internal/ceres/power_series_expansion_preconditioner.cc

// Ceres Solver - A fast non-linear least squares minimizer
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// Author: markshachkov@gmail.com (Mark Shachkov)

#include "ceres/power_series_expansion_preconditioner.h"

namespace ceres::internal {

PowerSeriesExpansionPreconditioner::PowerSeriesExpansionPreconditioner(
    const ImplicitSchurComplement* isc,
    const int max_num_spse_iterations,
    const double spse_tolerance)
    : isc_(isc),
      max_num_spse_iterations_(max_num_spse_iterations),
      spse_tolerance_(spse_tolerance) {}

PowerSeriesExpansionPreconditioner::~PowerSeriesExpansionPreconditioner() =
    default;

bool PowerSeriesExpansionPreconditioner::Update(const LinearOperator& /*A*/,
                                                const double* /*D*/) {
  return true;
}

void PowerSeriesExpansionPreconditioner::RightMultiplyAndAccumulate(
    const double* x, double* y) const {
  VectorRef yref(y, num_rows());
  Vector series_term(num_rows());
  Vector previous_series_term(num_rows());
  yref.setZero();
  isc_->block_diagonal_FtF_inverse()->RightMultiplyAndAccumulate(x, y);
  previous_series_term = yref;

  const double norm_threshold = spse_tolerance_ * yref.norm();

  for (int i = 1;; i++) {
    series_term.setZero();
    isc_->InversePowerSeriesOperatorRightMultiplyAccumulate(
        previous_series_term.data(), series_term.data());
    yref += series_term;
    if (i >= max_num_spse_iterations_ || series_term.norm() < norm_threshold) {
      break;
    }
    std::swap(previous_series_term, series_term);
  }
}

int PowerSeriesExpansionPreconditioner::num_rows() const {
  return isc_->num_rows();
}

}  // namespace ceres::internal