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Removed some unneeded namespace qualifications

release/4.3a0
Frank Dellaert 2013-08-30 16:53:21 +00:00
parent c9a7796fc3
commit 2baa593458
4 changed files with 9 additions and 9 deletions
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4
examples/SelfCalibrationExample.cpp
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@ -46,8 +46,8 @@ using namespace gtsam;
int main(int argc, char* argv[]) { int main(int argc, char* argv[]) {
// Create the set of ground-truth // Create the set of ground-truth
std::vector<gtsam::Point3> points = createPoints(); vector<Point3> points = createPoints();
std::vector<gtsam::Pose3> poses = createPoses(); vector<Pose3> poses = createPoses();
// Create the factor graph // Create the factor graph
NonlinearFactorGraph graph; NonlinearFactorGraph graph;

4
examples/VisualISAM2Example.cpp
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@ -64,10 +64,10 @@ int main(int argc, char* argv[]) {
noiseModel::Isotropic::shared_ptr measurementNoise = noiseModel::Isotropic::Sigma(2, 1.0); // one pixel in u and v noiseModel::Isotropic::shared_ptr measurementNoise = noiseModel::Isotropic::Sigma(2, 1.0); // one pixel in u and v
// Create the set of ground-truth landmarks // Create the set of ground-truth landmarks
std::vector<gtsam::Point3> points = createPoints(); vector<Point3> points = createPoints();
// Create the set of ground-truth poses // Create the set of ground-truth poses
std::vector<gtsam::Pose3> poses = createPoses(); vector<Pose3> poses = createPoses();
// Create an iSAM2 object. Unlike iSAM1, which performs periodic batch steps to maintain proper linearization // Create an iSAM2 object. Unlike iSAM1, which performs periodic batch steps to maintain proper linearization
// and efficient variable ordering, iSAM2 performs partial relinearization/reordering at each step. A parameter // and efficient variable ordering, iSAM2 performs partial relinearization/reordering at each step. A parameter

4
examples/VisualISAMExample.cpp
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@ -64,10 +64,10 @@ int main(int argc, char* argv[]) {
noiseModel::Isotropic::shared_ptr measurementNoise = noiseModel::Isotropic::Sigma(2, 1.0); // one pixel in u and v noiseModel::Isotropic::shared_ptr measurementNoise = noiseModel::Isotropic::Sigma(2, 1.0); // one pixel in u and v
// Create the set of ground-truth landmarks // Create the set of ground-truth landmarks
std::vector<gtsam::Point3> points = createPoints(); vector<Point3> points = createPoints();
// Create the set of ground-truth poses // Create the set of ground-truth poses
std::vector<gtsam::Pose3> poses = createPoses(); vector<Pose3> poses = createPoses();
// Create a NonlinearISAM object which will relinearize and reorder the variables every "relinearizeInterval" updates // Create a NonlinearISAM object which will relinearize and reorder the variables every "relinearizeInterval" updates
int relinearizeInterval = 3; int relinearizeInterval = 3;

6
examples/VisualSLAMExample.cpp
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@ -71,10 +71,10 @@ int main(int argc, char* argv[]) {
noiseModel::Isotropic::shared_ptr measurementNoise = noiseModel::Isotropic::Sigma(2, 1.0); // one pixel in u and v noiseModel::Isotropic::shared_ptr measurementNoise = noiseModel::Isotropic::Sigma(2, 1.0); // one pixel in u and v
// Create the set of ground-truth landmarks // Create the set of ground-truth landmarks
std::vector<gtsam::Point3> points = createPoints(); vector<Point3> points = createPoints();
// Create the set of ground-truth poses // Create the set of ground-truth poses
std::vector<gtsam::Pose3> poses = createPoses(); vector<Pose3> poses = createPoses();
// Create a factor graph // Create a factor graph
NonlinearFactorGraph graph; NonlinearFactorGraph graph;
@ -99,7 +99,7 @@ int main(int argc, char* argv[]) {
graph.push_back(PriorFactor<Point3>(Symbol('l', 0), points[0], pointNoise)); // add directly to graph graph.push_back(PriorFactor<Point3>(Symbol('l', 0), points[0], pointNoise)); // add directly to graph
graph.print("Factor Graph:\n"); graph.print("Factor Graph:\n");
// Create the data structure to hold the initialEstimate estimate to the solution // Create the data structure to hold the initial estimate to the solution
// Intentionally initialize the variables off from the ground truth // Intentionally initialize the variables off from the ground truth
Values initialEstimate; Values initialEstimate;
for (size_t i = 0; i < poses.size(); ++i) for (size_t i = 0; i < poses.size(); ++i)