102 lines
2.7 KiB
C++
102 lines
2.7 KiB
C++
/* ----------------------------------------------------------------------------
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* GTSAM Copyright 2010, Georgia Tech Research Corporation,
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* Atlanta, Georgia 30332-0415
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* All Rights Reserved
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* Authors: Frank Dellaert, et al. (see THANKS for the full author list)
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* See LICENSE for the license information
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* -------------------------------------------------------------------------- */
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/**
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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 <boost/shared_ptr.hpp>
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#include <gtsam/base/types.h>
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#include <gtsam/linear/GaussianConditional.h>
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#include <gtsam/inference/BayesNet.h>
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namespace gtsam {
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/** A Bayes net made from linear-Gaussian densities */
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typedef BayesNet<GaussianConditional> GaussianBayesNet;
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/** Create a scalar Gaussian */
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GaussianBayesNet scalarGaussian(Index 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 simpleGaussian(Index key, const Vector& mu, double sigma=1.0);
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/**
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* Add a conditional node with one parent
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* |Rx+Sy-d|
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*/
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void push_front(GaussianBayesNet& bn, Index key, Vector d, Matrix R,
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Index name1, Matrix S, Vector sigmas);
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/**
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* Add a conditional node with two parents
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* |Rx+Sy+Tz-d|
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*/
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void push_front(GaussianBayesNet& bn, Index key, Vector d, Matrix R,
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Index name1, Matrix S, Index name2, Matrix T, Vector sigmas);
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/**
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* Allocate a VectorValues for the variables in a BayesNet
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*/
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boost::shared_ptr<VectorValues> allocateVectorValues(const GaussianBayesNet& bn);
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/**
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* optimize, i.e. return x = inv(R)*d
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*/
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VectorValues optimize(const GaussianBayesNet&);
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/**
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* shared pointer version
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*/
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boost::shared_ptr<VectorValues> optimize_(const GaussianBayesNet& bn);
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/*
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* Backsubstitute
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* (R*x)./sigmas = y by solving x=inv(R)*(y.*sigmas)
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*/
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VectorValues backSubstitute(const GaussianBayesNet& bn, const VectorValues& y);
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/*
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* Backsubstitute in place, y is replaced with solution
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*/
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void backSubstituteInPlace(const GaussianBayesNet& bn, VectorValues& y);
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/*
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* Transpose Backsubstitute
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* gy=inv(L)*gx by solving L*gy=gx.
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* gy=inv(R'*inv(Sigma))*gx
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* gz'*R'=gx', gy = gz.*sigmas
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*/
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VectorValues backSubstituteTranspose(const GaussianBayesNet& bn, const VectorValues& gx);
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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 GaussianBayesNet&);
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/**
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* Return RHS d as a VectorValues
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* Such that backSubstitute(bn,d) = optimize(bn)
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*/
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VectorValues rhs(const GaussianBayesNet&);
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} /// namespace gtsam
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