// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 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
// 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
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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: sameeragarwal@google.com (Sameer Agarwal)
#include <algorithm>
#include "ceres/compressed_col_sparse_matrix_utils.h"
#include "ceres/internal/port.h"
#include "ceres/suitesparse.h"
#include "ceres/triplet_sparse_matrix.h"
#include "glog/logging.h"
#include "gtest/gtest.h"
namespace ceres {
namespace internal {
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]);
}
}
// Helper function to fill the sparsity pattern of a TripletSparseMatrix.
int FillBlock(const vector<int>& row_blocks,
const vector<int>& col_blocks,
const int row_block_id,
const int col_block_id,
int* rows,
int* cols) {
int row_pos = 0;
for (int i = 0; i < row_block_id; ++i) {
row_pos += row_blocks[i];
}
int col_pos = 0;
for (int i = 0; i < col_block_id; ++i) {
col_pos += col_blocks[i];
}
int offset = 0;
for (int r = 0; r < row_blocks[row_block_id]; ++r) {
for (int c = 0; c < col_blocks[col_block_id]; ++c, ++offset) {
rows[offset] = row_pos + r;
cols[offset] = col_pos + c;
}
}
return offset;
}
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);
TripletSparseMatrix tsm(5, 8, 18);
int* rows = tsm.mutable_rows();
int* cols = tsm.mutable_cols();
fill(tsm.mutable_values(), tsm.mutable_values() + 18, 1.0);
int offset = 0;
#define CERES_TEST_FILL_BLOCK(row_block_id, col_block_id) \
offset += FillBlock(row_blocks, col_blocks, \
row_block_id, col_block_id, \
rows + offset, cols + offset);
CERES_TEST_FILL_BLOCK(0, 0);
CERES_TEST_FILL_BLOCK(2, 0);
CERES_TEST_FILL_BLOCK(1, 1);
CERES_TEST_FILL_BLOCK(2, 1);
CERES_TEST_FILL_BLOCK(0, 2);
CERES_TEST_FILL_BLOCK(1, 3);
#undef CERES_TEST_FILL_BLOCK
tsm.set_num_nonzeros(offset);
SuiteSparse ss;
scoped_ptr<cholmod_sparse> ccsm(ss.CreateSparseMatrix(&tsm));
vector<int> expected_block_rows;
expected_block_rows.push_back(0);
expected_block_rows.push_back(2);
expected_block_rows.push_back(1);
expected_block_rows.push_back(2);
expected_block_rows.push_back(0);
expected_block_rows.push_back(1);
vector<int> expected_block_cols;
expected_block_cols.push_back(0);
expected_block_cols.push_back(2);
expected_block_cols.push_back(4);
expected_block_cols.push_back(5);
expected_block_cols.push_back(6);
vector<int> block_rows;
vector<int> block_cols;
CompressedColumnScalarMatrixToBlockMatrix(
reinterpret_cast<const int*>(ccsm->i),
reinterpret_cast<const int*>(ccsm->p),
row_blocks,
col_blocks,
&block_rows,
&block_cols);
EXPECT_EQ(block_cols.size(), expected_block_cols.size());
EXPECT_EQ(block_rows.size(), expected_block_rows.size());
for (int i = 0; i < expected_block_cols.size(); ++i) {
EXPECT_EQ(block_cols[i], expected_block_cols[i]);
}
for (int i = 0; i < expected_block_rows.size(); ++i) {
EXPECT_EQ(block_rows[i], expected_block_rows[i]);
}
ss.Free(ccsm.release());
}
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