Functions | Variables
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.



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autogenerated on Sun Nov 10 2024 04:14:54