| // Ceres Solver - A fast non-linear least squares minimizer | 
 | // Copyright 2023 Google Inc. All rights reserved. | 
 | // http://ceres-solver.org/ | 
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 | // | 
 | // Author: sameeragarwal@google.com (Sameer Agarwal) | 
 |  | 
 | #include "ceres/block_random_access_sparse_matrix.h" | 
 |  | 
 | #include <limits> | 
 | #include <memory> | 
 | #include <utility> | 
 | #include <vector> | 
 |  | 
 | #include "absl/container/btree_set.h" | 
 | #include "ceres/internal/eigen.h" | 
 | #include "gtest/gtest.h" | 
 |  | 
 | namespace ceres::internal { | 
 |  | 
 | TEST(BlockRandomAccessSparseMatrix, GetCell) { | 
 |   ContextImpl context; | 
 |   constexpr int num_threads = 1; | 
 |   std::vector<Block> blocks; | 
 |   blocks.emplace_back(3, 0); | 
 |   blocks.emplace_back(4, 3); | 
 |   blocks.emplace_back(5, 7); | 
 |   constexpr int num_rows = 3 + 4 + 5; | 
 |  | 
 |   absl::btree_set<std::pair<int, int>> block_pairs; | 
 |   int num_nonzeros = 0; | 
 |   block_pairs.emplace(0, 0); | 
 |   num_nonzeros += blocks[0].size * blocks[0].size; | 
 |  | 
 |   block_pairs.emplace(1, 1); | 
 |   num_nonzeros += blocks[1].size * blocks[1].size; | 
 |  | 
 |   block_pairs.emplace(1, 2); | 
 |   num_nonzeros += blocks[1].size * blocks[2].size; | 
 |  | 
 |   block_pairs.emplace(0, 2); | 
 |   num_nonzeros += blocks[2].size * blocks[0].size; | 
 |  | 
 |   BlockRandomAccessSparseMatrix m(blocks, block_pairs, &context, num_threads); | 
 |   EXPECT_EQ(m.num_rows(), num_rows); | 
 |   EXPECT_EQ(m.num_cols(), num_rows); | 
 |  | 
 |   for (const auto& block_pair : block_pairs) { | 
 |     const int row_block_id = block_pair.first; | 
 |     const int col_block_id = block_pair.second; | 
 |     int row; | 
 |     int col; | 
 |     int row_stride; | 
 |     int col_stride; | 
 |     CellInfo* cell = m.GetCell( | 
 |         row_block_id, col_block_id, &row, &col, &row_stride, &col_stride); | 
 |     EXPECT_TRUE(cell != nullptr); | 
 |     EXPECT_EQ(row, 0); | 
 |     EXPECT_EQ(col, 0); | 
 |     EXPECT_EQ(row_stride, blocks[row_block_id].size); | 
 |     EXPECT_EQ(col_stride, blocks[col_block_id].size); | 
 |  | 
 |     // Write into the block | 
 |     MatrixRef(cell->values, row_stride, col_stride) | 
 |         .block(row, col, blocks[row_block_id].size, blocks[col_block_id].size) = | 
 |         (row_block_id + 1) * (col_block_id + 1) * | 
 |         Matrix::Ones(blocks[row_block_id].size, blocks[col_block_id].size); | 
 |   } | 
 |  | 
 |   const BlockSparseMatrix* bsm = m.matrix(); | 
 |   EXPECT_EQ(bsm->num_nonzeros(), num_nonzeros); | 
 |  | 
 |   Matrix dense; | 
 |   bsm->ToDenseMatrix(&dense); | 
 |  | 
 |   double kTolerance = 1e-14; | 
 |  | 
 |   // (0, 0) | 
 |   EXPECT_NEAR( | 
 |       (dense.block(0, 0, 3, 3) - Matrix::Ones(3, 3)).norm(), 0.0, kTolerance); | 
 |   // (1, 1) | 
 |   EXPECT_NEAR((dense.block(3, 3, 4, 4) - 2 * 2 * Matrix::Ones(4, 4)).norm(), | 
