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// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2023 Google Inc. All rights reserved.
// http://ceres-solver.org/
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are met:
//
// * Redistributions of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
// * Redistributions in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
// * Neither the name of Google Inc. nor the names of its contributors may be
// used to endorse or promote products derived from this software without
// specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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//
// Author: sameeragarwal@google.com (Sameer Agarwal)
#ifndef CERES_INTERNAL_ITERATIVE_REFINER_H_
#define CERES_INTERNAL_ITERATIVE_REFINER_H_
// This include must come before any #ifndef check on Ceres compile options.
// clang-format off
#include "ceres/internal/config.h"
// clang-format on
#include "ceres/internal/eigen.h"
#include "ceres/internal/export.h"
namespace ceres::internal {
class DenseCholesky;
class SparseCholesky;
class SparseMatrix;
// Iterative refinement
// (https://en.wikipedia.org/wiki/Iterative_refinement) is the process
// of improving the solution to a linear system, by using the
// following iteration.
//
// r_i = b - Ax_i
// Ad_i = r_i
// x_{i+1} = x_i + d_i
//
// IterativeRefiner implements this process for Symmetric Positive
// Definite linear systems.
//
// The above iterative loop is run until max_num_iterations is reached.
class CERES_NO_EXPORT SparseIterativeRefiner {
public:
// max_num_iterations is the number of refinement iterations to
// perform.
explicit SparseIterativeRefiner(int max_num_iterations);
// Needed for mocking.
virtual ~SparseIterativeRefiner();
// Given an initial estimate of the solution of lhs * x = rhs, use
// max_num_iterations rounds of iterative refinement to improve it.
//
// cholesky is assumed to contain an already computed factorization (or
// an approximation thereof) of lhs.
//
// solution is expected to contain a approximation to the solution
// to lhs * x = rhs. It can be zero.
//
// This method is virtual to facilitate mocking.
virtual void Refine(const SparseMatrix& lhs,
const double* rhs,
SparseCholesky* cholesky,
double* solution);
private:
void Allocate(int num_cols);
int max_num_iterations_;
Vector residual_;
Vector correction_;
Vector lhs_x_solution_;
};
class CERES_NO_EXPORT DenseIterativeRefiner {
public:
// max_num_iterations is the number of refinement iterations to
// perform.
explicit DenseIterativeRefiner(int max_num_iterations);
// Needed for mocking.
virtual ~DenseIterativeRefiner();
// Given an initial estimate of the solution of lhs * x = rhs, use
// max_num_iterations rounds of iterative refinement to improve it.
//
// cholesky is assumed to contain an already computed factorization (or
// an approximation thereof) of lhs.
//
// solution is expected to contain a approximation to the solution
// to lhs * x = rhs. It can be zero.
//
// This method is virtual to facilitate mocking.
virtual void Refine(int num_cols,
const double* lhs,
const double* rhs,
DenseCholesky* cholesky,
double* solution);
private:
void Allocate(int num_cols);
int max_num_iterations_;
Vector residual_;
Vector correction_;
};
} // namespace ceres::internal
#endif // CERES_INTERNAL_ITERATIVE_REFINER_H_