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some cleanup

release/4.3a0
Varun Agrawal 2023-03-01 14:44:40 -05:00
parent c204524a3b
commit 8ba5da44a6
2 changed files with 5 additions and 6 deletions
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9
gtsam/hybrid/HybridGaussianFactorGraph.cpp
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@ -190,8 +190,7 @@ discreteElimination(const HybridGaussianFactorGraph &factors,
/* ************************************************************************ */ /* ************************************************************************ */
// If any GaussianFactorGraph in the decision tree contains a nullptr, convert // If any GaussianFactorGraph in the decision tree contains a nullptr, convert
// that leaf to an empty GaussianFactorGraph. Needed since the DecisionTree will // that leaf to an empty GaussianFactorGraph. Needed since the DecisionTree will
// otherwise create a GFG with a single (null) factor. // otherwise create a GFG with a single (null) factor, which doesn't register as null.
// TODO(dellaert): still a mystery to me why this is needed.
GaussianFactorGraphTree removeEmpty(const GaussianFactorGraphTree &sum) { GaussianFactorGraphTree removeEmpty(const GaussianFactorGraphTree &sum) {
auto emptyGaussian = [](const GaussianFactorGraph &graph) { auto emptyGaussian = [](const GaussianFactorGraph &graph) {
bool hasNull = bool hasNull =
@ -275,9 +274,9 @@ hybridElimination(const HybridGaussianFactorGraph &factors,
}; };
DecisionTree<Key, double> probabilities(eliminationResults, probability); DecisionTree<Key, double> probabilities(eliminationResults, probability);
return {std::make_shared<HybridConditional>(gaussianMixture), return {
std::make_shared<DecisionTreeFactor>(discreteSeparator, std::make_shared<HybridConditional>(gaussianMixture),
probabilities)}; std::make_shared<DecisionTreeFactor>(discreteSeparator, probabilities)};
} else { } else {
// Otherwise, we create a resulting GaussianMixtureFactor on the separator, // Otherwise, we create a resulting GaussianMixtureFactor on the separator,
// taking care to correct for conditional constant. // taking care to correct for conditional constant.

2
gtsam/linear/HessianFactor.h
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@ -131,7 +131,7 @@ namespace gtsam {
* term, and f the constant term. * term, and f the constant term.
* JacobianFactor error is \f[ 0.5* (Ax-b)' M (Ax-b) = 0.5*x'A'MAx - x'A'Mb + 0.5*b'Mb \f] * JacobianFactor error is \f[ 0.5* (Ax-b)' M (Ax-b) = 0.5*x'A'MAx - x'A'Mb + 0.5*b'Mb \f]
* HessianFactor error is \f[ 0.5*(x'Gx - 2x'g + f) = 0.5*x'Gx - x'*g + 0.5*f \f] * HessianFactor error is \f[ 0.5*(x'Gx - 2x'g + f) = 0.5*x'Gx - x'*g + 0.5*f \f]
* So, with \f$ A = [A1 A2] \f$ and \f$ G=A*'M*A = [A1';A2']*M*[A1 A2] \f$ we have * So, with \f$ A = [A1 A2] \f$ and \f$ G=A'*M*A = [A1';A2']*M*[A1 A2] \f$ we have
\code \code
n1*n1 G11 = A1'*M*A1 n1*n1 G11 = A1'*M*A1
n1*n2 G12 = A1'*M*A2 n1*n2 G12 = A1'*M*A2