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// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2022 Google Inc. All rights reserved.
// http://ceres-solver.org/
//
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// 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
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// Author: sameeragarwal@google.com (Sameer Agarwal)
#include "ceres/compressed_col_sparse_matrix_utils.h"
#include <algorithm>
#include <numeric>
#include <vector>
#include "Eigen/SparseCore"
#include "ceres/internal/export.h"
#include "ceres/triplet_sparse_matrix.h"
#include "glog/logging.h"
#include "gtest/gtest.h"
namespace ceres::internal {
TEST(_, BlockPermutationToScalarPermutation) {
// Block structure
// 0 --1- ---2--- ---3--- 4
// [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
std::vector<Block> blocks{{1, 0}, {2, 1}, {3, 3}, {3, 6}, {1, 9}};
// Block ordering
// [1, 0, 2, 4, 5]
std::vector<int> block_ordering{{1, 0, 2, 4, 3}};
// Expected ordering
// [1, 2, 0, 3, 4, 5, 9, 6, 7, 8]
std::vector<int> expected_scalar_ordering{{1, 2, 0, 3, 4, 5, 9, 6, 7, 8}};
std::vector<int> scalar_ordering;
BlockOrderingToScalarOrdering(blocks, block_ordering, &scalar_ordering);
EXPECT_EQ(scalar_ordering.size(), expected_scalar_ordering.size());
for (int i = 0; i < expected_scalar_ordering.size(); ++i) {
EXPECT_EQ(scalar_ordering[i], expected_scalar_ordering[i]);
}
}
static void FillBlock(const std::vector<Block>& row_blocks,
const std::vector<Block>& col_blocks,
const int row_block_id,
const int col_block_id,
std::vector<Eigen::Triplet<double>>* triplets) {
for (int r = 0; r < row_blocks[row_block_id].size; ++r) {
for (int c = 0; c < col_blocks[col_block_id].size; ++c) {
triplets->push_back(
Eigen::Triplet<double>(row_blocks[row_block_id].position + r,
col_blocks[col_block_id].position + c,
1.0));
}
}
}
TEST(_, ScalarMatrixToBlockMatrix) {
// Block sparsity.
//
// [1 2 3 2]
// [1] x x
// [2] x x
// [2] x x
// num_nonzeros = 1 + 3 + 4 + 4 + 1 + 2 = 15
std::vector<Block> col_blocks{{1, 0}, {2, 1}, {3, 3}, {2, 5}};
const int num_cols = NumScalarEntries(col_blocks);
std::vector<Block> row_blocks{{1, 0}, {2, 1}, {2, 3}};
const int num_rows = NumScalarEntries(row_blocks);
std::vector<Eigen::Triplet<double>> triplets;
FillBlock(row_blocks, col_blocks, 0, 0, &triplets);
FillBlock(row_blocks, col_blocks, 2, 0, &triplets);
FillBlock(row_blocks, col_blocks, 1, 1, &triplets);
FillBlock(row_blocks, col_blocks, 2, 1, &triplets);
FillBlock(row_blocks, col_blocks, 0, 2, &triplets);
FillBlock(row_blocks, col_blocks, 1, 3, &triplets);
Eigen::SparseMatrix<double> sparse_matrix(num_rows, num_cols);
sparse_matrix.setFromTriplets(triplets.begin(), triplets.end());
const std::vector<int> expected_compressed_block_rows{{0, 2, 1, 2, 0, 1}};
const std::vector<int> expected_compressed_block_cols{{0, 2, 4, 5, 6}};
std::vector<int> compressed_block_rows;
std::vector<int> compressed_block_cols;
CompressedColumnScalarMatrixToBlockMatrix(sparse_matrix.innerIndexPtr(),
sparse_matrix.outerIndexPtr(),
row_blocks,
col_blocks,
&compressed_block_rows,
&compressed_block_cols);
EXPECT_EQ(compressed_block_rows, expected_compressed_block_rows);
EXPECT_EQ(compressed_block_cols, expected_compressed_block_cols);
}
class SolveUpperTriangularTest : public ::testing::Test {
protected:
const std::vector<int>& cols() const { return cols_; }
const std::vector<int>& rows() const { return rows_; }
const std::vector<double>& values() const { return values_; }
private:
const std::vector<int> cols_ = {0, 1, 2, 4, 7};
const std::vector<int> rows_ = {0, 1, 1, 2, 0, 1, 3};
const std::vector<double> values_ = {
0.50754, 0.80483, 0.14120, 0.3, 0.77696, 0.41860, 0.88979};
};
TEST_F(SolveUpperTriangularTest, SolveInPlace) {
double rhs_and_solution[] = {1.0, 1.0, 2.0, 2.0};
const double expected[] = {-1.4706, -1.0962, 6.6667, 2.2477};
SolveUpperTriangularInPlace<int>(cols().size() - 1,
rows().data(),
cols().data(),
values().data(),
rhs_and_solution);
for (int i = 0; i < 4; ++i) {
EXPECT_NEAR(rhs_and_solution[i], expected[i], 1e-4) << i;
}
}
TEST_F(SolveUpperTriangularTest, TransposeSolveInPlace) {
double rhs_and_solution[] = {1.0, 1.0, 2.0, 2.0};
double expected[] = {1.970288, 1.242498, 6.081864, -0.057255};
SolveUpperTriangularTransposeInPlace<int>(cols().size() - 1,
rows().data(),
cols().data(),
values().data(),
rhs_and_solution);
for (int i = 0; i < 4; ++i) {
EXPECT_NEAR(rhs_and_solution[i], expected[i], 1e-4) << i;
}
}
TEST_F(SolveUpperTriangularTest, RTRSolveWithSparseRHS) {
double solution[4];
// clang-format off
double expected[] = { 6.8420e+00, 1.0057e+00, -1.4907e-16, -1.9335e+00,
1.0057e+00, 2.2275e+00, -1.9493e+00, -6.5693e-01,
-1.4907e-16, -1.9493e+00, 1.1111e+01, 9.7381e-17,
-1.9335e+00, -6.5693e-01, 9.7381e-17, 1.2631e+00 };
// clang-format on
for (int i = 0; i < 4; ++i) {
SolveRTRWithSparseRHS<int>(cols().size() - 1,
rows().data(),
cols().data(),
values().data(),
i,
solution);
for (int j = 0; j < 4; ++j) {
EXPECT_NEAR(solution[j], expected[4 * i + j], 1e-3) << i;
}
}
}
} // namespace ceres::internal