| // 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: |
| // |
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| // 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 |
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| // specific prior written permission. |
| // |
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| // |
| // Author: sameeragarwal@google.com (Sameer Agarwal) |
| |
| #include "ceres/block_jacobi_preconditioner.h" |
| |
| #include <memory> |
| #include <random> |
| #include <vector> |
| |
| #include "Eigen/Dense" |
| #include "ceres/block_random_access_diagonal_matrix.h" |
| #include "ceres/block_sparse_matrix.h" |
| #include "ceres/linear_least_squares_problems.h" |
| #include "gtest/gtest.h" |
| |
| namespace ceres::internal { |
| |
| TEST(BlockSparseJacobiPreconditioner, _) { |
| constexpr int kNumtrials = 10; |
| BlockSparseMatrix::RandomMatrixOptions options; |
| options.num_col_blocks = 3; |
| options.min_col_block_size = 1; |
| options.max_col_block_size = 3; |
| |
| options.num_row_blocks = 5; |
| options.min_row_block_size = 1; |
| options.max_row_block_size = 4; |
| options.block_density = 0.25; |
| std::mt19937 prng; |
| |
| Preconditioner::Options preconditioner_options; |
| ContextImpl context; |
| preconditioner_options.context = &context; |
| |
| for (int trial = 0; trial < kNumtrials; ++trial) { |
| auto jacobian = BlockSparseMatrix::CreateRandomMatrix(options, prng); |
| Vector diagonal = Vector::Ones(jacobian->num_cols()); |
| Matrix dense_jacobian; |
| jacobian->ToDenseMatrix(&dense_jacobian); |
| Matrix hessian = dense_jacobian.transpose() * dense_jacobian; |
| hessian.diagonal() += diagonal.array().square().matrix(); |
| |
| BlockSparseJacobiPreconditioner pre(preconditioner_options, *jacobian); |
| pre.Update(*jacobian, diagonal.data()); |
| |
| // The const_cast is needed to be able to call GetCell. |
| auto* m = const_cast<BlockRandomAccessDiagonalMatrix*>(&pre.matrix()); |
| EXPECT_EQ(m->num_rows(), jacobian->num_cols()); |
| EXPECT_EQ(m->num_cols(), jacobian->num_cols()); |
| |
| const CompressedRowBlockStructure* bs = jacobian->block_structure(); |
| for (int i = 0; i < bs->cols.size(); ++i) { |
| const int block_size = bs->cols[i].size; |
| int r, c, row_stride, col_stride; |
| CellInfo* cell_info = m->GetCell(i, i, &r, &c, &row_stride, &col_stride); |
| Matrix actual_block_inverse = |
| MatrixRef(cell_info->values, row_stride, col_stride) |
| .block(r, c, block_size, block_size); |
| Matrix expected_block = hessian.block( |
| bs->cols[i].position, bs->cols[i].position, block_size, block_size); |
| const double residual = (actual_block_inverse * expected_block - |
| Matrix::Identity(block_size, block_size)) |
| .norm(); |
| EXPECT_NEAR(residual, 0.0, 1e-12) << "Block: " << i; |
| } |
| options.num_col_blocks++; |
| options.num_row_blocks++; |
| } |
| } |
| |
| TEST(CompressedRowSparseJacobiPreconditioner, _) { |
| constexpr int kNumtrials = 10; |
| CompressedRowSparseMatrix::RandomMatrixOptions options; |
| options.num_col_blocks = 3; |
| options.min_col_block_size = 1; |
| options.max_col_block_size = 3; |
| |
| options.num_row_blocks = 5; |
| options.min_row_block_size = 1; |
| options.max_row_block_size = 4; |
| options.block_density = 0.25; |
| std::mt19937 prng; |
| |
| Preconditioner::Options preconditioner_options; |
| ContextImpl context; |
| preconditioner_options.context = &context; |
| |
| for (int trial = 0; trial < kNumtrials; ++trial) { |
| auto jacobian = |
| CompressedRowSparseMatrix::CreateRandomMatrix(options, prng); |
| Vector diagonal = Vector::Ones(jacobian->num_cols()); |
| |
| Matrix dense_jacobian; |
| jacobian->ToDenseMatrix(&dense_jacobian); |
| Matrix hessian = dense_jacobian.transpose() * dense_jacobian; |
| hessian.diagonal() += diagonal.array().square().matrix(); |
| |
| BlockCRSJacobiPreconditioner pre(preconditioner_options, *jacobian); |
| pre.Update(*jacobian, diagonal.data()); |
| auto& m = pre.matrix(); |
| |
| EXPECT_EQ(m.num_rows(), jacobian->num_cols()); |
| EXPECT_EQ(m.num_cols(), jacobian->num_cols()); |
| |
| const auto& col_blocks = jacobian->col_blocks(); |
| for (int i = 0, col = 0; i < col_blocks.size(); ++i) { |
| const int block_size = col_blocks[i].size; |
| int idx = m.rows()[col]; |
| for (int j = 0; j < block_size; ++j) { |
| EXPECT_EQ(m.rows()[col + j + 1] - m.rows()[col + j], block_size); |
| for (int k = 0; k < block_size; ++k, ++idx) { |
| EXPECT_EQ(m.cols()[idx], col + k); |
| } |
| } |
| |
| ConstMatrixRef actual_block_inverse( |
| m.values() + m.rows()[col], block_size, block_size); |
| Matrix expected_block = hessian.block(col, col, block_size, block_size); |
| const double residual = (actual_block_inverse * expected_block - |
| Matrix::Identity(block_size, block_size)) |
| .norm(); |
| EXPECT_NEAR(residual, 0.0, 1e-12) << "Block: " << i; |
| col += block_size; |
| } |
| options.num_col_blocks++; |
| options.num_row_blocks++; |
| } |
| } |
| |
| } // namespace ceres::internal |