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// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2013 Google Inc. All rights reserved.
// http://code.google.com/p/ceres-solver/
//
// 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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// POSSIBILITY OF SUCH DAMAGE.
//
// Author: sameeragarwal@google.com (Sameer Agarwal)
#include "ceres/schur_jacobi_preconditioner.h"
#include <utility>
#include <vector>
#include "Eigen/Dense"
#include "ceres/block_random_access_sparse_matrix.h"
#include "ceres/block_sparse_matrix.h"
#include "ceres/collections_port.h"
#include "ceres/detect_structure.h"
#include "ceres/internal/scoped_ptr.h"
#include "ceres/linear_solver.h"
#include "ceres/schur_eliminator.h"
#include "glog/logging.h"
namespace ceres {
namespace internal {
SchurJacobiPreconditioner::SchurJacobiPreconditioner(
const CompressedRowBlockStructure& bs,
const Preconditioner::Options& options)
: options_(options) {
CHECK_GT(options_.elimination_groups.size(), 1);
CHECK_GT(options_.elimination_groups[0], 0);
const int num_blocks = bs.cols.size() - options_.elimination_groups[0];
CHECK_GT(num_blocks, 0)
<< "Jacobian should have atleast 1 f_block for "
<< "SCHUR_JACOBI preconditioner.";
block_size_.resize(num_blocks);
set<pair<int, int> > block_pairs;
int num_block_diagonal_entries = 0;
for (int i = 0; i < num_blocks; ++i) {
block_size_[i] = bs.cols[i + options_.elimination_groups[0]].size;
block_pairs.insert(make_pair(i, i));
num_block_diagonal_entries += block_size_[i] * block_size_[i];
}
m_.reset(new BlockRandomAccessSparseMatrix(block_size_, block_pairs));
InitEliminator(bs);
}
SchurJacobiPreconditioner::~SchurJacobiPreconditioner() {
}
// Initialize the SchurEliminator.
void SchurJacobiPreconditioner::InitEliminator(
const CompressedRowBlockStructure& bs) {
LinearSolver::Options eliminator_options;
eliminator_options.elimination_groups = options_.elimination_groups;
eliminator_options.num_threads = options_.num_threads;
DetectStructure(bs, options_.elimination_groups[0],
&eliminator_options.row_block_size,
&eliminator_options.e_block_size,
&eliminator_options.f_block_size);
eliminator_.reset(SchurEliminatorBase::Create(eliminator_options));
eliminator_->Init(options_.elimination_groups[0], &bs);
}
// Update the values of the preconditioner matrix and factorize it.
bool SchurJacobiPreconditioner::Update(const BlockSparseMatrix& A,
const double* D) {
const int num_rows = m_->num_rows();
CHECK_GT(num_rows, 0);
// We need a dummy rhs vector and a dummy b vector since the Schur
// eliminator combines the computation of the reduced camera matrix
// with the computation of the right hand side of that linear
// system.
//
// TODO(sameeragarwal): Perhaps its worth refactoring the
// SchurEliminator::Eliminate function to allow NULL for the rhs. As
// of now it does not seem to be worth the effort.
Vector rhs = Vector::Zero(m_->num_rows());
Vector b = Vector::Zero(A.num_rows());
// Compute a subset of the entries of the Schur complement.
eliminator_->Eliminate(&A, b.data(), D, m_.get(), rhs.data());
return true;
}
void SchurJacobiPreconditioner::RightMultiply(const double* x,
double* y) const {
CHECK_NOTNULL(x);
CHECK_NOTNULL(y);
const double* lhs_values =
down_cast<BlockRandomAccessSparseMatrix*>(m_.get())->matrix()->values();
// This loop can be easily multi-threaded with OpenMP if need be.
for (int i = 0; i < block_size_.size(); ++i) {
const int block_size = block_size_[i];
ConstMatrixRef block(lhs_values, block_size, block_size);
VectorRef(y, block_size) =
block
.selfadjointView<Eigen::Upper>()
.ldlt()
.solve(ConstVectorRef(x, block_size));
x += block_size;
y += block_size;
lhs_values += block_size * block_size;
}
}
int SchurJacobiPreconditioner::num_rows() const {
return m_->num_rows();
}
} // namespace internal
} // namespace ceres