gtsam/gtsam/linear/BinaryJacobianFactor.h

92 lines
3.0 KiB
C++

/* ----------------------------------------------------------------------------
* 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
* -------------------------------------------------------------------------- */
/**
* @file BinaryJacobianFactor.h
*
* @brief A binary JacobianFactor specialization that uses fixed matrix math for speed
*
* @date June 2015
* @author Frank Dellaert
*/
#pragma once
#include <gtsam/linear/JacobianFactor.h>
#include <gtsam/base/SymmetricBlockMatrix.h>
#include <gtsam/base/timing.h>
namespace gtsam {
/**
* A binary JacobianFactor specialization that uses fixed matrix math for speed
*/
template<int M, int N1, int N2>
struct BinaryJacobianFactor: JacobianFactor {
/// Constructor
BinaryJacobianFactor(Key key1, const Eigen::Matrix<double, M, N1>& A1,
Key key2, const Eigen::Matrix<double, M, N2>& A2,
const Eigen::Matrix<double, M, 1>& b, //
const SharedDiagonal& model = SharedDiagonal()) :
JacobianFactor(key1, A1, key2, A2, b, model) {
}
inline Key key1() const {
return keys_[0];
}
inline Key key2() const {
return keys_[1];
}
// Fixed-size matrix update
void updateHessian(const FastVector<Key>& infoKeys,
SymmetricBlockMatrix* info) const {
gttic(updateHessian_BinaryJacobianFactor);
// Whiten the factor if it has a noise model
const SharedDiagonal& model = get_model();
if (model && !model->isUnit()) {
if (model->isConstrained())
throw std::invalid_argument(
"BinaryJacobianFactor::updateHessian: cannot update information with "
"constrained noise model");
BinaryJacobianFactor whitenedFactor(key1(), model->Whiten(getA(begin())),
key2(), model->Whiten(getA(end())), model->whiten(getb()));
whitenedFactor.updateHessian(infoKeys, info);
} else {
// First build an array of slots
DenseIndex slot1 = Slot(infoKeys, key1());
DenseIndex slot2 = Slot(infoKeys, key2());
DenseIndex slotB = info->nBlocks() - 1;
const Matrix& Ab = Ab_.matrix();
Eigen::Block<const Matrix, M, N1> A1(Ab, 0, 0);
Eigen::Block<const Matrix, M, N2> A2(Ab, 0, N1);
Eigen::Block<const Matrix, M, 1> b(Ab, 0, N1 + N2);
// We perform I += A'*A to the upper triangle
(*info)(slot1, slot1).selfadjointView().rankUpdate(A1.transpose());
(*info)(slot1, slot2).knownOffDiagonal() += A1.transpose() * A2;
(*info)(slot1, slotB).knownOffDiagonal() += A1.transpose() * b;
(*info)(slot2, slot2).selfadjointView().rankUpdate(A2.transpose());
(*info)(slot2, slotB).knownOffDiagonal() += A2.transpose() * b;
(*info)(slotB, slotB)(0, 0) += b.transpose() * b;
}
}
};
template<int M, int N1, int N2>
struct traits<BinaryJacobianFactor<M, N1, N2> > : Testable<
BinaryJacobianFactor<M, N1, N2> > {
};
} //namespace gtsam