| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188189190191192193194195196197198199200201202203204205206 | // 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)#include "ceres/implicit_schur_complement.h"#include <cstddef>#include <memory>#include "Eigen/Dense"#include "ceres/block_random_access_dense_matrix.h"#include "ceres/block_sparse_matrix.h"#include "ceres/casts.h"#include "ceres/context_impl.h"#include "ceres/internal/eigen.h"#include "ceres/linear_least_squares_problems.h"#include "ceres/linear_solver.h"#include "ceres/schur_eliminator.h"#include "ceres/triplet_sparse_matrix.h"#include "ceres/types.h"#include "glog/logging.h"#include "gtest/gtest.h"namespace ceres {namespace internal {using testing::AssertionResult;const double kEpsilon = 1e-14;class ImplicitSchurComplementTest : public ::testing::Test { protected :  void SetUp() final {    std::unique_ptr<LinearLeastSquaresProblem> problem(        CreateLinearLeastSquaresProblemFromId(2));    CHECK(problem != nullptr);    A_.reset(down_cast<BlockSparseMatrix*>(problem->A.release()));    b_.reset(problem->b.release());    D_.reset(problem->D.release());    num_cols_ = A_->num_cols();    num_rows_ = A_->num_rows();    num_eliminate_blocks_ = problem->num_eliminate_blocks;  }  void ReducedLinearSystemAndSolution(double* D,                                      Matrix* lhs,                                      Vector* rhs,                                      Vector* solution) {    const CompressedRowBlockStructure* bs = A_->block_structure();    const int num_col_blocks = bs->cols.size();    std::vector<int> blocks(num_col_blocks - num_eliminate_blocks_, 0);    for (int i = num_eliminate_blocks_; i < num_col_blocks; ++i) {      blocks[i - num_eliminate_blocks_] = bs->cols[i].size;    }    BlockRandomAccessDenseMatrix blhs(blocks);    const int num_schur_rows = blhs.num_rows();    LinearSolver::Options options;    options.elimination_groups.push_back(num_eliminate_blocks_);    options.type = DENSE_SCHUR;    ContextImpl context;    options.context = &context;    std::unique_ptr<SchurEliminatorBase> eliminator(        SchurEliminatorBase::Create(options));    CHECK(eliminator != nullptr);    const bool kFullRankETE = true;    eliminator->Init(num_eliminate_blocks_, kFullRankETE, bs);    lhs->resize(num_schur_rows, num_schur_rows);    rhs->resize(num_schur_rows);    eliminator->Eliminate(        BlockSparseMatrixData(*A_), b_.get(), D, &blhs, rhs->data());    MatrixRef lhs_ref(blhs.mutable_values(), num_schur_rows, num_schur_rows);    // lhs_ref is an upper triangular matrix. Construct a full version    // of lhs_ref in lhs by transposing lhs_ref, choosing the strictly    // lower triangular part of the matrix and adding it to lhs_ref.    *lhs = lhs_ref;    lhs->triangularView<Eigen::StrictlyLower>() =        lhs_ref.triangularView<Eigen::StrictlyUpper>().transpose();    solution->resize(num_cols_);    solution->setZero();    VectorRef schur_solution(solution->data() + num_cols_ - num_schur_rows,                             num_schur_rows);    schur_solution = lhs->selfadjointView<Eigen::Upper>().llt().solve(*rhs);    eliminator->BackSubstitute(BlockSparseMatrixData(*A_), b_.get(), D,                               schur_solution.data(), solution->data());  }  AssertionResult TestImplicitSchurComplement(double* D) {    Matrix lhs;    Vector rhs;    Vector reference_solution;    ReducedLinearSystemAndSolution(D, &lhs, &rhs, &reference_solution);    LinearSolver::Options options;    options.elimination_groups.push_back(num_eliminate_blocks_);    options.preconditioner_type = JACOBI;    ContextImpl context;    options.context = &context;    ImplicitSchurComplement isc(options);    isc.Init(*A_, D, b_.get());    int num_sc_cols = lhs.cols();    for (int i = 0; i < num_sc_cols; ++i) {      Vector x(num_sc_cols);      x.setZero();      x(i) = 1.0;      Vector y(num_sc_cols);      y = lhs * x;      Vector z(num_sc_cols);      isc.RightMultiply(x.data(), z.data());      // The i^th column of the implicit schur complement is the same as      // the explicit schur complement.      if ((y - z).norm() > kEpsilon) {        return testing::AssertionFailure()            << "Explicit and Implicit SchurComplements differ in "            << "column " << i << ". explicit: " << y.transpose()            << " implicit: " << z.transpose();      }    }    // Compare the rhs of the reduced linear system    if ((isc.rhs() - rhs).norm() > kEpsilon) {      return testing::AssertionFailure()            << "Explicit and Implicit SchurComplements differ in "            << "rhs. explicit: " << rhs.transpose()            << " implicit: " << isc.rhs().transpose();    }    // Reference solution to the f_block.    const Vector reference_f_sol =        lhs.selfadjointView<Eigen::Upper>().llt().solve(rhs);    // Backsubstituted solution from the implicit schur solver using the    // reference solution to the f_block.    Vector sol(num_cols_);    isc.BackSubstitute(reference_f_sol.data(), sol.data());    if ((sol - reference_solution).norm() > kEpsilon) {      return testing::AssertionFailure()          << "Explicit and Implicit SchurComplements solutions differ. "          << "explicit: " << reference_solution.transpose()          << " implicit: " << sol.transpose();    }    return testing::AssertionSuccess();  }  int num_rows_;  int num_cols_;  int num_eliminate_blocks_;  std::unique_ptr<BlockSparseMatrix> A_;  std::unique_ptr<double[]> b_;  std::unique_ptr<double[]> D_;};// Verify that the Schur Complement matrix implied by the// ImplicitSchurComplement class matches the one explicitly computed// by the SchurComplement solver.//// We do this with and without regularization to check that the// support for the LM diagonal is correct.TEST_F(ImplicitSchurComplementTest, SchurMatrixValuesTest) {  EXPECT_TRUE(TestImplicitSchurComplement(NULL));  EXPECT_TRUE(TestImplicitSchurComplement(D_.get()));}}  // namespace internal}  // namespace ceres
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