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40 bool manyModes =
false) {
44 std::vector<std::pair<Vector, double>> measurementModels{{Z_1x1, 0.5},
46 for (
size_t i = 0;
i < num_measurements;
i++) {
49 X(0), measurementModels);
57 const size_t nrModes = manyModes ? num_measurements : 1;
58 for (
size_t i = 0;
i < nrModes;
i++) {
71 size_t num_measurements = 1, std::optional<VectorValues>
measurements = {},
72 bool manyModes =
false) {
Eigen::Matrix< double, 1, 1 > Vector1
A Bayes net of Gaussian Conditionals indexed by discrete keys.
const HybridBayesNet bayesNet
A conditional of gaussian conditionals indexed by discrete variables, as part of a Bayes Network....
Linearized Hybrid factor graph that uses type erasure.
HybridGaussianFactorGraph createHybridGaussianFactorGraph(size_t num_measurements=1, std::optional< VectorValues > measurements={}, bool manyModes=false)
std::vector< double > measurements
std::pair< Key, size_t > DiscreteKey
HybridBayesNet createHybridBayesNet(size_t num_measurements=1, bool manyModes=false)
static shared_ptr sharedMeanAndStddev(Args &&... args)
Create shared pointer by forwarding arguments to fromMeanAndStddev.
Matrix< RealScalar, Dynamic, Dynamic > M
gtsam
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autogenerated on Sun Nov 10 2024 04:07:34