Remove one bougie constructor

release/4.3a0
Frank Dellaert 2024-09-28 22:15:35 -07:00
parent 85e57f1c20
commit 3a5d7a4648
3 changed files with 3 additions and 34 deletions

View File

@ -62,21 +62,6 @@ struct HybridGaussianConditional::ConstructorHelper {
}
}
/// Construct from means and a single sigma.
ConstructorHelper(Key x, const DiscreteKey mode,
const std::vector<Vector> &means, double sigma)
: nrFrontals(1), minNegLogConstant(0) {
std::vector<GaussianConditional::shared_ptr> gcs;
for (const auto &mean : means) {
auto c = GaussianConditional::sharedMeanAndStddev(x, mean, sigma);
gcs.push_back(c);
}
conditionals = Conditionals({mode}, gcs);
pairs = FactorValuePairs(conditionals, [](const auto &c) {
return GaussianFactorValuePair{c, 0.0};
});
}
/// Construct from means and a sigmas.
ConstructorHelper(Key x, const DiscreteKey mode,
const std::vector<std::pair<Vector, double>> &parameters)
@ -110,12 +95,6 @@ HybridGaussianConditional::HybridGaussianConditional(
: HybridGaussianConditional(DiscreteKeys{mode},
Conditionals({mode}, conditionals)) {}
HybridGaussianConditional::HybridGaussianConditional(
Key x, const DiscreteKey mode, const std::vector<Vector> &means,
double sigma)
: HybridGaussianConditional(DiscreteKeys{mode},
ConstructorHelper(x, mode, means, sigma)) {}
HybridGaussianConditional::HybridGaussianConditional(
Key x, const DiscreteKey mode,
const std::vector<std::pair<Vector, double>> &parameters)

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@ -87,17 +87,6 @@ class GTSAM_EXPORT HybridGaussianConditional
const DiscreteKey &mode,
const std::vector<GaussianConditional::shared_ptr> &conditionals);
/**
* @brief Construct from vector of means and a single sigma.
*
* @param x The continuous key.
* @param mode The discrete key.
* @param means The means for the Gaussian conditionals.
* @param sigma The standard deviation for the Gaussian conditionals.
*/
HybridGaussianConditional(Key x, const DiscreteKey mode,
const std::vector<Vector> &means, double sigma);
/**
* @brief Construct from vector of means and sigmas.
*

View File

@ -80,8 +80,9 @@ TEST(GaussianMixture, GaussianMixtureModel) {
double sigma = 2.0;
HybridBayesNet hbn;
std::vector<Vector> means{Vector1(mu0), Vector1(mu1)};
hbn.emplace_shared<HybridGaussianConditional>(Z(0), m, means, sigma);
std::vector<std::pair<Vector, double>> parameters{{Vector1(mu0), sigma},
{Vector1(mu1), sigma}};
hbn.emplace_shared<HybridGaussianConditional>(Z(0), m, parameters);
hbn.push_back(mixing);
// At the halfway point between the means, we should get P(m|z)=0.5