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// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2023 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
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//
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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// POSSIBILITY OF SUCH DAMAGE.
//
// Author: sameeragarwal@google.com (Sameer Agarwal)
#include <memory>
#include "Eigen/Cholesky"
#include "ceres/casts.h"
#include "ceres/compressed_row_sparse_matrix.h"
#include "ceres/context_impl.h"
#include "ceres/internal/config.h"
#include "ceres/linear_least_squares_problems.h"
#include "ceres/linear_solver.h"
#include "ceres/triplet_sparse_matrix.h"
#include "ceres/types.h"
#include "glog/logging.h"
#include "gtest/gtest.h"
namespace ceres {
namespace internal {
// TODO(sameeragarwal): These tests needs to be re-written to be more
// thorough, they do not really test the dynamic nature of the
// sparsity.
class DynamicSparseNormalCholeskySolverTest : public ::testing::Test {
protected:
void SetUp() final {
std::unique_ptr<LinearLeastSquaresProblem> problem =
CreateLinearLeastSquaresProblemFromId(1);
A_ = CompressedRowSparseMatrix::FromTripletSparseMatrix(
*down_cast<TripletSparseMatrix*>(problem->A.get()));
b_ = std::move(problem->b);
D_ = std::move(problem->D);
}
void TestSolver(const LinearSolver::Options& options, double* D) {
Matrix dense_A;
A_->ToDenseMatrix(&dense_A);
Matrix lhs = dense_A.transpose() * dense_A;
if (D != nullptr) {
lhs += (ConstVectorRef(D, A_->num_cols()).array() *
ConstVectorRef(D, A_->num_cols()).array())
.matrix()
.asDiagonal();
}
Vector rhs(A_->num_cols());
rhs.setZero();
A_->LeftMultiplyAndAccumulate(b_.get(), rhs.data());
Vector expected_solution = lhs.llt().solve(rhs);
std::unique_ptr<LinearSolver> solver(LinearSolver::Create(options));
LinearSolver::PerSolveOptions per_solve_options;
per_solve_options.D = D;
Vector actual_solution(A_->num_cols());
LinearSolver::Summary summary;
summary = solver->Solve(
A_.get(), b_.get(), per_solve_options, actual_solution.data());
EXPECT_EQ(summary.termination_type, LinearSolverTerminationType::SUCCESS);
for (int i = 0; i < A_->num_cols(); ++i) {
EXPECT_NEAR(expected_solution(i), actual_solution(i), 1e-8)
<< "\nExpected: " << expected_solution.transpose()
<< "\nActual: " << actual_solution.transpose();
}
}
void TestSolver(
const SparseLinearAlgebraLibraryType sparse_linear_algebra_library_type,
const OrderingType ordering_type) {
LinearSolver::Options options;
options.type = SPARSE_NORMAL_CHOLESKY;
options.dynamic_sparsity = true;
options.sparse_linear_algebra_library_type =
sparse_linear_algebra_library_type;
options.ordering_type = ordering_type;
ContextImpl context;
options.context = &context;
TestSolver(options, nullptr);
TestSolver(options, D_.get());
}
std::unique_ptr<CompressedRowSparseMatrix> A_;
std::unique_ptr<double[]> b_;
std::unique_ptr<double[]> D_;
};
#ifndef CERES_NO_SUITESPARSE
TEST_F(DynamicSparseNormalCholeskySolverTest, SuiteSparseAMD) {
TestSolver(SUITE_SPARSE, OrderingType::AMD);
}
#ifndef CERES_NO_CHOLMOD_PARTITION
TEST_F(DynamicSparseNormalCholeskySolverTest, SuiteSparseNESDIS) {
TestSolver(SUITE_SPARSE, OrderingType::NESDIS);
}
#endif
#endif
#ifdef CERES_USE_EIGEN_SPARSE
TEST_F(DynamicSparseNormalCholeskySolverTest, EigenAMD) {
TestSolver(EIGEN_SPARSE, OrderingType::AMD);
}
#ifndef CERES_NO_EIGEN_METIS
TEST_F(DynamicSparseNormalCholeskySolverTest, EigenNESDIS) {
TestSolver(EIGEN_SPARSE, OrderingType::NESDIS);
}
#endif
#endif // CERES_USE_EIGEN_SPARSE
} // namespace internal
} // namespace ceres