1// Ceres Solver - A fast non-linear least squares minimizer 2// Copyright 2010, 2011, 2012 Google Inc. All rights reserved. 3// http://code.google.com/p/ceres-solver/ 4// 5// Redistribution and use in source and binary forms, with or without 6// modification, are permitted provided that the following conditions are met: 7// 8// * Redistributions of source code must retain the above copyright notice, 9// this list of conditions and the following disclaimer. 10// * Redistributions in binary form must reproduce the above copyright notice, 11// this list of conditions and the following disclaimer in the documentation 12// and/or other materials provided with the distribution. 13// * Neither the name of Google Inc. nor the names of its contributors may be 14// used to endorse or promote products derived from this software without 15// specific prior written permission. 16// 17// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" 18// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE 19// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE 20// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE 21// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR 22// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF 23// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS 24// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN 25// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) 26// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE 27// POSSIBILITY OF SUCH DAMAGE. 28// 29// Author: sameeragarwal@google.com (Sameer Agarwal) 30 31#include "ceres/block_sparse_matrix.h" 32 33#include <string> 34#include "ceres/casts.h" 35#include "ceres/internal/eigen.h" 36#include "ceres/internal/scoped_ptr.h" 37#include "ceres/linear_least_squares_problems.h" 38#include "ceres/triplet_sparse_matrix.h" 39#include "glog/logging.h" 40#include "gtest/gtest.h" 41 42namespace ceres { 43namespace internal { 44 45class BlockSparseMatrixTest : public ::testing::Test { 46 protected : 47 virtual void SetUp() { 48 scoped_ptr<LinearLeastSquaresProblem> problem( 49 CreateLinearLeastSquaresProblemFromId(2)); 50 CHECK_NOTNULL(problem.get()); 51 A_.reset(down_cast<BlockSparseMatrix*>(problem->A.release())); 52 53 problem.reset(CreateLinearLeastSquaresProblemFromId(1)); 54 CHECK_NOTNULL(problem.get()); 55 B_.reset(down_cast<TripletSparseMatrix*>(problem->A.release())); 56 57 CHECK_EQ(A_->num_rows(), B_->num_rows()); 58 CHECK_EQ(A_->num_cols(), B_->num_cols()); 59 CHECK_EQ(A_->num_nonzeros(), B_->num_nonzeros()); 60 } 61 62 scoped_ptr<BlockSparseMatrix> A_; 63 scoped_ptr<TripletSparseMatrix> B_; 64}; 65 66TEST_F(BlockSparseMatrixTest, SetZeroTest) { 67 A_->SetZero(); 68 EXPECT_EQ(13, A_->num_nonzeros()); 69} 70 71TEST_F(BlockSparseMatrixTest, RightMultiplyTest) { 72 Vector y_a = Vector::Zero(A_->num_rows()); 73 Vector y_b = Vector::Zero(A_->num_rows()); 74 for (int i = 0; i < A_->num_cols(); ++i) { 75 Vector x = Vector::Zero(A_->num_cols()); 76 x[i] = 1.0; 77 A_->RightMultiply(x.data(), y_a.data()); 78 B_->RightMultiply(x.data(), y_b.data()); 79 EXPECT_LT((y_a - y_b).norm(), 1e-12); 80 } 81} 82 83TEST_F(BlockSparseMatrixTest, LeftMultiplyTest) { 84 Vector y_a = Vector::Zero(A_->num_cols()); 85 Vector y_b = Vector::Zero(A_->num_cols()); 86 for (int i = 0; i < A_->num_rows(); ++i) { 87 Vector x = Vector::Zero(A_->num_rows()); 88 x[i] = 1.0; 89 A_->LeftMultiply(x.data(), y_a.data()); 90 B_->LeftMultiply(x.data(), y_b.data()); 91 EXPECT_LT((y_a - y_b).norm(), 1e-12); 92 } 93} 94 95TEST_F(BlockSparseMatrixTest, SquaredColumnNormTest) { 96 Vector y_a = Vector::Zero(A_->num_cols()); 97 Vector y_b = Vector::Zero(A_->num_cols()); 98 A_->SquaredColumnNorm(y_a.data()); 99 B_->SquaredColumnNorm(y_b.data()); 100 EXPECT_LT((y_a - y_b).norm(), 1e-12); 101} 102 103TEST_F(BlockSparseMatrixTest, ToDenseMatrixTest) { 104 Matrix m_a; 105 Matrix m_b; 106 A_->ToDenseMatrix(&m_a); 107 B_->ToDenseMatrix(&m_b); 108 EXPECT_LT((m_a - m_b).norm(), 1e-12); 109} 110 111} // namespace internal 112} // namespace ceres 113