SparseEigen.h

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/* ----------------------------------------------------------------------------
 
 * GTSAM Copyright 2010, Georgia Tech Research Corporation,
 * Atlanta, Georgia 30332-0415
 * All Rights Reserved
 * Authors: Frank Dellaert, et al. (see THANKS for the full author list)
 
 * See LICENSE for the license information
 
 * -------------------------------------------------------------------------- */
 
#pragma once
 
#include <gtsam/linear/GaussianFactorGraph.h>
#include <gtsam/linear/VectorValues.h>
 
#include <Eigen/Sparse>
 
namespace gtsam {
 
typedef Eigen::SparseMatrix<double, Eigen::ColMajor, int> SparseEigen;
 
SparseEigen sparseJacobianEigen(
    const GaussianFactorGraph &gfg, const Ordering &ordering) {
  gttic_(SparseEigen_sparseJacobianEigen);
  // intermediate `entries` vector is kind of unavoidable due to how expensive
  // factor->rows() is, which prevents us from populating SparseEigen directly.
  size_t nrows, ncols;
  auto entries = gfg.sparseJacobian(ordering, nrows, ncols);
  // declare sparse matrix
  SparseEigen Ab(nrows, ncols);
  // See Eigen::set_from_triplets.  This is about 5% faster.
  // pass 1: count the nnz per inner-vector
  std::vector<int> nnz(ncols, 0);
  for (const auto &entry : entries) nnz[std::get<1>(entry)]++;
  Ab.reserve(nnz);
  // pass 2: insert the elements
  for (const auto &entry : entries)
    Ab.insert(std::get<0>(entry), std::get<1>(entry)) = std::get<2>(entry);
  return Ab;
}
 
SparseEigen sparseJacobianEigen(const GaussianFactorGraph &gfg) {
  gttic_(SparseEigen_sparseJacobianEigen_defaultOrdering);
  return sparseJacobianEigen(gfg, Ordering(gfg.keys()));
}
 
}  // namespace gtsam