49 lines
1.1 KiB
C++
49 lines
1.1 KiB
C++
/**
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* @file GaussianBayesNet.h
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* @brief Chordal Bayes Net, the result of eliminating a factor graph
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* @brief GaussianBayesNet
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* @author Frank Dellaert
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*/
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// \callgraph
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#pragma once
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#include <list>
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#include "ConditionalGaussian.h"
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#include "BayesNet.h"
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namespace gtsam {
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/** Chordal Bayes Net, the result of eliminating a factor graph */
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class GaussianBayesNet : public BayesNet<ConditionalGaussian>
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{
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public:
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typedef boost::shared_ptr<GaussianBayesNet> shared_ptr;
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/** Construct an empty net */
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GaussianBayesNet() {}
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/** Create a scalar Gaussian */
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GaussianBayesNet(const std::string& key, double mu=0.0, double sigma=1.0);
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/** Create a simple Gaussian on a single multivariate variable */
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GaussianBayesNet(const std::string& key, const Vector& mu, double sigma=1.0);
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/** Destructor */
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virtual ~GaussianBayesNet() {}
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/**
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* optimize, i.e. return x = inv(R)*d
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*/
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boost::shared_ptr<VectorConfig> optimize() const;
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/**
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* Return (dense) upper-triangular matrix representation
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*/
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std::pair<Matrix,Vector> matrix() const;
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};
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} /// namespace gtsam
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