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      1 // Ceres Solver - A fast non-linear least squares minimizer
      2 // Copyright 2014 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: richie.stebbing (at) gmail.com (Richard Stebbing)
     30 
     31 #include "ceres/dynamic_compressed_row_sparse_matrix.h"
     32 
     33 #include "ceres/casts.h"
     34 #include "ceres/compressed_row_sparse_matrix.h"
     35 #include "ceres/casts.h"
     36 #include "ceres/internal/eigen.h"
     37 #include "ceres/internal/scoped_ptr.h"
     38 #include "ceres/linear_least_squares_problems.h"
     39 #include "ceres/triplet_sparse_matrix.h"
     40 #include "gtest/gtest.h"
     41 
     42 namespace ceres {
     43 namespace internal {
     44 
     45 class DynamicCompressedRowSparseMatrixTest : public ::testing::Test {
     46  protected:
     47   virtual void SetUp() {
     48     num_rows = 7;
     49     num_cols = 4;
     50 
     51     // The number of additional elements reserved when `Finalize` is called
     52     // should have no effect on the number of rows, columns or nonzeros.
     53     // Set this to some nonzero value to be sure.
     54     num_additional_elements = 13;
     55 
     56     expected_num_nonzeros = num_rows * num_cols - min(num_rows, num_cols);
     57 
     58     InitialiseDenseReference();
     59     InitialiseSparseMatrixReferences();
     60 
     61     dcrsm.reset(new DynamicCompressedRowSparseMatrix(num_rows,
     62                                                      num_cols,
     63                                                      0));
     64   }
     65 
     66   void Finalize() {
     67     dcrsm->Finalize(num_additional_elements);
     68   }
     69 
     70   void InitialiseDenseReference() {
     71     dense.resize(num_rows, num_cols);
     72     dense.setZero();
     73     int num_nonzeros = 0;
     74     for (int i = 0; i < (num_rows * num_cols); ++i) {
     75       const int r = i / num_cols, c = i % num_cols;
     76       if (r != c) {
     77         dense(r, c) = i + 1;
     78         ++num_nonzeros;
     79       }
     80     }
     81     ASSERT_EQ(num_nonzeros, expected_num_nonzeros);
     82   }
     83 
     84   void InitialiseSparseMatrixReferences() {
     85     std::vector<int> rows, cols;
     86     std::vector<double> values;
     87     for (int i = 0; i < (num_rows * num_cols); ++i) {
     88       const int r = i / num_cols, c = i % num_cols;
     89       if (r != c) {
     90         rows.push_back(r);
     91         cols.push_back(c);
     92         values.push_back(i + 1);
     93       }
     94     }
     95     ASSERT_EQ(values.size(), expected_num_nonzeros);
     96 
     97     tsm.reset(new TripletSparseMatrix(num_rows,
     98                                       num_cols,
     99                                       expected_num_nonzeros));
    100     std::copy(rows.begin(), rows.end(), tsm->mutable_rows());
    101     std::copy(cols.begin(), cols.end(), tsm->mutable_cols());
    102     std::copy(values.begin(), values.end(), tsm->mutable_values());
    103     tsm->set_num_nonzeros(values.size());
    104 
    105     Matrix dense_from_tsm;
    106     tsm->ToDenseMatrix(&dense_from_tsm);
    107     ASSERT_TRUE((dense.array() == dense_from_tsm.array()).all());
    108 
    109     crsm.reset(new CompressedRowSparseMatrix(*tsm));
    110     Matrix dense_from_crsm;
    111     crsm->ToDenseMatrix(&dense_from_crsm);
    112     ASSERT_TRUE((dense.array() == dense_from_crsm.array()).all());
    113   }
    114 
    115   void InsertNonZeroEntriesFromDenseReference() {
