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// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2017 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.
//
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// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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// Author: sameeragarwal@google.com (Sameer Agarwal)
#ifndef CERES_INTERNAL_SUBSET_PRECONDITIONER_H_
#define CERES_INTERNAL_SUBSET_PRECONDITIONER_H_
#include <memory>
#include "ceres/internal/port.h"
#include "ceres/preconditioner.h"
namespace ceres {
namespace internal {
class BlockSparseMatrix;
class SparseCholesky;
class InnerProductComputer;
// Subset preconditioning, uses a subset of the rows of the Jacobian
// to construct a preconditioner for the normal equations.
//
// To keep the interface simple, we assume that the matrix A has
// already been re-ordered that the user wishes to some subset of the
// bottom row blocks of the matrix as the preconditioner. This is
// controlled by
// Preconditioner::Options::subset_preconditioner_start_row_block.
//
// When using the subset preconditioner, all row blocks starting
// from this row block are used to construct the preconditioner.
//
// More precisely the matrix A is horizontally partitioned as
//
// A = [P]
// [Q]
//
// where P has subset_preconditioner_start_row_block row blocks,
// and the preconditioner is the inverse of the matrix Q'Q.
//
// Obviously, the smaller this number, the more accurate and
// computationally expensive this preconditioner will be.
//
// See the tests for example usage.
class CERES_EXPORT_INTERNAL SubsetPreconditioner
: public BlockSparseMatrixPreconditioner {
public:
SubsetPreconditioner(const Preconditioner::Options& options,
const BlockSparseMatrix& A);
virtual ~SubsetPreconditioner();
// Preconditioner interface
void RightMultiply(const double* x, double* y) const final;
int num_rows() const final { return num_cols_; }
int num_cols() const final { return num_cols_; }
private:
bool UpdateImpl(const BlockSparseMatrix& A, const double* D) final;
const Preconditioner::Options options_;
const int num_cols_;
std::unique_ptr<SparseCholesky> sparse_cholesky_;
std::unique_ptr<InnerProductComputer> inner_product_computer_;
};
} // namespace internal
} // namespace ceres
#endif // CERES_INTERNAL_SUBSET_PRECONDITIONER_H_