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Diffstat (limited to 'internal/ceres/dense_sparse_matrix_test.cc')
-rw-r--r-- | internal/ceres/dense_sparse_matrix_test.cc | 232 |
1 files changed, 232 insertions, 0 deletions
diff --git a/internal/ceres/dense_sparse_matrix_test.cc b/internal/ceres/dense_sparse_matrix_test.cc new file mode 100644 index 0000000..354357f --- /dev/null +++ b/internal/ceres/dense_sparse_matrix_test.cc @@ -0,0 +1,232 @@ +// 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: keir@google.com (Keir Mierle) +// +// TODO(keir): Implement a generic "compare sparse matrix implementations" test +// suite that can compare all the implementations. Then this file would shrink +// in size. + +#include "ceres/dense_sparse_matrix.h" + +#include "gtest/gtest.h" +#include "ceres/casts.h" +#include "ceres/linear_least_squares_problems.h" +#include "ceres/matrix_proto.h" +#include "ceres/triplet_sparse_matrix.h" +#include "ceres/internal/eigen.h" +#include "ceres/internal/scoped_ptr.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 DenseSparseMatrixTest : 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())); + dsm.reset(new DenseSparseMatrix(*tsm)); + + num_rows = tsm->num_rows(); + num_cols = tsm->num_cols(); + } + + int num_rows; + int num_cols; + + scoped_ptr<TripletSparseMatrix> tsm; + scoped_ptr<DenseSparseMatrix> dsm; +}; + +TEST_F(DenseSparseMatrixTest, RightMultiply) { + CompareMatrices(tsm.get(), dsm.get()); + + // Try with a not entirely zero vector to verify column interactions, which + // could be masked by a subtle bug when using the elementary vectors. + Vector a(num_cols); + for (int i = 0; i < num_cols; i++) { + a(i) = i; + } + Vector b1 = Vector::Zero(num_rows); + Vector b2 = Vector::Zero(num_rows); + + tsm->RightMultiply(a.data(), b1.data()); + dsm->RightMultiply(a.data(), b2.data()); + + EXPECT_EQ((b1 - b2).norm(), 0); +} + +TEST_F(DenseSparseMatrixTest, 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()); + dsm->LeftMultiply(a.data(), b2.data()); + + EXPECT_EQ((b1 - b2).norm(), 0); + } + + // Try with a not entirely zero vector to verify column interactions, which + // could be masked by a subtle bug when using the elementary vectors. + Vector a(num_rows); + for (int i = 0; i < num_rows; i++) { + a(i) = i; + } + Vector b1 = Vector::Zero(num_cols); + Vector b2 = Vector::Zero(num_cols); + + tsm->LeftMultiply(a.data(), b1.data()); + dsm->LeftMultiply(a.data(), b2.data()); + + EXPECT_EQ((b1 - b2).norm(), 0); +} + +TEST_F(DenseSparseMatrixTest, ColumnNorm) { + Vector b1 = Vector::Zero(num_cols); + Vector b2 = Vector::Zero(num_cols); + + tsm->SquaredColumnNorm(b1.data()); + dsm->SquaredColumnNorm(b2.data()); + + EXPECT_EQ((b1 - b2).norm(), 0); +} + +TEST_F(DenseSparseMatrixTest, Scale) { + Vector scale(num_cols); + for (int i = 0; i < num_cols; ++i) { + scale(i) = i + 1; + } + tsm->ScaleColumns(scale.data()); + dsm->ScaleColumns(scale.data()); + CompareMatrices(tsm.get(), dsm.get()); +} + +#ifndef CERES_NO_PROTOCOL_BUFFERS +TEST_F(DenseSparseMatrixTest, Serialization) { + SparseMatrixProto proto; + dsm->ToProto(&proto); + + DenseSparseMatrix n(proto); + ASSERT_EQ(dsm->num_rows(), n.num_rows()); + ASSERT_EQ(dsm->num_cols(), n.num_cols()); + ASSERT_EQ(dsm->num_nonzeros(), n.num_nonzeros()); + + for (int i = 0; i < n.num_rows() + 1; ++i) { + ASSERT_EQ(dsm->values()[i], proto.dense_matrix().values(i)); + } +} +#endif + +TEST_F(DenseSparseMatrixTest, ToDenseMatrix) { + Matrix tsm_dense; + Matrix dsm_dense; + + tsm->ToDenseMatrix(&tsm_dense); + dsm->ToDenseMatrix(&dsm_dense); + + EXPECT_EQ((tsm_dense - dsm_dense).norm(), 0.0); +} + +// TODO(keir): Make this work without protocol buffers. +#ifndef CERES_NO_PROTOCOL_BUFFERS +TEST_F(DenseSparseMatrixTest, AppendDiagonal) { + DenseSparseMatrixProto proto; + proto.set_num_rows(3); + proto.set_num_cols(3); + for (int i = 0; i < 9; ++i) { + proto.add_values(i); + } + SparseMatrixProto outer_proto; + *outer_proto.mutable_dense_matrix() = proto; + + DenseSparseMatrix dsm(outer_proto); + + double diagonal[] = { 10, 11, 12 }; + dsm.AppendDiagonal(diagonal); + + // Verify the diagonal got added. + Matrix m = dsm.matrix(); + EXPECT_EQ(6, m.rows()); + EXPECT_EQ(3, m.cols()); + for (int i = 0; i < 3; ++i) { + for (int j = 0; j < 3; ++j) { + EXPECT_EQ(3 * i + j, m(i, j)); + if (i == j) { + EXPECT_EQ(10 + i, m(i + 3, j)); + } else { + EXPECT_EQ(0, m(i + 3, j)); + } + } + } + + // Verify the diagonal gets removed. + dsm.RemoveDiagonal(); + m = dsm.matrix(); + + EXPECT_EQ(3, m.rows()); + EXPECT_EQ(3, m.cols()); + + for (int i = 0; i < 3; ++i) { + for (int j = 0; j < 3; ++j) { + EXPECT_EQ(3 * i + j, m(i, j)); + } + } +} +#endif + +} // namespace internal +} // namespace ceres |