| // Ceres Solver - A fast non-linear least squares minimizer | |
| // Copyright 2015 Google Inc. All rights reserved. | |
| // http://ceres-solver.org/ | |
| // | |
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| // | |
| // Author: sameeragarwal@google.com (Sameer Agarwal) | |
| #include "ceres/partitioned_matrix_view.h" | |
| #include <vector> | |
| #include "ceres/block_structure.h" | |
| #include "ceres/casts.h" | |
| #include "ceres/internal/eigen.h" | |
| #include "ceres/internal/scoped_ptr.h" | |
| #include "ceres/linear_least_squares_problems.h" | |
| #include "ceres/random.h" | |
| #include "ceres/sparse_matrix.h" | |
| #include "glog/logging.h" | |
| #include "gtest/gtest.h" | |
| namespace ceres { | |
| namespace internal { | |
| const double kEpsilon = 1e-14; | |
| class PartitionedMatrixViewTest : public ::testing::Test { | |
| protected : | |
| virtual void SetUp() { | |
| srand(5); | |
| scoped_ptr<LinearLeastSquaresProblem> problem( | |
| CreateLinearLeastSquaresProblemFromId(2)); | |
| CHECK_NOTNULL(problem.get()); | |
| A_.reset(problem->A.release()); | |
| num_cols_ = A_->num_cols(); | |
| num_rows_ = A_->num_rows(); | |
| num_eliminate_blocks_ = problem->num_eliminate_blocks; | |
| LinearSolver::Options options; | |
| options.elimination_groups.push_back(num_eliminate_blocks_); | |
| pmv_.reset(PartitionedMatrixViewBase::Create( | |
| options, | |
| *down_cast<BlockSparseMatrix*>(A_.get()))); | |
| } | |
| int num_rows_; | |
| int num_cols_; | |
| int num_eliminate_blocks_; | |
| scoped_ptr<SparseMatrix> A_; | |
| scoped_ptr<PartitionedMatrixViewBase> pmv_; | |
| }; | |
| TEST_F(PartitionedMatrixViewTest, DimensionsTest) { | |
| EXPECT_EQ(pmv_->num_col_blocks_e(), num_eliminate_blocks_); | |
| EXPECT_EQ(pmv_->num_col_blocks_f(), num_cols_ - num_eliminate_blocks_); | |
| EXPECT_EQ(pmv_->num_cols_e(), num_eliminate_blocks_); | |
| EXPECT_EQ(pmv_->num_cols_f(), num_cols_ - num_eliminate_blocks_); | |
| EXPECT_EQ(pmv_->num_cols(), A_->num_cols()); | |
| EXPECT_EQ(pmv_->num_rows(), A_->num_rows()); | |
| } | |
| TEST_F(PartitionedMatrixViewTest, RightMultiplyE) { | |
| Vector x1(pmv_->num_cols_e()); | |
| Vector x2(pmv_->num_cols()); | |
| x2.setZero(); | |
| for (int i = 0; i < pmv_->num_cols_e(); ++i) { | |
| x1(i) = x2(i) = RandDouble(); | |
| } | |
| Vector y1 = Vector::Zero(pmv_->num_rows()); | |
| pmv_->RightMultiplyE(x1.data(), y1.data()); | |
| Vector y2 = Vector::Zero(pmv_->num_rows()); | |
| A_->RightMultiply(x2.data(), y2.data()); | |
| for (int i = 0; i < pmv_->num_rows(); ++i) { | |
| EXPECT_NEAR(y1(i), y2(i), kEpsilon); | |
| } | |
| } | |
| TEST_F(PartitionedMatrixViewTest, RightMultiplyF) { | |
| Vector x1(pmv_->num_cols_f()); | |
| Vector x2 = Vector::Zero(pmv_->num_cols()); | |
| for (int i = 0; i < pmv_->num_cols_f(); ++i) { | |
| x1(i) = RandDouble(); | |
| x2(i + pmv_->num_cols_e()) = x1(i); | |
| } | |
| Vector y1 = Vector::Zero(pmv_->num_rows()); | |
| pmv_->RightMultiplyF(x1.data(), y1.data()); | |
| Vector y2 = Vector::Zero(pmv_->num_rows()); | |
| A_->RightMultiply(x2.data(), y2.data()); | |
| for (int i = 0; i < pmv_->num_rows(); ++i) { | |
| EXPECT_NEAR(y1(i), y2(i), kEpsilon); | |
| } | |
| } | |
| TEST_F(PartitionedMatrixViewTest, LeftMultiply) { | |
| Vector x = Vector::Zero(pmv_->num_rows()); | |
| for (int i = 0; i < pmv_->num_rows(); ++i) { | |
| x(i) = RandDouble(); | |
| } | |
| Vector y = Vector::Zero(pmv_->num_cols()); | |
| Vector y1 = Vector::Zero(pmv_->num_cols_e()); | |
| Vector y2 = Vector::Zero(pmv_->num_cols_f()); | |
| A_->LeftMultiply(x.data(), y.data()); | |
| pmv_->LeftMultiplyE(x.data(), y1.data()); | |
| pmv_->LeftMultiplyF(x.data(), y2.data()); | |
| for (int i = 0; i < pmv_->num_cols(); ++i) { | |
| EXPECT_NEAR(y(i), | |
| (i < pmv_->num_cols_e()) ? y1(i) : y2(i - pmv_->num_cols_e()), | |
| kEpsilon); | |
| } | |
| } | |
| TEST_F(PartitionedMatrixViewTest, BlockDiagonalEtE) { | |
| scoped_ptr<BlockSparseMatrix> | |
| block_diagonal_ee(pmv_->CreateBlockDiagonalEtE()); | |
| const CompressedRowBlockStructure* bs = block_diagonal_ee->block_structure(); | |
| EXPECT_EQ(block_diagonal_ee->num_rows(), 2); | |
| EXPECT_EQ(block_diagonal_ee->num_cols(), 2); | |
| EXPECT_EQ(bs->cols.size(), 2); | |
| EXPECT_EQ(bs->rows.size(), 2); | |
| EXPECT_NEAR(block_diagonal_ee->values()[0], 10.0, kEpsilon); | |
| EXPECT_NEAR(block_diagonal_ee->values()[1], 155.0, kEpsilon); | |
| } | |
| TEST_F(PartitionedMatrixViewTest, BlockDiagonalFtF) { | |
| scoped_ptr<BlockSparseMatrix> | |
| block_diagonal_ff(pmv_->CreateBlockDiagonalFtF()); | |
| const CompressedRowBlockStructure* bs = block_diagonal_ff->block_structure(); | |
| EXPECT_EQ(block_diagonal_ff->num_rows(), 3); | |
| EXPECT_EQ(block_diagonal_ff->num_cols(), 3); | |
| EXPECT_EQ(bs->cols.size(), 3); | |
| EXPECT_EQ(bs->rows.size(), 3); | |
| EXPECT_NEAR(block_diagonal_ff->values()[0], 70.0, kEpsilon); | |
| EXPECT_NEAR(block_diagonal_ff->values()[1], 17.0, kEpsilon); | |
| EXPECT_NEAR(block_diagonal_ff->values()[2], 37.0, kEpsilon); | |
| } | |
| } // namespace internal | |
| } // namespace ceres |