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Drastically simplified solve

release/4.3a0
Frank Dellaert 2013-12-10 05:32:13 +00:00
parent f2da19e4de
commit 4815f9cf5b
1 changed files with 6 additions and 17 deletions
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23
gtsam/linear/KalmanFilter.cpp
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@ -38,26 +38,15 @@ namespace gtsam {
static KalmanFilter::State solve(const GaussianFactorGraph& factorGraph, static KalmanFilter::State solve(const GaussianFactorGraph& factorGraph,
const GaussianFactorGraph::Eliminate& function) { const GaussianFactorGraph::Eliminate& function) {
// We will eliminate the keys in increasing order, except the last key
Ordering ordering1(factorGraph.keys());
Key lastKey = ordering1.back();
ordering1.pop_back();
// Eliminate the graph using the provided Eliminate function // Eliminate the graph using the provided Eliminate function
GaussianConditional::shared_ptr conditional; Ordering ordering(factorGraph.keys());
GaussianFactor::shared_ptr factor; GaussianBayesNet::shared_ptr bayesNet = //
boost::tie(conditional, factor) = function(factorGraph, ordering1); factorGraph.eliminateSequential(ordering, function);
// As this is a filter, all we need is the posterior P(x_t). // As this is a filter, all we need is the posterior P(x_t).
GaussianFactorGraph graphOfRemainingFactor; // This is the last GaussianConditional in the resulting BayesNet
graphOfRemainingFactor += factor; GaussianConditional::shared_ptr posterior = *(--bayesNet->end());
return boost::make_shared<GaussianDensity>(*posterior);
// Eliminate it to be upper-triangular.
Ordering ordering2;
ordering2 += lastKey;
boost::tie(conditional, factor) = function(graphOfRemainingFactor, ordering2);
return boost::make_shared<GaussianDensity>(*conditional);
} }
/* ************************************************************************* */ /* ************************************************************************* */