// Ceres Solver - A fast non-linear least squares minimizer // Copyright 2010, 2011, 2012 Google Inc. All rights reserved. // http://code.google.com/p/ceres-solver/ // // 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 <string> #include "ceres/casts.h" #include "ceres/internal/eigen.h" #include "ceres/internal/scoped_ptr.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() { scoped_ptr<LinearLeastSquaresProblem> problem( CreateLinearLeastSquaresProblemFromId(2)); CHECK_NOTNULL(problem.get()); A_.reset(down_cast<BlockSparseMatrix*>(problem->A.release())); problem.reset(CreateLinearLeastSquaresProblemFromId(1)); CHECK_NOTNULL(problem.get()); 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()); } scoped_ptr<BlockSparseMatrix> A_; scoped_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); } } // namespace internal } // namespace ceres