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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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// modification, are permitted provided that the following conditions are met:
//
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// Author: sameeragarwal@google.com (Sameer Agarwal)
//
// A solver for sparse linear least squares problem based on solving
// the normal equations via a sparse cholesky factorization.
#ifndef CERES_INTERNAL_DYNAMIC_SPARSE_NORMAL_CHOLESKY_SOLVER_H_
#define CERES_INTERNAL_DYNAMIC_SPARSE_NORMAL_CHOLESKY_SOLVER_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/export.h"
#include "ceres/linear_solver.h"
namespace ceres::internal {
class CompressedRowSparseMatrix;
// A variant of SparseNormalCholeskySolver in the case where matrix
// sparsity is not constant across calls to Solve. This means that
// there is no benefit to symbolically factorizing the matrix and
// caching this factorization.
//
// TODO(alex): Add support for Accelerate sparse solvers:
// https://github.com/ceres-solver/ceres-solver/issues/397
class CERES_NO_EXPORT DynamicSparseNormalCholeskySolver
: public CompressedRowSparseMatrixSolver {
public:
explicit DynamicSparseNormalCholeskySolver(LinearSolver::Options options);
private:
LinearSolver::Summary SolveImpl(CompressedRowSparseMatrix* A,
const double* b,
const LinearSolver::PerSolveOptions& options,
double* x) final;
LinearSolver::Summary SolveImplUsingSuiteSparse(CompressedRowSparseMatrix* A,
double* rhs_and_solution);
LinearSolver::Summary SolveImplUsingEigen(CompressedRowSparseMatrix* A,
double* rhs_and_solution);
const LinearSolver::Options options_;
};
} // namespace ceres::internal
#endif // CERES_INTERNAL_DYNAMIC_SPARSE_NORMAL_CHOLESKY_SOLVER_H_