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// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2023 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.
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//
// Authors: joydeepb@cs.utexas.edu (Joydeep Biswas)
#include "ceres/fake_bundle_adjustment_jacobian.h"
#include <memory>
#include <random>
#include <string>
#include <utility>
#include "Eigen/Dense"
#include "ceres/block_sparse_matrix.h"
#include "ceres/internal/eigen.h"
namespace ceres::internal {
std::unique_ptr<BlockSparseMatrix> CreateFakeBundleAdjustmentJacobian(
int num_cameras,
int num_points,
int camera_size,
int point_size,
double visibility,
std::mt19937& prng) {
constexpr int kResidualSize = 2;
CompressedRowBlockStructure* bs = new CompressedRowBlockStructure;
int c = 0;
// Add column blocks for each point
for (int i = 0; i < num_points; ++i) {
bs->cols.push_back(Block(point_size, c));
c += point_size;
}
// Add column blocks for each camera.
for (int i = 0; i < num_cameras; ++i) {
bs->cols.push_back(Block(camera_size, c));
c += camera_size;
}
std::bernoulli_distribution visibility_distribution(visibility);
int row_pos = 0;
int cell_pos = 0;
for (int i = 0; i < num_points; ++i) {
for (int j = 0; j < num_cameras; ++j) {
if (!visibility_distribution(prng)) {
continue;
}
bs->rows.emplace_back();
auto& row = bs->rows.back();
row.block.position = row_pos;
row.block.size = kResidualSize;
auto& cells = row.cells;
cells.resize(2);
cells[0].block_id = i;
cells[0].position = cell_pos;
cell_pos += kResidualSize * point_size;
cells[1].block_id = num_points + j;
cells[1].position = cell_pos;
cell_pos += kResidualSize * camera_size;
row_pos += kResidualSize;
}
}
auto jacobian = std::make_unique<BlockSparseMatrix>(bs);
VectorRef(jacobian->mutable_values(), jacobian->num_nonzeros()).setRandom();
return jacobian;
}
std::pair<
std::unique_ptr<PartitionedMatrixView<2, Eigen::Dynamic, Eigen::Dynamic>>,
std::unique_ptr<BlockSparseMatrix>>
CreateFakeBundleAdjustmentPartitionedJacobian(int num_cameras,
int num_points,
int camera_size,
int landmark_size,
double visibility,
std::mt19937& rng) {
using PartitionedView =
PartitionedMatrixView<2, Eigen::Dynamic, Eigen::Dynamic>;
auto block_sparse_matrix = CreateFakeBundleAdjustmentJacobian(
num_cameras, num_points, camera_size, landmark_size, visibility, rng);
LinearSolver::Options options;
options.elimination_groups.push_back(num_points);
auto partitioned_view =
std::make_unique<PartitionedView>(options, *block_sparse_matrix);
return std::make_pair(std::move(partitioned_view),
std::move(block_sparse_matrix));
}
} // namespace ceres::internal