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// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2015 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
// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
// POSSIBILITY OF SUCH DAMAGE.
//
// Author: sameeragarwal@google.com (Sameer Agarwal)
#ifndef CERES_INTERNAL_PRECONDITIONER_H_
#define CERES_INTERNAL_PRECONDITIONER_H_
#include <vector>
#include "ceres/casts.h"
#include "ceres/compressed_row_sparse_matrix.h"
#include "ceres/context_impl.h"
#include "ceres/linear_operator.h"
#include "ceres/sparse_matrix.h"
#include "ceres/types.h"
namespace ceres {
namespace internal {
class BlockSparseMatrix;
class SparseMatrix;
class Preconditioner : public LinearOperator {
public:
struct Options {
PreconditionerType type = JACOBI;
VisibilityClusteringType visibility_clustering_type = CANONICAL_VIEWS;
SparseLinearAlgebraLibraryType sparse_linear_algebra_library_type = SUITE_SPARSE;
// When using the subset preconditioner, all row blocks starting
// from this row block are used to construct the preconditioner.
//
// i.e., the Jacobian 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.
int subset_preconditioner_start_row_block = -1;
// See solver.h for information about these flags.
bool use_postordering = false;
// If possible, how many threads the preconditioner can use.
int num_threads = 1;
// Hints about the order in which the parameter blocks should be
// eliminated by the linear solver.
//
// For example if elimination_groups is a vector of size k, then
// the linear solver is informed that it should eliminate the
// parameter blocks 0 ... elimination_groups[0] - 1 first, and
// then elimination_groups[0] ... elimination_groups[1] - 1 and so
// on. Within each elimination group, the linear solver is free to
// choose how the parameter blocks are ordered. Different linear
// solvers have differing requirements on elimination_groups.
//
// The most common use is for Schur type solvers, where there
// should be at least two elimination groups and the first
// elimination group must form an independent set in the normal
// equations. The first elimination group corresponds to the
// num_eliminate_blocks in the Schur type solvers.
std::vector<int> elimination_groups;
// If the block sizes in a BlockSparseMatrix are fixed, then in
// some cases the Schur complement based solvers can detect and
// specialize on them.
//
// It is expected that these parameters are set programmatically
// rather than manually.
//
// Please see schur_complement_solver.h and schur_eliminator.h for
// more details.
int row_block_size = Eigen::Dynamic;
int e_block_size = Eigen::Dynamic;
int f_block_size = Eigen::Dynamic;
ContextImpl* context = nullptr;
};
// If the optimization problem is such that there are no remaining
// e-blocks, ITERATIVE_SCHUR with a Schur type preconditioner cannot
// be used. This function returns JACOBI if a preconditioner for
// ITERATIVE_SCHUR is used. The input preconditioner_type is
// returned otherwise.
static PreconditionerType PreconditionerForZeroEBlocks(
PreconditionerType preconditioner_type);
virtual ~Preconditioner();
// Update the numerical value of the preconditioner for the linear
// system:
//
// | A | x = |b|
// |diag(D)| |0|
//
// for some vector b. It is important that the matrix A have the
// same block structure as the one used to construct this object.
//
// D can be NULL, in which case its interpreted as a diagonal matrix
// of size zero.
virtual bool Update(const LinearOperator& A, const double* D) = 0;
// LinearOperator interface. Since the operator is symmetric,
// LeftMultiply and num_cols are just calls to RightMultiply and
// num_rows respectively. Update() must be called before
// RightMultiply can be called.
void RightMultiply(const double* x, double* y) const override = 0;
void LeftMultiply(const double* x, double* y) const override {
return RightMultiply(x, y);
}
int num_rows() const override = 0;
int num_cols() const override {
return num_rows();
}
};
// This templated subclass of Preconditioner serves as a base class for
// other preconditioners that depend on the particular matrix layout of
// the underlying linear operator.
template <typename MatrixType>
class TypedPreconditioner : public Preconditioner {
public:
virtual ~TypedPreconditioner() {}
bool Update(const LinearOperator& A, const double* D) final {
return UpdateImpl(*down_cast<const MatrixType*>(&A), D);
}
private:
virtual bool UpdateImpl(const MatrixType& A, const double* D) = 0;
};
// Preconditioners that depend on access to the low level structure
// of a SparseMatrix.
typedef TypedPreconditioner<SparseMatrix> SparseMatrixPreconditioner; // NOLINT
typedef TypedPreconditioner<BlockSparseMatrix> BlockSparseMatrixPreconditioner; // NOLINT
typedef TypedPreconditioner<CompressedRowSparseMatrix> CompressedRowSparseMatrixPreconditioner; // NOLINT
// Wrap a SparseMatrix object as a preconditioner.
class SparseMatrixPreconditionerWrapper : public SparseMatrixPreconditioner {
public:
// Wrapper does NOT take ownership of the matrix pointer.
explicit SparseMatrixPreconditionerWrapper(const SparseMatrix* matrix);
virtual ~SparseMatrixPreconditionerWrapper();
// Preconditioner interface
virtual void RightMultiply(const double* x, double* y) const;
virtual int num_rows() const;
private:
virtual bool UpdateImpl(const SparseMatrix& A, const double* D);
const SparseMatrix* matrix_;
};
} // namespace internal
} // namespace ceres
#endif // CERES_INTERNAL_PRECONDITIONER_H_
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