Block ordering for SPARSE_SCHUR + CX_SPARSE.
Uptil now only SuiteSparse when used with SPARSE_SCHUR would use
the block structure of the reduced camera matrix to find a fill-reducing
ordering.
This leads to substantial speedup for some bundle adjustment
problems.
Credit for this technique goes to the authors of g2o. I learned
about it from reading their source code.
Change-Id: I5403efefd4d9552c9c6fc6e02a65498bdf171584
diff --git a/internal/ceres/compressed_col_sparse_matrix_utils_test.cc b/internal/ceres/compressed_col_sparse_matrix_utils_test.cc
new file mode 100644
index 0000000..7efa0e3
--- /dev/null
+++ b/internal/ceres/compressed_col_sparse_matrix_utils_test.cc
@@ -0,0 +1,196 @@
+// 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
+// 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 <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());
+}
+
+} // namespace internal
+} // namespace ceres
