// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2015 Google Inc. All rights reserved.
// http://ceres-solver.org/
//
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// 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
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// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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// Author: sameeragarwal@google.com (Sameer Agarwal)
#include <algorithm>
#include <numeric>
#include "ceres/compressed_col_sparse_matrix_utils.h"
#include "ceres/internal/port.h"
#include "ceres/triplet_sparse_matrix.h"
#include "glog/logging.h"
#include "gtest/gtest.h"
#include "Eigen/SparseCore"
namespace ceres {
namespace internal {
using std::vector;
TEST(_, BlockPermutationToScalarPermutation) {
vector<int> blocks;
// Block structure
// 0 --1- ---2--- ---3--- 4
// [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
blocks.push_back(1);
blocks.push_back(2);
blocks.push_back(3);
blocks.push_back(3);
blocks.push_back(1);
// Block ordering
// [1, 0, 2, 4, 5]
vector<int> block_ordering;
block_ordering.push_back(1);
block_ordering.push_back(0);
block_ordering.push_back(2);
block_ordering.push_back(4);
block_ordering.push_back(3);
// Expected ordering
// [1, 2, 0, 3, 4, 5, 9, 6, 7, 8]
vector<int> expected_scalar_ordering;
expected_scalar_ordering.push_back(1);
expected_scalar_ordering.push_back(2);
expected_scalar_ordering.push_back(0);
expected_scalar_ordering.push_back(3);
expected_scalar_ordering.push_back(4);
expected_scalar_ordering.push_back(5);
expected_scalar_ordering.push_back(9);
expected_scalar_ordering.push_back(6);
expected_scalar_ordering.push_back(7);
expected_scalar_ordering.push_back(8);
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]);
}
}
void FillBlock(const vector<int>& row_blocks,
const vector<int>& col_blocks,
const int row_block_id,
const int col_block_id,
vector<Eigen::Triplet<double> >* triplets) {
const int row_offset = std::accumulate(&row_blocks[0], &row_blocks[row_block_id], 0);
const int col_offset = std::accumulate(&col_blocks[0], &col_blocks[col_block_id], 0);
for (int r = 0; r < row_blocks[row_block_id]; ++r) {
for (int c = 0; c < col_blocks[col_block_id]; ++c) {
triplets->push_back(Eigen::Triplet<double>(row_offset + r, col_offset + 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
vector<int> col_blocks;
col_blocks.push_back(1);
col_blocks.push_back(2);
col_blocks.push_back(3);
col_blocks.push_back(2);
vector<int> row_blocks;
row_blocks.push_back(1);
row_blocks.push_back(2);
row_blocks.push_back(2);
const int num_rows = std::accumulate(row_blocks.begin(), row_blocks.end(), 0.0);
const int num_cols = std::accumulate(col_blocks.begin(), col_blocks.end(), 0.0);
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());
vector<int> expected_compressed_block_rows;
expected_compressed_block_rows.push_back(0);
expected_compressed_block_rows.push_back(2);
expected_compressed_block_rows.push_back(1);
expected_compressed_block_rows.push_back(2);
expected_compressed_block_rows.push_back(0);
expected_compressed_block_rows.push_back(1);
vector<int> expected_compressed_block_cols;
expected_compressed_block_cols.push_back(0);
expected_compressed_block_cols.push_back(2);
expected_compressed_block_cols.push_back(4);
expected_compressed_block_cols.push_back(5);
expected_compressed_block_cols.push_back(6);
vector<int> compressed_block_rows;
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:
void SetUp() {
cols.resize(5);
rows.resize(7);
values.resize(7);
cols[0] = 0;
rows[0] = 0;
values[0] = 0.50754;
cols[1] = 1;
rows[1] = 1;
values[1] = 0.80483;
cols[2] = 2;
rows[2] = 1;
values[2] = 0.14120;
rows[3] = 2;
values[3] = 0.3;
cols[3] = 4;
rows[4] = 0;
values[4] = 0.77696;
rows[5] = 1;
values[5] = 0.41860;
rows[6] = 3;
values[6] = 0.88979;
cols[4] = 7;
}
vector<int> cols;
vector<int> rows;
vector<double> values;
};
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[0],
&cols[0],
&values[0],
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[0],
&cols[0],
&values[0],
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];
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 };
for (int i = 0; i < 4; ++i) {
SolveRTRWithSparseRHS<int>(cols.size() - 1,
&rows[0],
&cols[0],
&values[0],
i,
solution);
for (int j = 0; j < 4; ++j) {
EXPECT_NEAR(solution[j], expected[4 * i + j], 1e-3) << i;
}
}
}
} // namespace internal
} // namespace ceres