106 lines
4.1 KiB
C++
106 lines
4.1 KiB
C++
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// Ceres Solver - A fast non-linear least squares minimizer
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// Copyright 2015 Google Inc. All rights reserved.
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// http://ceres-solver.org/
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//
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// Redistribution and use in source and binary forms, with or without
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// modification, are permitted provided that the following conditions are met:
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//
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// * Redistributions of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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// * Redistributions in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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// * Neither the name of Google Inc. nor the names of its contributors may be
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// used to endorse or promote products derived from this software without
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// specific prior written permission.
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//
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// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
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// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
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// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
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// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
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// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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// POSSIBILITY OF SUCH DAMAGE.
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//
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// Author: sameeragarwal@google.com (Sameer Agarwal)
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#include "ceres/block_jacobi_preconditioner.h"
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#include <vector>
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#include "ceres/block_random_access_diagonal_matrix.h"
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#include "ceres/linear_least_squares_problems.h"
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#include "ceres/block_sparse_matrix.h"
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#include "ceres/internal/scoped_ptr.h"
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#include "gtest/gtest.h"
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#include "Eigen/Dense"
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namespace ceres {
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namespace internal {
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class BlockJacobiPreconditionerTest : public ::testing::Test {
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protected:
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void SetUpFromProblemId(int problem_id) {
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scoped_ptr<LinearLeastSquaresProblem> problem(
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CreateLinearLeastSquaresProblemFromId(problem_id));
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CHECK_NOTNULL(problem.get());
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A.reset(down_cast<BlockSparseMatrix*>(problem->A.release()));
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D.reset(problem->D.release());
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Matrix dense_a;
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A->ToDenseMatrix(&dense_a);
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dense_ata = dense_a.transpose() * dense_a;
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dense_ata += VectorRef(D.get(), A->num_cols())
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.array().square().matrix().asDiagonal();
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}
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void VerifyDiagonalBlocks(const int problem_id) {
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SetUpFromProblemId(problem_id);
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BlockJacobiPreconditioner pre(*A);
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pre.Update(*A, D.get());
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BlockRandomAccessDiagonalMatrix* m =
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const_cast<BlockRandomAccessDiagonalMatrix*>(&pre.matrix());
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EXPECT_EQ(m->num_rows(), A->num_cols());
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EXPECT_EQ(m->num_cols(), A->num_cols());
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const CompressedRowBlockStructure* bs = A->block_structure();
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for (int i = 0; i < bs->cols.size(); ++i) {
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const int block_size = bs->cols[i].size;
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int r, c, row_stride, col_stride;
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CellInfo* cell_info = m->GetCell(i, i,
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&r, &c,
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&row_stride, &col_stride);
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MatrixRef m(cell_info->values, row_stride, col_stride);
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Matrix actual_block_inverse = m.block(r, c, block_size, block_size);
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Matrix expected_block = dense_ata.block(bs->cols[i].position,
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bs->cols[i].position,
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block_size,
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block_size);
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const double residual = (actual_block_inverse * expected_block -
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Matrix::Identity(block_size, block_size)).norm();
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EXPECT_NEAR(residual, 0.0, 1e-12) << "Block: " << i;
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}
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}
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scoped_ptr<BlockSparseMatrix> A;
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scoped_array<double> D;
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Matrix dense_ata;
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};
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TEST_F(BlockJacobiPreconditionerTest, SmallProblem) {
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VerifyDiagonalBlocks(2);
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}
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TEST_F(BlockJacobiPreconditionerTest, LargeProblem) {
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VerifyDiagonalBlocks(3);
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}
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} // namespace internal
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} // namespace ceres
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