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								/* ----------------------------------------------------------------------------
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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    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  Duy-Nguyen Ta
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								 * @author  Ivan Dario Jimenez
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								 */
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								#pragma once
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								#include <gtsam/linear/JacobianFactor.h>
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								#include <gtsam/linear/VectorValues.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 a linear inequality constraint Ax-b <= 0,
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								 * inheriting JacobianFactor 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 std::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 */
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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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								  /** Conversion from JacobianFactor */
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								  explicit LinearInequality(const JacobianFactor& jf, Key dualKey) :
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								      Base(jf), dualKey_(dualKey), active_(true) {
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								    if (!jf.isConstrained()) {
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								      throw std::runtime_error(
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								          "Cannot convert an unconstrained JacobianFactor to LinearInequality");
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								    }
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								    if (jf.get_model()->dim() != 1) {
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								      throw std::runtime_error("Only support single-valued inequality factor!");
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								    }
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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(),
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								          noiseModel::Constrained::All(1)), dualKey_(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,
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								      double b, Key dualKey) :
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								      Base(i1, A1, i2, A2, (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 ternary factor */
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								  LinearInequality(Key i1, const RowVector& A1, Key i2, const RowVector& A2,
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								      Key i3, 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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								   *         In this inequality factor, each matrix must have only one row!! */
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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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								  ~LinearInequality() override {
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								  }
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								  /** equals */
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								  bool equals(const GaussianFactor& lf, double tol = 1e-9) const override {
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								    return Base::equals(lf, tol);
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								  }
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								  /** print */
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								  void print(const std::string& s = "", const KeyFormatter& formatter =
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								      DefaultKeyFormatter) const override {
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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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								  GaussianFactor::shared_ptr clone() const override {
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								    return std::static_pointer_cast < GaussianFactor
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								        > (std::make_shared < LinearInequality > (*this));
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								  }
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								  /// dual key
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								  Key dualKey() const {
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								    return dualKey_;
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								  }
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								  /// return true if this constraint is active
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								  bool active() const {
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								    return active_;
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								  }
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											2014-12-13 01:01:16 +08:00
										 
									 
								 
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								  /// Make this inequality constraint active
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								  void activate() {
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								    active_ = true;
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								  }
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											2014-12-13 01:01:16 +08:00
										 
									 
								 
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								  /// Make this inequality constraint inactive
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								  void inactivate() {
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								    active_ = false;
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								  }
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											2014-12-13 01:01:16 +08:00
										 
									 
								 
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											2014-12-09 19:13:57 +08:00
										 
									 
								 
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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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											2020-07-26 15:57:54 +08:00
										 
									 
								 
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								  double error(const VectorValues& c) const override {
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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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											2014-12-13 01:01:16 +08:00
										 
									 
								 
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								    return aTp;
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								  }
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											2016-06-14 10:58:36 +08:00
										 
									 
								 
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								};
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								// \ LinearInequality
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											2014-12-22 05:02:06 +08:00
										 
									 
								 
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								/// traits
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								template<> struct traits<LinearInequality> : public Testable<LinearInequality> {
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								};
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											2014-12-22 05:02:06 +08:00
										 
									 
								 
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								} // \ namespace gtsam
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