From fd601b55d856612bba879f20c48ec56198401f6a Mon Sep 17 00:00:00 2001 From: Alex Cunningham Date: Sat, 5 Nov 2011 03:10:49 +0000 Subject: [PATCH] Replaced expmap with retract in kalman filter example --- examples/elaboratePoint2KalmanFilter.cpp | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/examples/elaboratePoint2KalmanFilter.cpp b/examples/elaboratePoint2KalmanFilter.cpp index 23870a888..6b6e4fb30 100644 --- a/examples/elaboratePoint2KalmanFilter.cpp +++ b/examples/elaboratePoint2KalmanFilter.cpp @@ -118,7 +118,7 @@ int main() { // Extract the current estimate of x1,P1 from the Bayes Network VectorValues result = optimize(*linearBayesNet); - Point2 x1_predict = linearizationPoints[x1].expmap(result[ordering->at(x1)]); + Point2 x1_predict = linearizationPoints[x1].retract(result[ordering->at(x1)]); x1_predict.print("X1 Predict"); // Update the new linearization point to the new estimate @@ -190,7 +190,7 @@ int main() { // Extract the current estimate of x1 from the Bayes Network result = optimize(*linearBayesNet); - Point2 x1_update = linearizationPoints[x1].expmap(result[ordering->at(x1)]); + Point2 x1_update = linearizationPoints[x1].retract(result[ordering->at(x1)]); x1_update.print("X1 Update"); // Update the linearization point to the new estimate @@ -237,7 +237,7 @@ int main() { // Extract the current estimate of x2 from the Bayes Network result = optimize(*linearBayesNet); - Point2 x2_predict = linearizationPoints[x2].expmap(result[ordering->at(x2)]); + Point2 x2_predict = linearizationPoints[x2].retract(result[ordering->at(x2)]); x2_predict.print("X2 Predict"); // Update the linearization point to the new estimate @@ -281,7 +281,7 @@ int main() { // Extract the current estimate of x2 from the Bayes Network result = optimize(*linearBayesNet); - Point2 x2_update = linearizationPoints[x2].expmap(result[ordering->at(x2)]); + Point2 x2_update = linearizationPoints[x2].retract(result[ordering->at(x2)]); x2_update.print("X2 Update"); // Update the linearization point to the new estimate @@ -326,7 +326,7 @@ int main() { // Extract the current estimate of x3 from the Bayes Network result = optimize(*linearBayesNet); - Point2 x3_predict = linearizationPoints[x3].expmap(result[ordering->at(x3)]); + Point2 x3_predict = linearizationPoints[x3].retract(result[ordering->at(x3)]); x3_predict.print("X3 Predict"); // Update the linearization point to the new estimate @@ -370,7 +370,7 @@ int main() { // Extract the current estimate of x2 from the Bayes Network result = optimize(*linearBayesNet); - Point2 x3_update = linearizationPoints[x3].expmap(result[ordering->at(x3)]); + Point2 x3_update = linearizationPoints[x3].retract(result[ordering->at(x3)]); x3_update.print("X3 Update"); // Update the linearization point to the new estimate