blob: 006713fb50ab9a23970430005bccf5be219eaa9e [file] [log] [blame]
// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2022 Google Inc. All rights reserved.
// http://ceres-solver.org/
//
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// modification, are permitted provided that the following conditions are met:
//
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// 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
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// Author: sameeragarwal@google.com (Sameer Agarwal)
#include "ceres/block_random_access_diagonal_matrix.h"
#include <algorithm>
#include <memory>
#include <set>
#include <utility>
#include <vector>
#include "Eigen/Dense"
#include "ceres/internal/export.h"
#include "ceres/stl_util.h"
#include "ceres/triplet_sparse_matrix.h"
#include "ceres/types.h"
#include "glog/logging.h"
namespace ceres::internal {
using std::vector;
// TODO(sameeragarwal): Drop the dependence on TripletSparseMatrix.
BlockRandomAccessDiagonalMatrix::BlockRandomAccessDiagonalMatrix(
const vector<int>& blocks)
: blocks_(blocks) {
// Build the row/column layout vector and count the number of scalar
// rows/columns.
int num_cols = 0;
int num_nonzeros = 0;
vector<int> block_positions;
for (int block_size : blocks_) {
block_positions.push_back(num_cols);
num_cols += block_size;
num_nonzeros += block_size * block_size;
}
VLOG(1) << "Matrix Size [" << num_cols << "," << num_cols << "] "
<< num_nonzeros;
tsm_ =
std::make_unique<TripletSparseMatrix>(num_cols, num_cols, num_nonzeros);
tsm_->set_num_nonzeros(num_nonzeros);
int* rows = tsm_->mutable_rows();
int* cols = tsm_->mutable_cols();
double* values = tsm_->mutable_values();
int pos = 0;
for (int i = 0; i < blocks_.size(); ++i) {
const int block_size = blocks_[i];
layout_.push_back(new CellInfo(values + pos));
const int block_begin = block_positions[i];
for (int r = 0; r < block_size; ++r) {
for (int c = 0; c < block_size; ++c, ++pos) {
rows[pos] = block_begin + r;
cols[pos] = block_begin + c;
}
}
}
}
// Assume that the user does not hold any locks on any cell blocks
// when they are calling SetZero.
BlockRandomAccessDiagonalMatrix::~BlockRandomAccessDiagonalMatrix() {
STLDeleteContainerPointers(layout_.begin(), layout_.end());
}
CellInfo* BlockRandomAccessDiagonalMatrix::GetCell(int row_block_id,
int col_block_id,
int* row,
int* col,
int* row_stride,
int* col_stride) {
if (row_block_id != col_block_id) {
return nullptr;
}
const int stride = blocks_[row_block_id];
// Each cell is stored contiguously as its own little dense matrix.
*row = 0;
*col = 0;
*row_stride = stride;
*col_stride = stride;
return layout_[row_block_id];
}
// Assume that the user does not hold any locks on any cell blocks
// when they are calling SetZero.
void BlockRandomAccessDiagonalMatrix::SetZero() {
if (tsm_->num_nonzeros()) {
VectorRef(tsm_->mutable_values(), tsm_->num_nonzeros()).setZero();
}
}
void BlockRandomAccessDiagonalMatrix::Invert() {
double* values = tsm_->mutable_values();
for (int block_size : blocks_) {
MatrixRef block(values, block_size, block_size);
block = block.selfadjointView<Eigen::Upper>().llt().solve(
Matrix::Identity(block_size, block_size));
values += block_size * block_size;
}
}
void BlockRandomAccessDiagonalMatrix::RightMultiplyAndAccumulate(
const double* x, double* y) const {
CHECK(x != nullptr);
CHECK(y != nullptr);
const double* values = tsm_->values();
for (int block_size : blocks_) {
ConstMatrixRef block(values, block_size, block_size);
VectorRef(y, block_size).noalias() += block * ConstVectorRef(x, block_size);
x += block_size;
y += block_size;
values += block_size * block_size;
}
}
} // namespace ceres::internal