175 lines
6.0 KiB
C++
175 lines
6.0 KiB
C++
// 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/partitioned_matrix_view.h"
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#include <vector>
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#include "ceres/block_structure.h"
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#include "ceres/casts.h"
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#include "ceres/internal/eigen.h"
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#include "ceres/internal/scoped_ptr.h"
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#include "ceres/linear_least_squares_problems.h"
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#include "ceres/random.h"
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#include "ceres/sparse_matrix.h"
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#include "glog/logging.h"
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#include "gtest/gtest.h"
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namespace ceres {
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namespace internal {
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const double kEpsilon = 1e-14;
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class PartitionedMatrixViewTest : public ::testing::Test {
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protected :
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virtual void SetUp() {
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srand(5);
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scoped_ptr<LinearLeastSquaresProblem> problem(
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CreateLinearLeastSquaresProblemFromId(2));
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CHECK_NOTNULL(problem.get());
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A_.reset(problem->A.release());
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num_cols_ = A_->num_cols();
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num_rows_ = A_->num_rows();
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num_eliminate_blocks_ = problem->num_eliminate_blocks;
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LinearSolver::Options options;
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options.elimination_groups.push_back(num_eliminate_blocks_);
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pmv_.reset(PartitionedMatrixViewBase::Create(
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options,
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*down_cast<BlockSparseMatrix*>(A_.get())));
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}
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int num_rows_;
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int num_cols_;
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int num_eliminate_blocks_;
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scoped_ptr<SparseMatrix> A_;
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scoped_ptr<PartitionedMatrixViewBase> pmv_;
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};
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TEST_F(PartitionedMatrixViewTest, DimensionsTest) {
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EXPECT_EQ(pmv_->num_col_blocks_e(), num_eliminate_blocks_);
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EXPECT_EQ(pmv_->num_col_blocks_f(), num_cols_ - num_eliminate_blocks_);
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EXPECT_EQ(pmv_->num_cols_e(), num_eliminate_blocks_);
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EXPECT_EQ(pmv_->num_cols_f(), num_cols_ - num_eliminate_blocks_);
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EXPECT_EQ(pmv_->num_cols(), A_->num_cols());
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EXPECT_EQ(pmv_->num_rows(), A_->num_rows());
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}
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TEST_F(PartitionedMatrixViewTest, RightMultiplyE) {
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Vector x1(pmv_->num_cols_e());
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Vector x2(pmv_->num_cols());
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x2.setZero();
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for (int i = 0; i < pmv_->num_cols_e(); ++i) {
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x1(i) = x2(i) = RandDouble();
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}
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Vector y1 = Vector::Zero(pmv_->num_rows());
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pmv_->RightMultiplyE(x1.data(), y1.data());
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Vector y2 = Vector::Zero(pmv_->num_rows());
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A_->RightMultiply(x2.data(), y2.data());
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for (int i = 0; i < pmv_->num_rows(); ++i) {
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EXPECT_NEAR(y1(i), y2(i), kEpsilon);
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}
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}
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TEST_F(PartitionedMatrixViewTest, RightMultiplyF) {
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Vector x1(pmv_->num_cols_f());
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Vector x2 = Vector::Zero(pmv_->num_cols());
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for (int i = 0; i < pmv_->num_cols_f(); ++i) {
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x1(i) = RandDouble();
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x2(i + pmv_->num_cols_e()) = x1(i);
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}
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Vector y1 = Vector::Zero(pmv_->num_rows());
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pmv_->RightMultiplyF(x1.data(), y1.data());
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Vector y2 = Vector::Zero(pmv_->num_rows());
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A_->RightMultiply(x2.data(), y2.data());
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for (int i = 0; i < pmv_->num_rows(); ++i) {
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EXPECT_NEAR(y1(i), y2(i), kEpsilon);
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}
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}
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TEST_F(PartitionedMatrixViewTest, LeftMultiply) {
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Vector x = Vector::Zero(pmv_->num_rows());
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for (int i = 0; i < pmv_->num_rows(); ++i) {
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x(i) = RandDouble();
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}
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Vector y = Vector::Zero(pmv_->num_cols());
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Vector y1 = Vector::Zero(pmv_->num_cols_e());
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Vector y2 = Vector::Zero(pmv_->num_cols_f());
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A_->LeftMultiply(x.data(), y.data());
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pmv_->LeftMultiplyE(x.data(), y1.data());
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pmv_->LeftMultiplyF(x.data(), y2.data());
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for (int i = 0; i < pmv_->num_cols(); ++i) {
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EXPECT_NEAR(y(i),
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(i < pmv_->num_cols_e()) ? y1(i) : y2(i - pmv_->num_cols_e()),
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kEpsilon);
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}
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}
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TEST_F(PartitionedMatrixViewTest, BlockDiagonalEtE) {
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scoped_ptr<BlockSparseMatrix>
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block_diagonal_ee(pmv_->CreateBlockDiagonalEtE());
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const CompressedRowBlockStructure* bs = block_diagonal_ee->block_structure();
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EXPECT_EQ(block_diagonal_ee->num_rows(), 2);
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EXPECT_EQ(block_diagonal_ee->num_cols(), 2);
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EXPECT_EQ(bs->cols.size(), 2);
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EXPECT_EQ(bs->rows.size(), 2);
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EXPECT_NEAR(block_diagonal_ee->values()[0], 10.0, kEpsilon);
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EXPECT_NEAR(block_diagonal_ee->values()[1], 155.0, kEpsilon);
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}
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TEST_F(PartitionedMatrixViewTest, BlockDiagonalFtF) {
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scoped_ptr<BlockSparseMatrix>
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block_diagonal_ff(pmv_->CreateBlockDiagonalFtF());
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const CompressedRowBlockStructure* bs = block_diagonal_ff->block_structure();
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EXPECT_EQ(block_diagonal_ff->num_rows(), 3);
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EXPECT_EQ(block_diagonal_ff->num_cols(), 3);
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EXPECT_EQ(bs->cols.size(), 3);
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EXPECT_EQ(bs->rows.size(), 3);
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EXPECT_NEAR(block_diagonal_ff->values()[0], 70.0, kEpsilon);
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EXPECT_NEAR(block_diagonal_ff->values()[1], 17.0, kEpsilon);
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EXPECT_NEAR(block_diagonal_ff->values()[2], 37.0, kEpsilon);
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}
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} // namespace internal
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} // namespace ceres
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