mirror of
https://github.com/ceres-solver/ceres-solver.git
synced 2026-08-29 16:40:38 +08:00
Sameer Agarwal
bcc865f81c
For historical reasons we had a "using namespace std;" in port.h. This is generally a bad idea. So removing it and along the way doing a bunch of cpplint cleanup. Change-Id: Ia125601a55ae62695e247fb0250df4c6f86c46c6
287 lines
8.7 KiB
C++
287 lines
8.7 KiB
C++
// Ceres Solver - A fast non-linear least squares minimizer
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// Copyright 2013 Google Inc. All rights reserved.
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// http://code.google.com/p/ceres-solver/
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//
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// Redistribution and use in source and binary forms, with or without
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// modification, are permitted provided that the following conditions are met:
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//
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// * Redistributions of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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// * Redistributions in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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// * Neither the name of Google Inc. nor the names of its contributors may be
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// used to endorse or promote products derived from this software without
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// specific prior written permission.
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//
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// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
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// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
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// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
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// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
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// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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// POSSIBILITY OF SUCH DAMAGE.
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//
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// Author: sameeragarwal@google.com (Sameer Agarwal)
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#include <algorithm>
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#include "ceres/compressed_col_sparse_matrix_utils.h"
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#include "ceres/internal/port.h"
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#include "ceres/suitesparse.h"
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#include "ceres/triplet_sparse_matrix.h"
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#include "glog/logging.h"
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#include "gtest/gtest.h"
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namespace ceres {
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namespace internal {
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using std::vector;
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TEST(_, BlockPermutationToScalarPermutation) {
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vector<int> blocks;
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// Block structure
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// 0 --1- ---2--- ---3--- 4
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// [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
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blocks.push_back(1);
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blocks.push_back(2);
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blocks.push_back(3);
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blocks.push_back(3);
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blocks.push_back(1);
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// Block ordering
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// [1, 0, 2, 4, 5]
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vector<int> block_ordering;
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block_ordering.push_back(1);
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block_ordering.push_back(0);
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block_ordering.push_back(2);
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block_ordering.push_back(4);
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block_ordering.push_back(3);
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// Expected ordering
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// [1, 2, 0, 3, 4, 5, 9, 6, 7, 8]
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vector<int> expected_scalar_ordering;
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expected_scalar_ordering.push_back(1);
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expected_scalar_ordering.push_back(2);
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expected_scalar_ordering.push_back(0);
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expected_scalar_ordering.push_back(3);
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expected_scalar_ordering.push_back(4);
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expected_scalar_ordering.push_back(5);
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expected_scalar_ordering.push_back(9);
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expected_scalar_ordering.push_back(6);
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expected_scalar_ordering.push_back(7);
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expected_scalar_ordering.push_back(8);
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vector<int> scalar_ordering;
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BlockOrderingToScalarOrdering(blocks,
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block_ordering,
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&scalar_ordering);
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EXPECT_EQ(scalar_ordering.size(), expected_scalar_ordering.size());
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for (int i = 0; i < expected_scalar_ordering.size(); ++i) {
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EXPECT_EQ(scalar_ordering[i], expected_scalar_ordering[i]);
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}
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}
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// Helper function to fill the sparsity pattern of a TripletSparseMatrix.
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int FillBlock(const vector<int>& row_blocks,
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const vector<int>& col_blocks,
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const int row_block_id,
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const int col_block_id,
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int* rows,
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int* cols) {
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int row_pos = 0;
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for (int i = 0; i < row_block_id; ++i) {
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row_pos += row_blocks[i];
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}
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int col_pos = 0;
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for (int i = 0; i < col_block_id; ++i) {
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col_pos += col_blocks[i];
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}
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int offset = 0;
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for (int r = 0; r < row_blocks[row_block_id]; ++r) {
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for (int c = 0; c < col_blocks[col_block_id]; ++c, ++offset) {
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rows[offset] = row_pos + r;
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cols[offset] = col_pos + c;
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}
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}
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return offset;
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}
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TEST(_, ScalarMatrixToBlockMatrix) {
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// Block sparsity.
