gtsam/gtsam/nonlinear/factorTesting.h

69 lines
2.2 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 factorTesting.h
* @date September 18, 2014
* @author Frank Dellaert
* @author Paul Furgale
* @brief Evaluate derivatives of a nonlinear factor numerically
*/
#pragma once
#include <gtsam/nonlinear/NonlinearFactor.h>
#include <gtsam/base/numericalDerivative.h>
namespace gtsam {
/**
* Linearize a nonlinear factor using numerical differentiation
* The benefit of this method is that it does not need to know what types are
* involved to evaluate the factor. If all the machinery of gtsam is working
* correctly, we should get the correct numerical derivatives out the other side.
*/
JacobianFactor linearizeNumerically(const NoiseModelFactor& factor,
const Values& values, double delta = 1e-5) {
// We will fill a vector of key/Jacobians pairs (a map would sort)
std::vector<std::pair<Key, Matrix> > jacobians;
// Get size
Eigen::VectorXd e = factor.whitenedError(values);
const size_t rows = e.size();
// Loop over all variables
VectorValues dX = values.zeroVectors();
BOOST_FOREACH(Key key, factor) {
// Compute central differences using the values struct.
const size_t cols = dX.dim(key);
Matrix J = Matrix::Zero(rows, cols);
for (size_t col = 0; col < cols; ++col) {
Eigen::VectorXd dx = Eigen::VectorXd::Zero(cols);
dx[col] = delta;
dX[key] = dx;
Values eval_values = values.retract(dX);
Eigen::VectorXd left = factor.whitenedError(eval_values);
dx[col] = -delta;
dX[key] = dx;
eval_values = values.retract(dX);
Eigen::VectorXd right = factor.whitenedError(eval_values);
J.col(col) = (left - right) * (1.0 / (2.0 * delta));
}
jacobians.push_back(std::make_pair(key,J));
}
// Next step...return JacobianFactor
return JacobianFactor(jacobians, -e);
}
} // namespace gtsam