| // Ceres Solver - A fast non-linear least squares minimizer | |
| // Copyright 2010, 2011, 2012, 2013 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 | |
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| // INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN | |
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| // 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 "ceres/casts.h" | |
| #include "ceres/linear_least_squares_problems.h" | |
| #include "ceres/triplet_sparse_matrix.h" | |
| #include "ceres/internal/eigen.h" | |
| #include "ceres/internal/scoped_ptr.h" | |
| #include "glog/logging.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 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()); | |
| } | |
| 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); | |
| } | |
| } // namespace internal | |
| } // namespace ceres |