Squashed 'third_party/ceres/' content from commit e51e9b4
Change-Id: I763587619d57e594d3fa158dc3a7fe0b89a1743b
git-subtree-dir: third_party/ceres
git-subtree-split: e51e9b46f6ca88ab8b2266d0e362771db6d98067
diff --git a/internal/ceres/block_sparse_matrix_test.cc b/internal/ceres/block_sparse_matrix_test.cc
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+// 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:
+//
+// * Redistributions of source code must retain the above copyright notice,
+// 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
+// and/or other materials provided with the distribution.
+// * Neither the name of Google Inc. nor the names of its contributors may be
+// used to endorse or promote products derived from this software without
+// specific prior written permission.
+//
+// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
+// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
+// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
+// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
+// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
+// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
+// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
+// POSSIBILITY OF SUCH DAMAGE.
+//
+// Author: sameeragarwal@google.com (Sameer Agarwal)
+
+#include "ceres/block_sparse_matrix.h"
+
+#include <memory>
+#include <string>
+#include "ceres/casts.h"
+#include "ceres/internal/eigen.h"
+#include "ceres/linear_least_squares_problems.h"
+#include "ceres/triplet_sparse_matrix.h"
+#include "glog/logging.h"
+#include "gtest/gtest.h"
+
+namespace ceres {
+namespace internal {
+
+class BlockSparseMatrixTest : public ::testing::Test {
+ protected :
+ virtual void SetUp() {
+ std::unique_ptr<LinearLeastSquaresProblem> problem(
+ CreateLinearLeastSquaresProblemFromId(2));
+ CHECK(problem != nullptr);
+ A_.reset(down_cast<BlockSparseMatrix*>(problem->A.release()));
+
+ problem.reset(CreateLinearLeastSquaresProblemFromId(1));
+ CHECK(problem != nullptr);
+ B_.reset(down_cast<TripletSparseMatrix*>(problem->A.release()));
+
+ CHECK_EQ(A_->num_rows(), B_->num_rows());
+ CHECK_EQ(A_->num_cols(), B_->num_cols());
+ CHECK_EQ(A_->num_nonzeros(), B_->num_nonzeros());
+ }
+
+ std::unique_ptr<BlockSparseMatrix> A_;
+ std::unique_ptr<TripletSparseMatrix> B_;
+};
+
+TEST_F(BlockSparseMatrixTest, SetZeroTest) {
+ A_->SetZero();
+ EXPECT_EQ(13, A_->num_nonzeros());
+}
+
+TEST_F(BlockSparseMatrixTest, RightMultiplyTest) {
+ Vector y_a = Vector::Zero(A_->num_rows());
+ Vector y_b = Vector::Zero(A_->num_rows());
+ for (int i = 0; i < A_->num_cols(); ++i) {
+ Vector x = Vector::Zero(A_->num_cols());
+ x[i] = 1.0;
+ A_->RightMultiply(x.data(), y_a.data());
+ B_->RightMultiply(x.data(), y_b.data());
+ EXPECT_LT((y_a - y_b).norm(), 1e-12);
+ }
+}
+
+TEST_F(BlockSparseMatrixTest, LeftMultiplyTest) {
+ Vector y_a = Vector::Zero(A_->num_cols());
+ Vector y_b = Vector::Zero(A_->num_cols());
+ for (int i = 0; i < A_->num_rows(); ++i) {
+ Vector x = Vector::Zero(A_->num_rows());
+ x[i] = 1.0;
+ A_->LeftMultiply(x.data(), y_a.data());
+ B_->LeftMultiply(x.data(), y_b.data());
+ EXPECT_LT((y_a - y_b).norm(), 1e-12);
+ }
+}
+
+TEST_F(BlockSparseMatrixTest, SquaredColumnNormTest) {
+ Vector y_a = Vector::Zero(A_->num_cols());
+ Vector y_b = Vector::Zero(A_->num_cols());
+ A_->SquaredColumnNorm(y_a.data());
+ B_->SquaredColumnNorm(y_b.data());
+ EXPECT_LT((y_a - y_b).norm(), 1e-12);
+}
+
+TEST_F(BlockSparseMatrixTest, ToDenseMatrixTest) {
+ Matrix m_a;
+ Matrix m_b;
+ A_->ToDenseMatrix(&m_a);
+ B_->ToDenseMatrix(&m_b);
