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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
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29
gtsam/slam/AntiFactor.h
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@ -23,9 +23,9 @@
namespace gtsam { namespace gtsam {
/** /**
* A class for a measurement predicted by "between(config[key1],config[key2])" * A class for downdating an existing factor from a graph. The AntiFactor returns the same
* KEY1::Value is the Lie Group type * linearized Hessian matrices of the original factor, but with the opposite sign. This effectively
* T is the measurement type, by default the same * cancels out any affects of the original factor during optimization."
*/ */
template<class VALUES> template<class VALUES>
class AntiFactor: public NonlinearFactor<VALUES> { class AntiFactor: public NonlinearFactor<VALUES> {
@ -69,27 +69,26 @@ namespace gtsam {
/** /**
* Calculate the error of the factor * 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. * For the AntiFactor, this will have the same magnitude of the original factor,
* You can override this for systems with unusual noise models. * but the opposite sign.
*/ */
double error(const VALUES& c) const { return -factor_->error(c); } 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(); } size_t dim() const { return factor_->dim(); }
/** /**
* Checks whether a factor should be used based on a set of values. * Checks whether this factor should be used based on a set of values.
* This is primarily used to implment inequality constraints that * The AntiFactor will have the same 'active' profile as the original factor.
* 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
*/ */
bool active(const VALUES& c) const { return factor_->active(c); } 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> boost::shared_ptr<GaussianFactor>
linearize(const VALUES& c, const Ordering& ordering) const { linearize(const VALUES& c, const Ordering& ordering) const {