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factor errors in negative log space

release/4.3a0
Varun Agrawal 2024-09-23 15:08:12 -04:00
parent 2c7e5eb656
commit 5da7588b66
1 changed files with 7 additions and 7 deletions
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14
gtsam/hybrid/HybridGaussianFactorGraph.cpp
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@ -233,8 +233,8 @@ continuousElimination(const HybridGaussianFactorGraph &factors,
/* ************************************************************************ */
/**
* @brief Exponentiate log-values, not necessarily normalized, normalize, and
* return as AlgebraicDecisionTree<Key>.
* @brief Exponentiate (not necessarily normalized) log-values, normalize, and
* then return as AlgebraicDecisionTree<Key>.
*
* @param logValues DecisionTree of (unnormalized) log values.
* @return AlgebraicDecisionTree<Key>
@ -242,9 +242,9 @@ continuousElimination(const HybridGaussianFactorGraph &factors,
static AlgebraicDecisionTree<Key> probabilitiesFromLogValues(
const AlgebraicDecisionTree<Key> &logValues) {
// Perform normalization
double max_log = logValues.max();
double min_log = logValues.min();
AlgebraicDecisionTree<Key> probabilities = DecisionTree<Key, double>(
logValues, [&max_log](const double x) { return exp(x - max_log); });
logValues, [&min_log](const double x) { return exp(-(x - min_log)); });
probabilities = probabilities.normalize(probabilities.sum());
return probabilities;
@ -265,7 +265,7 @@ discreteElimination(const HybridGaussianFactorGraph &factors,
auto logProbability =
[&](const GaussianFactor::shared_ptr &factor) -> double {
if (!factor) return 0.0;
return -factor->error(VectorValues());
return factor->error(VectorValues());
};
AlgebraicDecisionTree<Key> logProbabilities =
DecisionTree<Key, double>(gmf->factors(), logProbability);
@ -327,11 +327,11 @@ static std::shared_ptr<Factor> createDiscreteFactor(
// If the factor is not null, it has no keys, just contains the residual.
if (!factor) return 1.0; // TODO(dellaert): not loving this.
// Logspace version of:
// Negative logspace version of:
// exp(-factor->error(kEmpty)) / conditional->normalizationConstant();
// negLogConstant gives `-log(k)`
// which is `-log(k) = log(1/k) = log(\sqrt{|2πΣ|})`.
return -factor->error(kEmpty) + conditional->negLogConstant();
return factor->error(kEmpty) - conditional->negLogConstant();
};
AlgebraicDecisionTree<Key> logProbabilities(