| // 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 <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 |