144 lines
4.2 KiB
C++
144 lines
4.2 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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* LinearInequality.h
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* @brief: LinearInequality derived from Base with constrained noise model
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* @date: Nov 27, 2014
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* @author: thduynguyen
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*/
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#pragma once
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#include <gtsam/linear/JacobianFactor.h>
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namespace gtsam {
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typedef Eigen::RowVectorXd RowVector;
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/**
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* This class defines Linear constraints by inherit Base
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* with the special Constrained noise model
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*/
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class LinearInequality: public JacobianFactor {
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public:
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typedef LinearInequality This; ///< Typedef to this class
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typedef JacobianFactor Base; ///< Typedef to base class
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typedef boost::shared_ptr<This> shared_ptr; ///< shared_ptr to this class
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private:
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Key dualKey_;
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bool active_;
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public:
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/** default constructor for I/O */
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LinearInequality() :
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Base(), active_(true) {
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}
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/** Conversion from HessianFactor (does Cholesky to obtain Jacobian matrix) */
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explicit LinearInequality(const HessianFactor& hf) {
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throw std::runtime_error(
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"Cannot convert HessianFactor to LinearInequality");
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}
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/** Construct unary factor */
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LinearInequality(Key i1, const RowVector& A1, double b, Key dualKey) :
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Base(i1, A1, (Vector(1) << b).finished(), noiseModel::Constrained::All(1)), dualKey_(
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dualKey), active_(true) {
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}
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/** Construct binary factor */
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LinearInequality(Key i1, const RowVector& A1, Key i2, const RowVector& A2, double b,
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Key dualKey) :
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Base(i1, A1, i2, A2, (Vector(1) << b).finished(), noiseModel::Constrained::All(1)), dualKey_(
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dualKey), active_(true) {
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}
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/** Construct ternary factor */
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LinearInequality(Key i1, const RowVector& A1, Key i2, const RowVector& A2, Key i3,
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const RowVector& A3, double b, Key dualKey) :
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Base(i1, A1, i2, A2, i3, A3, (Vector(1) << b).finished(),
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noiseModel::Constrained::All(1)), dualKey_(dualKey), active_(true) {
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}
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/** Construct an n-ary factor
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* @tparam TERMS A container whose value type is std::pair<Key, Matrix>, specifying the
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* collection of keys and matrices making up the factor. */
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template<typename TERMS>
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LinearInequality(const TERMS& terms, double b, Key dualKey) :
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Base(terms, (Vector(1) << b).finished(), noiseModel::Constrained::All(1)), dualKey_(
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dualKey), active_(true) {
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}
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/** Virtual destructor */
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virtual ~LinearInequality() {
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}
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/** equals */
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virtual bool equals(const GaussianFactor& lf, double tol = 1e-9) const {
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return Base::equals(lf, tol);
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}
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/** print */
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virtual void print(const std::string& s = "", const KeyFormatter& formatter =
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DefaultKeyFormatter) const {
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if (active())
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Base::print(s + " Active", formatter);
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else
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Base::print(s + " Inactive", formatter);
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}
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/** Clone this LinearInequality */
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virtual GaussianFactor::shared_ptr clone() const {
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return boost::static_pointer_cast<GaussianFactor>(
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boost::make_shared<LinearInequality>(*this));
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}
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/// dual key
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Key dualKey() const { return dualKey_; }
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/// return true if this constraint is active
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bool active() const { return active_; }
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/// Make this inequality constraint active
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void activate() { active_ = true; }
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/// Make this inequality constraint inactive
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void inactivate() { active_ = false; }
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/** Special error_vector for constraints (A*x-b) */
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Vector error_vector(const VectorValues& c) const {
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return unweighted_error(c);
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}
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/** Special error for single-valued inequality constraints. */
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virtual double error(const VectorValues& c) const {
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return error_vector(c)[0];
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}
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/** dot product of row s with the corresponding vector in p */
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double dotProductRow(const VectorValues& p) const {
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double aTp = 0.0;
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for (const_iterator xj = begin(); xj != end(); ++xj) {
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Vector pj = p.at(*xj);
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Vector aj = getA(xj).transpose();
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aTp += aj.dot(pj);
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}
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return aTp;
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}
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};
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// LinearInequality
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}// gtsam
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