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// Ceres Solver - A fast non-linear least squares minimizer
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// Copyright 2010, 2011, 2012 Google Inc. All rights reserved.
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// http://code.google.com/p/ceres-solver/
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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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// * 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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// 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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// Author: keir@google.com (Keir Mierle)
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#include "ceres/compressed_row_jacobian_writer.h"
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#include "ceres/casts.h"
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#include "ceres/compressed_row_sparse_matrix.h"
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#include "ceres/parameter_block.h"
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#include "ceres/program.h"
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#include "ceres/residual_block.h"
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#include "ceres/scratch_evaluate_preparer.h"
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SparseMatrix* CompressedRowJacobianWriter::CreateJacobian() const {
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const vector<ResidualBlock*>& residual_blocks =
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program_->residual_blocks();
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int total_num_residuals = program_->NumResiduals();
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int total_num_effective_parameters = program_->NumEffectiveParameters();
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// Count the number of jacobian nonzeros.
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int num_jacobian_nonzeros = 0;
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for (int i = 0; i < residual_blocks.size(); ++i) {
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ResidualBlock* residual_block = residual_blocks[i];
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const int num_residuals = residual_block->NumResiduals();
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const int num_parameter_blocks = residual_block->NumParameterBlocks();
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for (int j = 0; j < num_parameter_blocks; ++j) {
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ParameterBlock* parameter_block = residual_block->parameter_blocks()[j];
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if (!parameter_block->IsConstant()) {
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num_jacobian_nonzeros += num_residuals * parameter_block->LocalSize();
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// Allocate storage for the jacobian with some extra space at the end.
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// Allocate more space than needed to store the jacobian so that when the LM
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// algorithm adds the diagonal, no reallocation is necessary. This reduces
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// peak memory usage significantly.
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CompressedRowSparseMatrix* jacobian =
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new CompressedRowSparseMatrix(
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total_num_effective_parameters,
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num_jacobian_nonzeros + total_num_effective_parameters);
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// At this stage, the CompressedSparseMatrix is an invalid state. But this
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// seems to be the only way to construct it without doing a memory copy.
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int* rows = jacobian->mutable_rows();
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int* cols = jacobian->mutable_cols();
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for (int i = 0; i < residual_blocks.size(); ++i) {
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const ResidualBlock* residual_block = residual_blocks[i];
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const int num_parameter_blocks = residual_block->NumParameterBlocks();
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// Count the number of derivatives for a row of this residual block and
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// build a list of active parameter block indices.
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int num_derivatives = 0;
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vector<int> parameter_indices;
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for (int j = 0; j < num_parameter_blocks; ++j) {
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ParameterBlock* parameter_block = residual_block->parameter_blocks()[j];
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if (!parameter_block->IsConstant()) {
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parameter_indices.push_back(parameter_block->index());
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num_derivatives += parameter_block->LocalSize();
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// Sort the parameters by their position in the state vector.
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sort(parameter_indices.begin(), parameter_indices.end());
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CHECK(unique(parameter_indices.begin(), parameter_indices.end()) ==
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parameter_indices.end())
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<< "Ceres internal error: "
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<< "Duplicate parameter blocks detected in a cost function. "
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<< "This should never happen. Please report this to "
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<< "the Ceres developers.";
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// Update the row indices.
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const int num_residuals = residual_block->NumResiduals();
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for (int j = 0; j < num_residuals; ++j) {
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rows[row_pos + j + 1] = rows[row_pos + j] + num_derivatives;
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// Iterate over parameter blocks in the order which they occur in the
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// parameter vector. This code mirrors that in Write(), where jacobian
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// values are updated.
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for (int j = 0; j < parameter_indices.size(); ++j) {
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ParameterBlock* parameter_block =
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program_->parameter_blocks()[parameter_indices[j]];
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const int parameter_block_size = parameter_block->LocalSize();
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for (int r = 0; r < num_residuals; ++r) {
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// This is the position in the values array of the jacobian where this
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// row of the jacobian block should go.
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const int column_block_begin = rows[row_pos + r] + col_pos;
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for (int c = 0; c < parameter_block_size; ++c) {
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cols[column_block_begin + c] = parameter_block->delta_offset() + c;
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col_pos += parameter_block_size;
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row_pos += num_residuals;
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CHECK_EQ(num_jacobian_nonzeros, rows[total_num_residuals]);
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void CompressedRowJacobianWriter::Write(int residual_id,
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SparseMatrix* base_jacobian) {
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CompressedRowSparseMatrix* jacobian =
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down_cast<CompressedRowSparseMatrix*>(base_jacobian);
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double* jacobian_values = jacobian->mutable_values();
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const int* jacobian_rows = jacobian->rows();
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const ResidualBlock* residual_block =
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program_->residual_blocks()[residual_id];
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const int num_parameter_blocks = residual_block->NumParameterBlocks();
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const int num_residuals = residual_block->NumResiduals();
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// It is necessary to determine the order of the jacobian blocks before
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// copying them into the CompressedRowSparseMatrix. Just because a cost
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// function uses parameter blocks 1 after 2 in its arguments does not mean
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// that the block 1 occurs before block 2 in the column layout of the
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// jacobian. Thus, determine the order by sorting the jacobian blocks by their
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// position in the state vector.
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vector<pair<int, int> > evaluated_jacobian_blocks;
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for (int j = 0; j < num_parameter_blocks; ++j) {
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const ParameterBlock* parameter_block =
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residual_block->parameter_blocks()[j];
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if (!parameter_block->IsConstant()) {
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evaluated_jacobian_blocks.push_back(
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make_pair(parameter_block->index(), j));
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sort(evaluated_jacobian_blocks.begin(), evaluated_jacobian_blocks.end());
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// Where in the current row does the jacobian for a parameter block begin.
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// Iterate over the jacobian blocks in increasing order of their
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// positions in the reduced parameter vector.
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for (int i = 0; i < evaluated_jacobian_blocks.size(); ++i) {
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const ParameterBlock* parameter_block =
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program_->parameter_blocks()[evaluated_jacobian_blocks[i].first];
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const int argument = evaluated_jacobian_blocks[i].second;
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const int parameter_block_size = parameter_block->LocalSize();
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// Copy one row of the jacobian block at a time.
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for (int r = 0; r < num_residuals; ++r) {
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// Position of the r^th row of the current jacobian block.
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const double* block_row_begin =
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jacobians[argument] + r * parameter_block_size;
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// Position in the values array of the jacobian where this
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// row of the jacobian block should go.
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double* column_block_begin =
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jacobian_values + jacobian_rows[residual_offset + r] + col_pos;
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copy(block_row_begin,
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block_row_begin + parameter_block_size,
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col_pos += parameter_block_size;
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} // namespace internal
added
removed
internal/ceres/compressed_row_jacobian_writer.cc