 |               0.0, | 
 |               kTolerance); | 
 |   // (1, 2) | 
 |   EXPECT_NEAR((dense.block(3, 3 + 4, 4, 5) - 2 * 3 * Matrix::Ones(4, 5)).norm(), | 
 |               0.0, | 
 |               kTolerance); | 
 |   // (0, 2) | 
 |   EXPECT_NEAR((dense.block(0, 3 + 4, 3, 5) - 3 * 1 * Matrix::Ones(3, 5)).norm(), | 
 |               0.0, | 
 |               kTolerance); | 
 |  | 
 |   // There is nothing else in the matrix besides these four blocks. | 
 |   EXPECT_NEAR( | 
 |       dense.norm(), sqrt(9. + 16. * 16. + 36. * 20. + 9. * 15.), kTolerance); | 
 |  | 
 |   Vector x = Vector::Ones(dense.rows()); | 
 |   Vector actual_y = Vector::Zero(dense.rows()); | 
 |   Vector expected_y = Vector::Zero(dense.rows()); | 
 |  | 
 |   expected_y += dense.selfadjointView<Eigen::Upper>() * x; | 
 |   m.SymmetricRightMultiplyAndAccumulate(x.data(), actual_y.data()); | 
 |   EXPECT_NEAR((expected_y - actual_y).norm(), 0.0, kTolerance) | 
 |       << "actual: " << actual_y.transpose() << "\n" | 
 |       << "expected: " << expected_y.transpose() << "matrix: \n " << dense; | 
 | } | 
 |  | 
 | // IntPairToInt64 is private, thus this fixture is needed to access and | 
 | // test it. | 
 | class BlockRandomAccessSparseMatrixTest : public ::testing::Test { | 
 |  public: | 
 |   void SetUp() final { | 
 |     std::vector<Block> blocks; | 
 |     blocks.emplace_back(1, 0); | 
 |     absl::btree_set<std::pair<int, int>> block_pairs; | 
 |     block_pairs.emplace(0, 0); | 
 |     m_ = std::make_unique<BlockRandomAccessSparseMatrix>( | 
 |         blocks, block_pairs, &context_, 1); | 
 |   } | 
 |  | 
 |   void CheckIntPairToInt64(int a, int b) { | 
 |     int64_t value = m_->IntPairToInt64(a, b); | 
 |     EXPECT_GT(value, 0) << "Overflow a = " << a << " b = " << b; | 
 |     EXPECT_GT(value, a) << "Overflow a = " << a << " b = " << b; | 
 |     EXPECT_GT(value, b) << "Overflow a = " << a << " b = " << b; | 
 |   } | 
 |  | 
 |   void CheckInt64ToIntPair() { | 
 |     uint64_t max_rows = m_->kRowShift; | 
 |     for (int row = max_rows - 10; row < max_rows; ++row) { | 
 |       for (int col = 0; col < 10; ++col) { | 
 |         int row_computed; | 
 |         int col_computed; | 
 |         m_->Int64ToIntPair( | 
 |             m_->IntPairToInt64(row, col), &row_computed, &col_computed); | 
 |         EXPECT_EQ(row, row_computed); | 
 |         EXPECT_EQ(col, col_computed); | 
 |       } | 
 |     } | 
 |   } | 
 |  | 
 |  private: | 
 |   ContextImpl context_; | 
 |   std::unique_ptr<BlockRandomAccessSparseMatrix> m_; | 
 | }; | 
 |  | 
 | TEST_F(BlockRandomAccessSparseMatrixTest, IntPairToInt64Overflow) { | 
 |   CheckIntPairToInt64(std::numeric_limits<int32_t>::max(), | 
 |                       std::numeric_limits<int32_t>::max()); | 
 | } | 
 |  | 
 | TEST_F(BlockRandomAccessSparseMatrixTest, Int64ToIntPair) { | 
 |   CheckInt64ToIntPair(); | 
 | } | 
 |  | 
 | }  // namespace ceres::internal |