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//
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// [1 2 3 2]
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// [1] x x
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// [2] x x
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// [2] x x
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// num_nonzeros = 1 + 3 + 4 + 4 + 1 + 2 = 15
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vector<int> col_blocks;
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col_blocks.push_back(1);
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col_blocks.push_back(2);
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col_blocks.push_back(3);
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col_blocks.push_back(2);
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vector<int> row_blocks;
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row_blocks.push_back(1);
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row_blocks.push_back(2);
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row_blocks.push_back(2);
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TripletSparseMatrix tsm(5, 8, 18);
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int* rows = tsm.mutable_rows();
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int* cols = tsm.mutable_cols();
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std::fill(tsm.mutable_values(), tsm.mutable_values() + 18, 1.0);
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int offset = 0;
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#define CERES_TEST_FILL_BLOCK(row_block_id, col_block_id) \
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offset += FillBlock(row_blocks, col_blocks, \
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row_block_id, col_block_id, \
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rows + offset, cols + offset);
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CERES_TEST_FILL_BLOCK(0, 0);
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CERES_TEST_FILL_BLOCK(2, 0);
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CERES_TEST_FILL_BLOCK(1, 1);
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CERES_TEST_FILL_BLOCK(2, 1);
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CERES_TEST_FILL_BLOCK(0, 2);
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CERES_TEST_FILL_BLOCK(1, 3);
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#undef CERES_TEST_FILL_BLOCK
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tsm.set_num_nonzeros(offset);
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SuiteSparse ss;
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scoped_ptr<cholmod_sparse> ccsm(ss.CreateSparseMatrix(&tsm));
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vector<int> expected_block_rows;
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expected_block_rows.push_back(0);
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expected_block_rows.push_back(2);
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expected_block_rows.push_back(1);
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expected_block_rows.push_back(2);
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expected_block_rows.push_back(0);
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expected_block_rows.push_back(1);
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vector<int> expected_block_cols;
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expected_block_cols.push_back(0);
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expected_block_cols.push_back(2);
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expected_block_cols.push_back(4);
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expected_block_cols.push_back(5);
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expected_block_cols.push_back(6);
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vector<int> block_rows;
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vector<int> block_cols;
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CompressedColumnScalarMatrixToBlockMatrix(
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reinterpret_cast<const int*>(ccsm->i),
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reinterpret_cast<const int*>(ccsm->p),
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row_blocks,
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col_blocks,
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&block_rows,
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&block_cols);
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EXPECT_EQ(block_cols.size(), expected_block_cols.size());
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EXPECT_EQ(block_rows.size(), expected_block_rows.size());
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for (int i = 0; i < expected_block_cols.size(); ++i) {
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EXPECT_EQ(block_cols[i], expected_block_cols[i]);
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}
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for (int i = 0; i < expected_block_rows.size(); ++i) {
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EXPECT_EQ(block_rows[i], expected_block_rows[i]);
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}
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ss.Free(ccsm.release());
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}
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class SolveUpperTriangularTest : public ::testing::Test {
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protected:
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void SetUp() {
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cols.resize(5);
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rows.resize(7);
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values.resize(7);
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cols[0] = 0;
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rows[0] = 0;
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values[0] = 0.50754;
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cols[1] = 1;
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rows[1] = 1;
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values[1] = 0.80483;
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cols[2] = 2;
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rows[2] = 1;
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values[2] = 0.14120;
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rows[3] = 2;
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values[3] = 0.3;
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cols[3] = 4;
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rows[4] = 0;
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values[4] = 0.77696;
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rows[5] = 1;
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values[5] = 0.41860;
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rows[6] = 3;
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values[6] = 0.88979;
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cols[4] = 7;
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}
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vector<int> cols;
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vector<int> rows;
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vector<double> values;
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};
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TEST_F(SolveUpperTriangularTest, SolveInPlace) {
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double rhs_and_solution[] = {1.0, 1.0, 2.0, 2.0};
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const double expected[] = { -1.4706, -1.0962, 6.6667, 2.2477};
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SolveUpperTriangularInPlace<int>(cols.size() - 1,
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&rows[0],
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&cols[0],
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&values[0],
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rhs_and_solution);
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for (int i = 0; i < 4; ++i) {
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EXPECT_NEAR(rhs_and_solution[i], expected[i], 1e-4) << i;
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}
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}
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TEST_F(SolveUpperTriangularTest, TransposeSolveInPlace) {
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double rhs_and_solution[] = {1.0, 1.0, 2.0, 2.0};
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double expected[] = {1.970288, 1.242498, 6.081864, -0.057255};
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SolveUpperTriangularTransposeInPlace<int>(cols.size() - 1,
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&rows[0],
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&cols[0],
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&values[0],
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rhs_and_solution);
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for (int i = 0; i < 4; ++i) {
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EXPECT_NEAR(rhs_and_solution[i], expected[i], 1e-4) << i;
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}
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}
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TEST_F(SolveUpperTriangularTest, RTRSolveWithSparseRHS) {
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double solution[4];
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double expected[] = { 6.8420e+00, 1.0057e+00, -1.4907e-16, -1.9335e+00,
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1.0057e+00, 2.2275e+00, -1.9493e+00, -6.5693e-01,
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-1.4907e-16, -1.9493e+00, 1.1111e+01, 9.7381e-17,
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-1.9335e+00, -6.5693e-01, 9.7381e-17, 1.2631e+00 };
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for (int i = 0; i < 4; ++i) {
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SolveRTRWithSparseRHS<int>(cols.size() - 1,
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&rows[0],
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&cols[0],
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&values[0],
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i,
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solution);
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for (int j = 0; j < 4; ++j) {
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EXPECT_NEAR(solution[j], expected[4 * i + j], 1e-3) << i;
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}
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}
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}
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} // namespace internal
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} // namespace ceres
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