newton_matrix_callbacks.hpp

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// Copyright (c) Sleipnir contributors
 
#pragma once
 
#include <functional>
 
#include <Eigen/Core>
#include <Eigen/SparseCore>
 
namespace slp {
 
/// Matrix callbacks for the Newton's method solver.
///
/// @tparam Scalar Scalar type.
template <typename Scalar>
struct NewtonMatrixCallbacks {
  /// Type alias for dense vector.
  using DenseVector = Eigen::Vector<Scalar, Eigen::Dynamic>;
  /// Type alias for sparse matrix.
  using SparseMatrix = Eigen::SparseMatrix<Scalar>;
  /// Type alias for sparse vector.
  using SparseVector = Eigen::SparseVector<Scalar>;
 
  /// Cost function value f(x) getter.
  ///
  /// <table>
  ///   <tr>
  ///     <th>Variable</th>
  ///     <th>Rows</th>
  ///     <th>Columns</th>
  ///   </tr>
  ///   <tr>
  ///     <td>x</td>
  ///     <td>num_decision_variables</td>
  ///     <td>1</td>
  ///   </tr>
  ///   <tr>
  ///     <td>f(x)</td>
  ///     <td>1</td>
  ///     <td>1</td>
  ///   </tr>
  /// </table>
  std::function<Scalar(const DenseVector& x)> f;
 
  /// Cost function gradient ∇f(x) getter.
  ///
  /// <table>
  ///   <tr>
  ///     <th>Variable</th>
  ///     <th>Rows</th>
  ///     <th>Columns</th>
  ///   </tr>
  ///   <tr>
  ///     <td>x</td>
  ///     <td>num_decision_variables</td>
  ///     <td>1</td>
  ///   </tr>
  ///   <tr>
  ///     <td>∇f(x)</td>
  ///     <td>num_decision_variables</td>
  ///     <td>1</td>
  ///   </tr>
  /// </table>
  std::function<SparseVector(const DenseVector& x)> g;
 
  /// Lagrangian Hessian ∇ₓₓ²L(x) getter.
  ///
  /// L(xₖ) = f(xₖ)
  ///
  /// <table>
  ///   <tr>
  ///     <th>Variable</th>
  ///     <th>Rows</th>
  ///     <th>Columns</th>
  ///   </tr>
  ///   <tr>
  ///     <td>x</td>
  ///     <td>num_decision_variables</td>
  ///     <td>1</td>
  ///   </tr>
  ///   <tr>
  ///     <td>∇ₓₓ²L(x)</td>
  ///     <td>num_decision_variables</td>
  ///     <td>num_decision_variables</td>
  ///   </tr>
  /// </table>
  std::function<SparseMatrix(const DenseVector& x)> H;
};
 
}  // namespace slp