| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135 | // 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/matrix_proto.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);}#ifndef CERES_NO_PROTOCOL_BUFFERSTEST_F(BlockSparseMatrixTest, Serialization) {  // Roundtrip through serialization and check for equality.  SparseMatrixProto proto;  A_->ToProto(&proto);  LOG(INFO) << proto.DebugString();  BlockSparseMatrix A2(proto);  Matrix m_a;  Matrix m_b;  A_->ToDenseMatrix(&m_a);  A2.ToDenseMatrix(&m_b);  LOG(INFO) << "\n" << m_a;  LOG(INFO) << "\n" << m_b;  EXPECT_LT((m_a - m_b).norm(), 1e-12);}#endif}  // namespace internal}  // namespace ceres
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