12345qiupeng
/
gtsam
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Updated comments on the AntiFactor

release/4.3a0
Stephen Williams 2012-01-28 21:42:49 +00:00
parent 43cb3a3cae
commit 0364d16d15
1 changed files with 14 additions and 15 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

29
gtsam/slam/AntiFactor.h
View File

@ -23,9 +23,9 @@
namespace gtsam {
/**
* A class for a measurement predicted by "between(config[key1],config[key2])"
* KEY1::Value is the Lie Group type
* T is the measurement type, by default the same
* A class for downdating an existing factor from a graph. The AntiFactor returns the same
* linearized Hessian matrices of the original factor, but with the opposite sign. This effectively
* cancels out any affects of the original factor during optimization."
*/
template<class VALUES>
class AntiFactor: public NonlinearFactor<VALUES> {
@ -69,27 +69,26 @@ namespace gtsam {
/**
* Calculate the error of the factor
* This is typically equal to log-likelihood, e.g. 0.5(h(x)-z)^2/sigma^2 in case of Gaussian.
* You can override this for systems with unusual noise models.
* For the AntiFactor, this will have the same magnitude of the original factor,
* but the opposite sign.
*/
double error(const VALUES& c) const { return -factor_->error(c); }
/** get the dimension of the factor (number of rows on linearization) */
/** get the dimension of the factor (same as the original factor) */
size_t dim() const { return factor_->dim(); }
/**
* Checks whether a factor should be used based on a set of values.
* This is primarily used to implment inequality constraints that
* require a variable active set. For all others, the default implementation
* returning true solves this problem.
*
* In an inequality/bounding constraint, this active() returns true
* when the constraint is *NOT* fulfilled.
* @return true if the constraint is active
* Checks whether this factor should be used based on a set of values.
* The AntiFactor will have the same 'active' profile as the original factor.
*/
bool active(const VALUES& c) const { return factor_->active(c); }
/** linearize to a GaussianFactor */
/**
* Linearize to a GaussianFactor. The AntiFactor always returns a Hessian Factor
* with the same Hessian matrices as the original factor (even if the original factor
* returns a Jacobian instead of a full Hessian), but with the opposite sign. This
* effectively cancels the effect of the original factor on the factor graph.
*/
boost::shared_ptr<GaussianFactor>
linearize(const VALUES& c, const Ordering& ordering) const {