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remove const ref push_back

release/4.3a0
Varun Agrawal 2024-09-05 15:51:37 -04:00
parent c7e1c60224
commit 3dbb16a114
2 changed files with 9 additions and 22 deletions
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20
gtsam/hybrid/HybridBayesNet.h
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@ -111,28 +111,10 @@ class GTSAM_EXPORT HybridBayesNet : public BayesNet<HybridConditional> {
* @return IsSharedPtr<CONDITIONAL> * @return IsSharedPtr<CONDITIONAL>
*/ */
template <class CONDITIONAL> template <class CONDITIONAL>
IsSharedPtr<CONDITIONAL> push_back(const CONDITIONAL &conditional) { void push_back(std::shared_ptr<CONDITIONAL> conditional) {
factors_.push_back(std::make_shared<HybridConditional>(conditional)); factors_.push_back(std::make_shared<HybridConditional>(conditional));
} }
/**
* @brief Add a conditional to the Bayes net.
* Implicitly convert to a HybridConditional.
*
* E.g.
* hbn.push_back(DiscreteConditional(m, "1/1"));
* hbn.push_back(GaussianConditional(X(0), Vector1(0.0), I_1x1));
*
* @tparam CONDITIONAL Type of conditional. This is const ref version.
* @param conditional The conditional as a const reference.
* @return IsSharedPtr<CONDITIONAL>
*/
template <class CONDITIONAL>
IsNotSharedPtr<CONDITIONAL> push_back(const CONDITIONAL &conditional) {
auto cond_shared_ptr = std::make_shared<CONDITIONAL>(conditional);
push_back(cond_shared_ptr);
}
/** /**
* Preferred: add a conditional directly using a pointer. * Preferred: add a conditional directly using a pointer.
* *

11
gtsam/hybrid/tests/testGaussianMixtureFactor.cpp
View File

@ -228,12 +228,17 @@ static HybridBayesNet GetGaussianMixtureModel(double mu0, double mu1,
auto c0 = make_shared<GaussianConditional>(z, Vector1(mu0), I_1x1, model0), auto c0 = make_shared<GaussianConditional>(z, Vector1(mu0), I_1x1, model0),
c1 = make_shared<GaussianConditional>(z, Vector1(mu1), I_1x1, model1); c1 = make_shared<GaussianConditional>(z, Vector1(mu1), I_1x1, model1);
GaussianMixture gm({z}, {}, {m}, {c0, c1}); KeyVector frontalKeys{z}, continuousParents;
DiscreteConditional mixing(m, "0.5/0.5"); DiscreteKeys discreteParents{m};
std::vector<GaussianConditional::shared_ptr> conditionals = {c0, c1};
auto gm = make_shared<GaussianMixture>(frontalKeys, continuousParents,
discreteParents, conditionals);
HybridBayesNet hbn; HybridBayesNet hbn;
hbn.push_back(gm); hbn.push_back(gm);
hbn.push_back(mixing);
auto mixing = make_shared<DiscreteConditional>(m, "0.5/0.5");
hbn.emplace_shared<HybridConditional>(mixing);
return hbn; return hbn;
} }