+ EXPECT_LT((m_a - m_b).norm(), 1e-12);
+}
+
+TEST_F(BlockSparseMatrixTest, AppendRows) {
+ std::unique_ptr<LinearLeastSquaresProblem> problem(
+ CreateLinearLeastSquaresProblemFromId(2));
+ std::unique_ptr<BlockSparseMatrix> m(
+ down_cast<BlockSparseMatrix*>(problem->A.release()));
+ A_->AppendRows(*m);
+ EXPECT_EQ(A_->num_rows(), 2 * m->num_rows());
+ EXPECT_EQ(A_->num_cols(), m->num_cols());
+
+ problem.reset(CreateLinearLeastSquaresProblemFromId(1));
+ std::unique_ptr<TripletSparseMatrix> m2(
+ down_cast<TripletSparseMatrix*>(problem->A.release()));
+ B_->AppendRows(*m2);
+
+ Vector y_a = Vector::Zero(A_->num_rows());
+ Vector y_b = Vector::Zero(A_->num_rows());
+ for (int i = 0; i < A_->num_cols(); ++i) {
+ Vector x = Vector::Zero(A_->num_cols());
+ x[i] = 1.0;
+ y_a.setZero();
+ y_b.setZero();
+
+ A_->RightMultiply(x.data(), y_a.data());
+ B_->RightMultiply(x.data(), y_b.data());
+ EXPECT_LT((y_a - y_b).norm(), 1e-12);
+ }
+}
+
+TEST_F(BlockSparseMatrixTest, AppendAndDeleteBlockDiagonalMatrix) {
+ const std::vector<Block>& column_blocks = A_->block_structure()->cols;
+ const int num_cols =
+ column_blocks.back().size + column_blocks.back().position;
+ Vector diagonal(num_cols);
+ for (int i = 0; i < num_cols; ++i) {
+ diagonal(i) = 2 * i * i + 1;
+ }
+ std::unique_ptr<BlockSparseMatrix> appendage(
+ BlockSparseMatrix::CreateDiagonalMatrix(diagonal.data(), column_blocks));
+
+ A_->AppendRows(*appendage);
+ Vector y_a, y_b;
+ y_a.resize(A_->num_rows());
+ y_b.resize(A_->num_rows());
+ for (int i = 0; i < A_->num_cols(); ++i) {
+ Vector x = Vector::Zero(A_->num_cols());
+ x[i] = 1.0;
+ y_a.setZero();
+ y_b.setZero();
+
+ A_->RightMultiply(x.data(), y_a.data());
+ B_->RightMultiply(x.data(), y_b.data());
+ EXPECT_LT((y_a.head(B_->num_rows()) - y_b.head(B_->num_rows())).norm(), 1e-12);
+ Vector expected_tail = Vector::Zero(A_->num_cols());
+ expected_tail(i) = diagonal(i);
+ EXPECT_LT((y_a.tail(A_->num_cols()) - expected_tail).norm(), 1e-12);
+ }
+
+
+ A_->DeleteRowBlocks(column_blocks.size());
+ EXPECT_EQ(A_->num_rows(), B_->num_rows());
+ EXPECT_EQ(A_->num_cols(), B_->num_cols());
+
+ y_a.resize(A_->num_rows());
+ y_b.resize(A_->num_rows());
+ for (int i = 0; i < A_->num_cols(); ++i) {
+ Vector x = Vector::Zero(A_->num_cols());
+ x[i] = 1.0;
+ y_a.setZero();
+ y_b.setZero();
+
+ A_->RightMultiply(x.data(), y_a.data());
+ B_->RightMultiply(x.data(), y_b.data());
+ EXPECT_LT((y_a - y_b).norm(), 1e-12);
+ }
+}
+
+TEST(BlockSparseMatrix, CreateDiagonalMatrix) {
+ std::vector<Block> column_blocks;
+ column_blocks.push_back(Block(2, 0));
+ column_blocks.push_back(Block(1, 2));
+ column_blocks.push_back(Block(3, 3));
+ const int num_cols =
+ column_blocks.back().size + column_blocks.back().position;
+ Vector diagonal(num_cols);
+ for (int i = 0; i < num_cols; ++i) {
+ diagonal(i) = 2 * i * i + 1;
+ }
+
+ std::unique_ptr<BlockSparseMatrix> m(
+ BlockSparseMatrix::CreateDiagonalMatrix(diagonal.data(), column_blocks));
+ const CompressedRowBlockStructure* bs = m->block_structure();
+ EXPECT_EQ(bs->cols.size(), column_blocks.size());
+ for (int i = 0; i < column_blocks.size(); ++i) {
+ EXPECT_EQ(bs->cols[i].size, column_blocks[i].size);
+ EXPECT_EQ(bs->cols[i].position, column_blocks[i].position);
+ }
+ EXPECT_EQ(m->num_rows(), m->num_cols());
+ Vector x = Vector::Ones(num_cols);
+ Vector y = Vector::Zero(num_cols);
+ m->RightMultiply(x.data(), y.data());
+ for (int i = 0; i < num_cols; ++i) {
+ EXPECT_NEAR(y[i], diagonal[i], std::numeric_limits<double>::epsilon());
+ }
+}
+
+
+} // namespace internal
+} // namespace ceres