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// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2023 Google Inc. All rights reserved.
// http://ceres-solver.org/
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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