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// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2010, 2011, 2012 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
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// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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// POSSIBILITY OF SUCH DAMAGE.
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// Author: sameeragarwal@google.com (Sameer Agarwal)
#include <vector>
#include <glog/logging.h>
#include "gtest/gtest.h"
#include "ceres/block_random_access_sparse_matrix.h"
#include "ceres/internal/eigen.h"
namespace ceres {
namespace internal {
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(2, 0));
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 (set<pair<int, int> >::const_iterator it = block_pairs.begin();
it != block_pairs.end();
++it) {
const int row_block_id = it->first;
const int col_block_id = it->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 != NULL);
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);
// (2,0)
EXPECT_NEAR((dense.block(3 + 4, 0, 5, 3) - 3 * 1 * Matrix::Ones(5, 3)).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);
}
} // namespace internal
} // namespace ceres