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Diffstat (limited to 'internal/ceres/dynamic_compressed_row_sparse_matrix_test.cc')
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1 files changed, 217 insertions, 0 deletions
diff --git a/internal/ceres/dynamic_compressed_row_sparse_matrix_test.cc b/internal/ceres/dynamic_compressed_row_sparse_matrix_test.cc new file mode 100644 index 0000000..03bfcb6 --- /dev/null +++ b/internal/ceres/dynamic_compressed_row_sparse_matrix_test.cc @@ -0,0 +1,217 @@ +// Ceres Solver - A fast non-linear least squares minimizer +// Copyright 2014 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: richie.stebbing@gmail.com (Richard Stebbing) + +#include "ceres/dynamic_compressed_row_sparse_matrix.h" + +#include "ceres/casts.h" +#include "ceres/compressed_row_sparse_matrix.h" +#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 "gtest/gtest.h" + +namespace ceres { +namespace internal { + +class DynamicCompressedRowSparseMatrixTest : public ::testing::Test { + protected: + virtual void SetUp() { + num_rows = 7; + num_cols = 4; + + // The number of additional elements reserved when `Finalize` is called + // should have no effect on the number of rows, columns or nonzeros. + // Set this to some nonzero value to be sure. + num_additional_elements = 13; + + expected_num_nonzeros = num_rows * num_cols - min(num_rows, num_cols); + + InitialiseDenseReference(); + InitialiseSparseMatrixReferences(); + + dcrsm.reset(new DynamicCompressedRowSparseMatrix(num_rows, + num_cols, + 0)); + } + + void Finalize() { + dcrsm->Finalize(num_additional_elements); + } + + void InitialiseDenseReference() { + dense.resize(num_rows, num_cols); + dense.setZero(); + int num_nonzeros = 0; + for (int i = 0; i < (num_rows * num_cols); ++i) { + const int r = i / num_cols, c = i % num_cols; + if (r != c) { + dense(r, c) = i + 1; + ++num_nonzeros; + } + } + ASSERT_EQ(num_nonzeros, expected_num_nonzeros); + } + + void InitialiseSparseMatrixReferences() { + std::vector<int> rows, cols; + std::vector<double> values; + for (int i = 0; i < (num_rows * num_cols); ++i) { + const int r = i / num_cols, c = i % num_cols; + if (r != c) { + rows.push_back(r); + cols.push_back(c); + values.push_back(i + 1); + } + } + ASSERT_EQ(values.size(), expected_num_nonzeros); + + tsm.reset(new TripletSparseMatrix(num_rows, + num_cols, + expected_num_nonzeros)); + std::copy(rows.begin(), rows.end(), tsm->mutable_rows()); + std::copy(cols.begin(), cols.end(), tsm->mutable_cols()); + std::copy(values.begin(), values.end(), tsm->mutable_values()); + tsm->set_num_nonzeros(values.size()); + + Matrix dense_from_tsm; + tsm->ToDenseMatrix(&dense_from_tsm); + ASSERT_TRUE((dense.array() == dense_from_tsm.array()).all()); + + crsm.reset(new CompressedRowSparseMatrix(*tsm)); + Matrix dense_from_crsm; + crsm->ToDenseMatrix(&dense_from_crsm); + ASSERT_TRUE((dense.array() == dense_from_crsm.array()).all()); + } + + void InsertNonZeroEntriesFromDenseReference() { + for (int r = 0; r < num_rows; ++r) { + for (int c = 0; c < num_cols; ++c) { + const double& v = dense(r, c); + if (v != 0.0) { + dcrsm->InsertEntry(r, c, v); + } + } + } + } + + void ExpectEmpty() { + EXPECT_EQ(dcrsm->num_rows(), num_rows); + EXPECT_EQ(dcrsm->num_cols(), num_cols); + EXPECT_EQ(dcrsm->num_nonzeros(), 0); + + Matrix dense_from_dcrsm; + dcrsm->ToDenseMatrix(&dense_from_dcrsm); + EXPECT_EQ(dense_from_dcrsm.rows(), num_rows); + EXPECT_EQ(dense_from_dcrsm.cols(), num_cols); + EXPECT_TRUE((dense_from_dcrsm.array() == 0.0).all()); + } + + void ExpectEqualToDenseReference() { + Matrix dense_from_dcrsm; + dcrsm->ToDenseMatrix(&dense_from_dcrsm); + EXPECT_TRUE((dense.array() == dense_from_dcrsm.array()).all()); + } + + void ExpectEqualToCompressedRowSparseMatrixReference() { + typedef Eigen::Map<const Eigen::VectorXi> ConstIntVectorRef; + + ConstIntVectorRef crsm_rows(crsm->rows(), crsm->num_rows() + 1); + ConstIntVectorRef dcrsm_rows(dcrsm->rows(), dcrsm->num_rows() + 1); + EXPECT_TRUE((crsm_rows.array() == dcrsm_rows.array()).all()); + + ConstIntVectorRef crsm_cols(crsm->cols(), crsm->num_nonzeros()); + ConstIntVectorRef dcrsm_cols(dcrsm->cols(), dcrsm->num_nonzeros()); + EXPECT_TRUE((crsm_cols.array() == dcrsm_cols.array()).all()); + + ConstVectorRef crsm_values(crsm->values(), crsm->num_nonzeros()); + ConstVectorRef dcrsm_values(dcrsm->values(), dcrsm->num_nonzeros()); + EXPECT_TRUE((crsm_values.array() == dcrsm_values.array()).all()); + } + + int num_rows; + int num_cols; + + int num_additional_elements; + + int expected_num_nonzeros; + + Matrix dense; + scoped_ptr<TripletSparseMatrix> tsm; + scoped_ptr<CompressedRowSparseMatrix> crsm; + + scoped_ptr<DynamicCompressedRowSparseMatrix> dcrsm; +}; + +TEST_F(DynamicCompressedRowSparseMatrixTest, Initialization) { + ExpectEmpty(); + + Finalize(); + ExpectEmpty(); +} + +TEST_F(DynamicCompressedRowSparseMatrixTest, InsertEntryAndFinalize) { + InsertNonZeroEntriesFromDenseReference(); + ExpectEmpty(); + + Finalize(); + ExpectEqualToDenseReference(); + ExpectEqualToCompressedRowSparseMatrixReference(); +} + +TEST_F(DynamicCompressedRowSparseMatrixTest, ClearRows) { + InsertNonZeroEntriesFromDenseReference(); + Finalize(); + ExpectEqualToDenseReference(); + ExpectEqualToCompressedRowSparseMatrixReference(); + + dcrsm->ClearRows(0, 0); + Finalize(); + ExpectEqualToDenseReference(); + ExpectEqualToCompressedRowSparseMatrixReference(); + + dcrsm->ClearRows(0, num_rows); + ExpectEqualToCompressedRowSparseMatrixReference(); + + Finalize(); + ExpectEmpty(); + + InsertNonZeroEntriesFromDenseReference(); + dcrsm->ClearRows(1, 2); + Finalize(); + dense.block(1, 0, 2, num_cols).setZero(); + ExpectEqualToDenseReference(); + + InitialiseDenseReference(); +} + +} // namespace internal +} // namespace ceres |