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De-clutter header

release/4.3a0
Frank Dellaert 2024-09-26 11:45:09 -07:00
parent ebebf7ddd5
commit e04f0afd0e
2 changed files with 28 additions and 39 deletions
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65
gtsam/hybrid/HybridGaussianConditional.h
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@ -64,47 +64,11 @@ class GTSAM_EXPORT HybridGaussianConditional
private: private:
Conditionals conditionals_; ///< a decision tree of Gaussian conditionals. Conditionals conditionals_; ///< a decision tree of Gaussian conditionals.
///< Negative-log of the normalization constant (log(\sqrt(|2πΣ|))). ///< Negative-log of the normalization constant (log(\sqrt(|2πΣ|))).
///< Take advantage of the neg-log space so everything is a minimization ///< Take advantage of the neg-log space so everything is a minimization
double negLogConstant_; double negLogConstant_;
/// Helper struct for private constructor.
struct ConstructorHelper {
KeyVector frontals;
KeyVector parents;
KeyVector continuousKeys;
HybridGaussianFactor::FactorValuePairs pairs;
double negLogConstant;
ConstructorHelper(const Conditionals &conditionals);
};
/// Private constructor
HybridGaussianConditional(
const DiscreteKeys &discreteParents,
const HybridGaussianConditional::Conditionals &conditionals,
const ConstructorHelper &helper)
: BaseFactor(helper.continuousKeys, discreteParents, helper.pairs),
BaseConditional(helper.frontals.size()),
conditionals_(conditionals),
negLogConstant_(helper.negLogConstant) {}
/**
* @brief Convert a HybridGaussianConditional of conditionals into
* a DecisionTree of Gaussian factor graphs.
*/
GaussianFactorGraphTree asGaussianFactorGraphTree() const;
/**
* @brief Helper function to get the pruner functor.
*
* @param discreteProbs The pruned discrete probabilities.
* @return std::function<GaussianConditional::shared_ptr(
* const Assignment<Key> &, const GaussianConditional::shared_ptr &)>
*/
std::function<GaussianConditional::shared_ptr(
const Assignment<Key> &, const GaussianConditional::shared_ptr &)>
prunerFunc(const DecisionTreeFactor &discreteProbs);
public: public:
/// @name Constructors /// @name Constructors
/// @{ /// @{
@ -220,6 +184,33 @@ class GTSAM_EXPORT HybridGaussianConditional
/// @} /// @}
private: private:
/// Helper struct for private constructor.
struct ConstructorHelper {
KeyVector frontals, parents, continuousKeys;
HybridGaussianFactor::FactorValuePairs pairs;
double negLogConstant;
/// Compute all variables needed for the private constructor below.
ConstructorHelper(const Conditionals &conditionals);
};
/// Private constructor that uses helper struct above.
HybridGaussianConditional(
const DiscreteKeys &discreteParents,
const HybridGaussianConditional::Conditionals &conditionals,
const ConstructorHelper &helper)
: BaseFactor(helper.continuousKeys, discreteParents, helper.pairs),
BaseConditional(helper.frontals.size()),
conditionals_(conditionals),
negLogConstant_(helper.negLogConstant) {}
/// Convert to a DecisionTree of Gaussian factor graphs.
GaussianFactorGraphTree asGaussianFactorGraphTree() const;
//// Get the pruner functor from pruned discrete probabilities.
std::function<GaussianConditional::shared_ptr(
const Assignment<Key> &, const GaussianConditional::shared_ptr &)>
prunerFunc(const DecisionTreeFactor &prunedProbabilities);
/// Check whether `given` has values for all frontal keys. /// Check whether `given` has values for all frontal keys.
bool allFrontalsGiven(const VectorValues &given) const; bool allFrontalsGiven(const VectorValues &given) const;

2
gtsam/hybrid/tests/testHybridConditional.cpp
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@ -39,8 +39,6 @@ TEST(HybridConditional, Invariants) {
const DiscreteValues d{{M(0), 1}}; const DiscreteValues d{{M(0), 1}};
const HybridValues values{c, d}; const HybridValues values{c, d};
GTSAM_PRINT(bn);
// Check invariants for p(z|x,m) // Check invariants for p(z|x,m)
auto hc0 = bn.at(0); auto hc0 = bn.at(0);
CHECK(hc0->isHybrid()); CHECK(hc0->isHybrid());