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// 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:
//
// * 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: sameeragarwal@google.com (Sameer Agarwal)
#include "ceres/block_random_access_sparse_matrix.h"
#include <limits>
#include <memory>
#include <vector>
#include "ceres/internal/eigen.h"
#include "glog/logging.h"
#include "gtest/gtest.h"
namespace ceres {
namespace internal {
using std::make_pair;
using std::pair;
using std::set;
using std::vector;
TEST(BlockRandomAccessSparseMatrix, GetCell) {
vector<int> blocks;
blocks.push_back(3);
blocks.push_back(4);
blocks.push_back(5);
const int num_rows = 3 + 4 + 5;
set<pair<int, int>> block_pairs;
int num_nonzeros = 0;
block_pairs.insert(make_pair(0, 0));
num_nonzeros += blocks[0] * blocks[0];
block_pairs.insert(make_pair(1, 1));
num_nonzeros += blocks[1] * blocks[1];
block_pairs.insert(make_pair(1, 2));
num_nonzeros += blocks[1] * blocks[2];
block_pairs.insert(make_pair(0, 2));
num_nonzeros += blocks[2] * blocks[0];
BlockRandomAccessSparseMatrix m(blocks, block_pairs);
EXPECT_EQ(m.num_rows(), num_rows);
EXPECT_EQ(m.num_cols(), num_rows);
for (const auto& block_pair : block_pairs) {
const int row_block_id = block_pair.first;
const int col_block_id = block_pair.second;
int row;
int col;
int row_stride;
int col_stride;
CellInfo* cell = m.GetCell(
row_block_id, col_block_id, &row, &col, &row_stride, &col_stride);
EXPECT_TRUE(cell != nullptr);
EXPECT_EQ(row, 0);
EXPECT_EQ(col, 0);
EXPECT_EQ(row_stride, blocks[row_block_id]);
EXPECT_EQ(col_stride, blocks[col_block_id]);
// Write into the block
MatrixRef(cell->values, row_stride, col_stride)
.block(row, col, blocks[row_block_id], blocks[col_block_id]) =
(row_block_id + 1) * (col_block_id + 1) *
Matrix::Ones(blocks[row_block_id], blocks[col_block_id]);
}
const TripletSparseMatrix* tsm = m.matrix();
EXPECT_EQ(tsm->num_nonzeros(), num_nonzeros);
EXPECT_EQ(tsm->max_num_nonzeros(), num_nonzeros);
Matrix dense;
tsm->ToDenseMatrix(&dense);
double kTolerance = 1e-14;
// (0, 0)
EXPECT_NEAR(
(dense.block(0, 0, 3, 3) - Matrix::Ones(3, 3)).norm(), 0.0, kTolerance);
// (1, 1)
EXPECT_NEAR((dense.block(3, 3, 4, 4) - 2 * 2 * Matrix::Ones(4, 4)).norm(),
0.0,
kTolerance);
// (1, 2)
EXPECT_NEAR((dense.block(3, 3 + 4, 4, 5) - 2 * 3 * Matrix::Ones(4, 5)).norm(),
0.0,
kTolerance);
// (0, 2)
EXPECT_NEAR((dense.block(0, 3 + 4, 3, 5) - 3 * 1 * Matrix::Ones(3, 5)).norm(),
0.0,
kTolerance);
// There is nothing else in the matrix besides these four blocks.
EXPECT_NEAR(
dense.norm(), sqrt(9. + 16. * 16. + 36. * 20. + 9. * 15.), kTolerance);
Vector x = Vector::Ones(dense.rows());
Vector actual_y = Vector::Zero(dense.rows());
Vector expected_y = Vector::Zero(dense.rows());
expected_y += dense.selfadjointView<Eigen::Upper>() * x;
m.SymmetricRightMultiply(x.data(), actual_y.data());
EXPECT_NEAR((expected_y - actual_y).norm(), 0.0, kTolerance)
<< "actual: " << actual_y.transpose() << "\n"
<< "expected: " << expected_y.transpose() << "matrix: \n " << dense;
}
// IntPairToLong is private, thus this fixture is needed to access and
// test it.
class BlockRandomAccessSparseMatrixTest : public ::testing::Test {
public:
void SetUp() final {
vector<int> blocks;
blocks.push_back(1);
set<pair<int, int>> block_pairs;
block_pairs.insert(make_pair(0, 0));
m_ = std::make_unique<BlockRandomAccessSparseMatrix>(blocks, block_pairs);
}
void CheckIntPairToLong(int a, int b) {
int64_t value = m_->IntPairToLong(a, b);
EXPECT_GT(value, 0) << "Overflow a = " << a << " b = " << b;
EXPECT_GT(value, a) << "Overflow a = " << a << " b = " << b;
EXPECT_GT(value, b) << "Overflow a = " << a << " b = " << b;
}
void CheckLongToIntPair() {
uint64_t max_rows = m_->kMaxRowBlocks;
for (int row = max_rows - 10; row < max_rows; ++row) {
for (int col = 0; col < 10; ++col) {
int row_computed;
int col_computed;
m_->LongToIntPair(
m_->IntPairToLong(row, col), &row_computed, &col_computed);
EXPECT_EQ(row, row_computed);
EXPECT_EQ(col, col_computed);
}
}
}
private:
std::unique_ptr<BlockRandomAccessSparseMatrix> m_;
};
TEST_F(BlockRandomAccessSparseMatrixTest, IntPairToLongOverflow) {
CheckIntPairToLong(std::numeric_limits<int>::max(),
std::numeric_limits<int>::max());
}
TEST_F(BlockRandomAccessSparseMatrixTest, LongToIntPair) {
CheckLongToIntPair();
}
} // namespace internal
} // namespace ceres
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