    116     for (int r = 0; r < num_rows; ++r) {
    117       for (int c = 0; c < num_cols; ++c) {
    118         const double& v = dense(r, c);
    119         if (v != 0.0) {
    120           dcrsm->InsertEntry(r, c, v);
    121         }
    122       }
    123     }
    124   }
    125 
    126   void ExpectEmpty() {
    127     EXPECT_EQ(dcrsm->num_rows(), num_rows);
    128     EXPECT_EQ(dcrsm->num_cols(), num_cols);
    129     EXPECT_EQ(dcrsm->num_nonzeros(), 0);
    130 
    131     Matrix dense_from_dcrsm;
    132     dcrsm->ToDenseMatrix(&dense_from_dcrsm);
    133     EXPECT_EQ(dense_from_dcrsm.rows(), num_rows);
    134     EXPECT_EQ(dense_from_dcrsm.cols(), num_cols);
    135     EXPECT_TRUE((dense_from_dcrsm.array() == 0.0).all());
    136   }
    137 
    138   void ExpectEqualToDenseReference() {
    139     Matrix dense_from_dcrsm;
    140     dcrsm->ToDenseMatrix(&dense_from_dcrsm);
    141     EXPECT_TRUE((dense.array() == dense_from_dcrsm.array()).all());
    142   }
    143 
    144   void ExpectEqualToCompressedRowSparseMatrixReference() {
    145     typedef Eigen::Map<const Eigen::VectorXi> ConstIntVectorRef;
    146 
    147     ConstIntVectorRef crsm_rows(crsm->rows(), crsm->num_rows() + 1);
    148     ConstIntVectorRef dcrsm_rows(dcrsm->rows(), dcrsm->num_rows() + 1);
    149     EXPECT_TRUE((crsm_rows.array() == dcrsm_rows.array()).all());
    150 
    151     ConstIntVectorRef crsm_cols(crsm->cols(), crsm->num_nonzeros());
    152     ConstIntVectorRef dcrsm_cols(dcrsm->cols(), dcrsm->num_nonzeros());
    153     EXPECT_TRUE((crsm_cols.array() == dcrsm_cols.array()).all());
    154 
    155     ConstVectorRef crsm_values(crsm->values(), crsm->num_nonzeros());
    156     ConstVectorRef dcrsm_values(dcrsm->values(), dcrsm->num_nonzeros());
    157     EXPECT_TRUE((crsm_values.array() == dcrsm_values.array()).all());
    158   }
    159 
    160   int num_rows;
    161   int num_cols;
    162 
    163   int num_additional_elements;
    164 
    165   int expected_num_nonzeros;
    166 
    167   Matrix dense;
    168   scoped_ptr<TripletSparseMatrix> tsm;
    169   scoped_ptr<CompressedRowSparseMatrix> crsm;
    170 
    171   scoped_ptr<DynamicCompressedRowSparseMatrix> dcrsm;
    172 };
    173 
    174 TEST_F(DynamicCompressedRowSparseMatrixTest, Initialization) {
    175   ExpectEmpty();
    176 
    177   Finalize();
    178   ExpectEmpty();
    179 }
    180 
    181 TEST_F(DynamicCompressedRowSparseMatrixTest, InsertEntryAndFinalize) {
    182   InsertNonZeroEntriesFromDenseReference();
    183   ExpectEmpty();
    184 
    185   Finalize();
    186   ExpectEqualToDenseReference();
    187   ExpectEqualToCompressedRowSparseMatrixReference();
    188 }
    189 
    190 TEST_F(DynamicCompressedRowSparseMatrixTest, ClearRows) {
    191   InsertNonZeroEntriesFromDenseReference();
    192   Finalize();
    193   ExpectEqualToDenseReference();
    194   ExpectEqualToCompressedRowSparseMatrixReference();
    195 
    196   dcrsm->ClearRows(0, 0);
    197   Finalize();
    198   ExpectEqualToDenseReference();
    199   ExpectEqualToCompressedRowSparseMatrixReference();
    200 
    201   dcrsm->ClearRows(0, num_rows);
    202   ExpectEqualToCompressedRowSparseMatrixReference();
    203 
    204   Finalize();
    205   ExpectEmpty();
    206 
    207   InsertNonZeroEntriesFromDenseReference();
    208   dcrsm->ClearRows(1, 2);
    209   Finalize();
    210   dense.block(1, 0, 2, num_cols).setZero();
    211   ExpectEqualToDenseReference();
    212 
    213   InitialiseDenseReference();
    214 }
    215 
    216 }  // namespace internal
    217 }  // namespace ceres
    218