size_t  num_measurements = 1, bool  manyModes = false  )

inline

Create a tiny two variable hybrid model which represents the generative probability P(z,x,mode) = P(z|x,mode)P(x)P(mode). num_measurements is the number of measurements of the continuous variable x0. If manyModes is true, then we introduce one mode per measurement.

Definition at line 39 of file TinyHybridExample.h.

createHybridGaussianFactorGraph()

HybridGaussianFactorGraph gtsam::tiny::createHybridGaussianFactorGraph ( size_t  num_measurements = 1, std::optional< VectorValues >  measurements = {}, bool  manyModes = false  )

inline

Create a tiny two variable hybrid factor graph which represents a discrete mode and a continuous variable x0, given a number of measurements of the continuous variable x0. If no measurements are given, they are sampled from the generative Bayes net model HybridBayesNet::Example(num_measurements)

Definition at line 70 of file TinyHybridExample.h.

Variable Documentation

mode

const DiscreteKey gtsam::tiny::mode {M(0), 2}

Definition at line 31 of file TinyHybridExample.h.