// Copyright (c) 2018, ETH Zurich and UNC Chapel Hill.
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// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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// Author: Johannes L. Schoenberger (jsch at inf.ethz.ch)

#include "optim/least_absolute_deviations.h"

#include <Eigen/SparseCholesky>

namespace colmap {
namespace {

Eigen::VectorXd Shrinkage(const Eigen::VectorXd& a, const double kappa) {
  const Eigen::VectorXd a_plus_kappa = a.array() + kappa;
  const Eigen::VectorXd a_minus_kappa = a.array() - kappa;
  return a_plus_kappa.cwiseMin(0) + a_minus_kappa.cwiseMax(0);
}

}  // namespace

bool SolveLeastAbsoluteDeviations(const LeastAbsoluteDeviationsOptions& options,
                                  const Eigen::SparseMatrix<double>& A,
                                  const Eigen::VectorXd& b,
                                  Eigen::VectorXd* x) {
  CHECK_NOTNULL(x);
  CHECK_GT(options.rho, 0);
  CHECK_GT(options.alpha, 0);
  CHECK_GT(options.max_num_iterations, 0);
  CHECK_GE(options.absolute_tolerance, 0);
  CHECK_GE(options.relative_tolerance, 0);

  Eigen::SimplicialLLT<Eigen::SparseMatrix<double>> linear_solver;
  linear_solver.compute(A.transpose() * A);

  Eigen::VectorXd z = Eigen::VectorXd::Zero(A.rows());
  Eigen::VectorXd z_old(A.rows());
  Eigen::VectorXd u = Eigen::VectorXd::Zero(A.rows());

  Eigen::VectorXd Ax(A.rows());
  Eigen::VectorXd Ax_hat(A.rows());

  const double b_norm = b.norm();
  const double eps_pri_threshold =
      std::sqrt(A.rows()) * options.absolute_tolerance;
  const double eps_dual_threshold =
      std::sqrt(A.cols()) * options.absolute_tolerance;

  for (int i = 0; i < options.max_num_iterations; ++i) {
    *x = linear_solver.solve(A.transpose() * (b + z - u));
    if (linear_solver.info() != Eigen::Success) {
      return false;
    }

    Ax = A * *x;
    Ax_hat = options.alpha * Ax + (1 - options.alpha) * (z + b);

    z_old = z;
    z = Shrinkage(Ax_hat - b + u, 1 / options.rho);

    u += Ax_hat - z - b;

    const double r_norm = (Ax - z - b).norm();
    const double s_norm = (-options.rho * A.transpose() * (z - z_old)).norm();
    const double eps_pri =
        eps_pri_threshold + options.relative_tolerance *
                                std::max(b_norm, std::max(Ax.norm(), z.norm()));
    const double eps_dual =
        eps_dual_threshold +
        options.relative_tolerance * (options.rho * A.transpose() * u).norm();

    if (r_norm < eps_pri && s_norm < eps_dual) {
      break;
    }
  }

  return true;
}

}  // namespace colmap
