From af15401b17f2078208d77543c4cb1b94ed236e5b Mon Sep 17 00:00:00 2001 From: Frank Dellaert Date: Wed, 7 Sep 2011 17:11:11 +0000 Subject: [PATCH] use QR by default --- gtsam/linear/KalmanFilter.cpp | 17 +++++++++-------- 1 file changed, 9 insertions(+), 8 deletions(-) diff --git a/gtsam/linear/KalmanFilter.cpp b/gtsam/linear/KalmanFilter.cpp index 227c270d7..f85f3fcb2 100644 --- a/gtsam/linear/KalmanFilter.cpp +++ b/gtsam/linear/KalmanFilter.cpp @@ -9,15 +9,15 @@ * -------------------------------------------------------------------------- */ -/* - * testKalmanFilter.cpp +/** + * @file KalmanFilter.cpp * - * Simple linear Kalman filter. + * @brief Simple linear Kalman filter. * Implemented using factor graphs, i.e., does LDL-based SRIF, really. * - * Created on: Sep 3, 2011 - * @author Stephen Williams - * @author Frank Dellaert + * @date Sep 3, 2011 + * @author Stephen Williams + * @author Frank Dellaert */ #include @@ -26,11 +26,12 @@ namespace gtsam { - // Auxiliary function to solve factor graph and return pointer to root conditional + /// Auxiliary function to solve factor graph and return pointer to root conditional GaussianConditional* solve(GaussianFactorGraph& factorGraph) { // Solve the factor graph - GaussianSequentialSolver solver(factorGraph); + const bool useQr = true; // make sure we use QR (numerically stable) + GaussianSequentialSolver solver(factorGraph, useQR); GaussianBayesNet::shared_ptr bayesNet = solver.eliminate(); // As this is a filter, all we need is the posterior P(x_t),