| // Ceres Solver - A fast non-linear least squares minimizer |
| // Copyright 2015 Google Inc. All rights reserved. |
| // http://ceres-solver.org/ |
| // |
| // Redistribution and use in source and binary forms, with or without |
| // modification, are permitted provided that the following conditions are met: |
| // |
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| // 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 |
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| // 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 |
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| // |
| // Author: richie.stebbing@gmail.com (Richard Stebbing) |
| |
| #include "ceres/dynamic_compressed_row_sparse_matrix.h" |
| |
| #include <memory> |
| #include "ceres/casts.h" |
| #include "ceres/compressed_row_sparse_matrix.h" |
| #include "ceres/internal/eigen.h" |
| #include "ceres/linear_least_squares_problems.h" |
| #include "ceres/triplet_sparse_matrix.h" |
| #include "gtest/gtest.h" |
| |
| namespace ceres { |
| namespace internal { |
| |
| using std::copy; |
| using std::vector; |
| |
| class DynamicCompressedRowSparseMatrixTest : public ::testing::Test { |
| protected: |
| void SetUp() final { |
| 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 - std::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() { |
| vector<int> rows, cols; |
| 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)); |
| copy(rows.begin(), rows.end(), tsm->mutable_rows()); |
| copy(cols.begin(), cols.end(), tsm->mutable_cols()); |
| 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(CompressedRowSparseMatrix::FromTripletSparseMatrix(*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; |
| std::unique_ptr<TripletSparseMatrix> tsm; |
| std::unique_ptr<CompressedRowSparseMatrix> crsm; |
| |
| std::unique_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 |