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Diffstat (limited to 'internal/ceres/compressed_row_sparse_matrix_test.cc')
-rw-r--r-- | internal/ceres/compressed_row_sparse_matrix_test.cc | 203 |
1 files changed, 203 insertions, 0 deletions
diff --git a/internal/ceres/compressed_row_sparse_matrix_test.cc b/internal/ceres/compressed_row_sparse_matrix_test.cc new file mode 100644 index 0000000..c9c3f14 --- /dev/null +++ b/internal/ceres/compressed_row_sparse_matrix_test.cc @@ -0,0 +1,203 @@ +// 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/compressed_row_sparse_matrix.h" + +#include "ceres/casts.h" +#include "ceres/crs_matrix.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 "gtest/gtest.h" + +namespace ceres { +namespace internal { + +void CompareMatrices(const SparseMatrix* a, const SparseMatrix* b) { + EXPECT_EQ(a->num_rows(), b->num_rows()); + EXPECT_EQ(a->num_cols(), b->num_cols()); + + int num_rows = a->num_rows(); + int num_cols = a->num_cols(); + + for (int i = 0; i < num_cols; ++i) { + Vector x = Vector::Zero(num_cols); + x(i) = 1.0; + + Vector y_a = Vector::Zero(num_rows); + Vector y_b = Vector::Zero(num_rows); + + a->RightMultiply(x.data(), y_a.data()); + b->RightMultiply(x.data(), y_b.data()); + + EXPECT_EQ((y_a - y_b).norm(), 0); + } +} + +class CompressedRowSparseMatrixTest : public ::testing::Test { + protected : + virtual void SetUp() { + scoped_ptr<LinearLeastSquaresProblem> problem( + CreateLinearLeastSquaresProblemFromId(1)); + + CHECK_NOTNULL(problem.get()); + + tsm.reset(down_cast<TripletSparseMatrix*>(problem->A.release())); + crsm.reset(new CompressedRowSparseMatrix(*tsm)); + + num_rows = tsm->num_rows(); + num_cols = tsm->num_cols(); + } + + int num_rows; + int num_cols; + + scoped_ptr<TripletSparseMatrix> tsm; + scoped_ptr<CompressedRowSparseMatrix> crsm; +}; + +TEST_F(CompressedRowSparseMatrixTest, RightMultiply) { + CompareMatrices(tsm.get(), crsm.get()); +} + +TEST_F(CompressedRowSparseMatrixTest, LeftMultiply) { + for (int i = 0; i < num_rows; ++i) { + Vector a = Vector::Zero(num_rows); + a(i) = 1.0; + + Vector b1 = Vector::Zero(num_cols); + Vector b2 = Vector::Zero(num_cols); + + tsm->LeftMultiply(a.data(), b1.data()); + crsm->LeftMultiply(a.data(), b2.data()); + + EXPECT_EQ((b1 - b2).norm(), 0); + } +} + +TEST_F(CompressedRowSparseMatrixTest, ColumnNorm) { + Vector b1 = Vector::Zero(num_cols); + Vector b2 = Vector::Zero(num_cols); + + tsm->SquaredColumnNorm(b1.data()); + crsm->SquaredColumnNorm(b2.data()); + + EXPECT_EQ((b1 - b2).norm(), 0); +} + +TEST_F(CompressedRowSparseMatrixTest, Scale) { + Vector scale(num_cols); + for (int i = 0; i < num_cols; ++i) { + scale(i) = i + 1; + } + + tsm->ScaleColumns(scale.data()); + crsm->ScaleColumns(scale.data()); + CompareMatrices(tsm.get(), crsm.get()); +} + +TEST_F(CompressedRowSparseMatrixTest, DeleteRows) { + for (int i = 0; i < num_rows; ++i) { + tsm->Resize(num_rows - i, num_cols); + crsm->DeleteRows(crsm->num_rows() - tsm->num_rows()); + CompareMatrices(tsm.get(), crsm.get()); + } +} + +TEST_F(CompressedRowSparseMatrixTest, AppendRows) { + for (int i = 0; i < num_rows; ++i) { + TripletSparseMatrix tsm_appendage(*tsm); + tsm_appendage.Resize(i, num_cols); + + tsm->AppendRows(tsm_appendage); + CompressedRowSparseMatrix crsm_appendage(tsm_appendage); + crsm->AppendRows(crsm_appendage); + + CompareMatrices(tsm.get(), crsm.get()); + } +} + +#ifndef CERES_NO_PROTOCOL_BUFFERS +TEST_F(CompressedRowSparseMatrixTest, Serialization) { + SparseMatrixProto proto; + crsm->ToProto(&proto); + + CompressedRowSparseMatrix n(proto); + ASSERT_EQ(n.num_rows(), crsm->num_rows()); + ASSERT_EQ(n.num_cols(), crsm->num_cols()); + ASSERT_EQ(n.num_nonzeros(), crsm->num_nonzeros()); + + for (int i = 0; i < n.num_rows() + 1; ++i) { + ASSERT_EQ(crsm->rows()[i], proto.compressed_row_matrix().rows(i)); + ASSERT_EQ(crsm->rows()[i], n.rows()[i]); + } + + for (int i = 0; i < crsm->num_nonzeros(); ++i) { + ASSERT_EQ(crsm->cols()[i], proto.compressed_row_matrix().cols(i)); + ASSERT_EQ(crsm->cols()[i], n.cols()[i]); + ASSERT_EQ(crsm->values()[i], proto.compressed_row_matrix().values(i)); + ASSERT_EQ(crsm->values()[i], n.values()[i]); + } +} +#endif + +TEST_F(CompressedRowSparseMatrixTest, ToDenseMatrix) { + Matrix tsm_dense; + Matrix crsm_dense; + + tsm->ToDenseMatrix(&tsm_dense); + crsm->ToDenseMatrix(&crsm_dense); + + EXPECT_EQ((tsm_dense - crsm_dense).norm(), 0.0); +} + +TEST_F(CompressedRowSparseMatrixTest, ToCRSMatrix) { + CRSMatrix crs_matrix; + crsm->ToCRSMatrix(&crs_matrix); + EXPECT_EQ(crsm->num_rows(), crs_matrix.num_rows); + EXPECT_EQ(crsm->num_cols(), crs_matrix.num_cols); + EXPECT_EQ(crsm->num_rows() + 1, crs_matrix.rows.size()); + EXPECT_EQ(crsm->num_nonzeros(), crs_matrix.cols.size()); + EXPECT_EQ(crsm->num_nonzeros(), crs_matrix.values.size()); + + for (int i = 0; i < crsm->num_rows() + 1; ++i) { + EXPECT_EQ(crsm->rows()[i], crs_matrix.rows[i]); + } + + for (int i = 0; i < crsm->num_nonzeros(); ++i) { + EXPECT_EQ(crsm->cols()[i], crs_matrix.cols[i]); + EXPECT_EQ(crsm->values()[i], crs_matrix.values[i]); + } +} + +} // namespace internal +} // namespace ceres |