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Updated the Doxygen style Comments on NonlinearOptimizer.h

release/4.3a0
Natesh Srinivasan 2011-09-09 02:34:29 +00:00
parent fd4c4fda5d
commit 3014daa140
1 changed files with 46 additions and 46 deletions
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92
gtsam/nonlinear/NonlinearOptimizer.h
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@ -26,10 +26,10 @@ namespace gtsam {
class NullOptimizerWriter {
public:
NullOptimizerWriter(double error) {}
NullOptimizerWriter(double error) {} ///Contructor
virtual ~NullOptimizerWriter() {}
virtual void write(double error) {}
};
virtual void write(double error) {} ///Capturing the values of the parameters after the optimization
}; ///
/**
* The class NonlinearOptimizer encapsulates an optimization state.
@ -62,13 +62,13 @@ class NonlinearOptimizer {
public:
// For performance reasons in recursion, we store values in a shared_ptr
typedef boost::shared_ptr<const T> shared_values;
typedef boost::shared_ptr<const G> shared_graph;
typedef boost::shared_ptr<L> shared_linear;
typedef boost::shared_ptr<const Ordering> shared_ordering;
typedef boost::shared_ptr<GS> shared_solver;
typedef NonlinearOptimizationParameters Parameters;
typedef boost::shared_ptr<const Parameters> shared_parameters ;
typedef boost::shared_ptr<const T> shared_values; ///Prevent memory leaks in Values
typedef boost::shared_ptr<const G> shared_graph; /// Prevent memory leaks in Graph
typedef boost::shared_ptr<L> shared_linear; /// Not sure
typedef boost::shared_ptr<const Ordering> shared_ordering; ///ordering parameters
typedef boost::shared_ptr<GS> shared_solver; /// Solver
typedef NonlinearOptimizationParameters Parameters; ///These take the parameters defined in NonLinearOptimizationParameters.h
typedef boost::shared_ptr<const Parameters> shared_parameters ; ///
typedef boost::shared_ptr<VariableIndex> shared_structure; // TODO: make this const
private:
@ -76,8 +76,8 @@ private:
typedef NonlinearOptimizer<G, T, L, GS> This;
typedef boost::shared_ptr<const std::vector<size_t> > shared_dimensions;
// keep a reference to const version of the graph
// These normally do not change
/// keep a reference to const version of the graph
/// These normally do not change
const shared_graph graph_;
// keep a values structure and its error
@ -234,12 +234,12 @@ public:
*/
NonlinearOptimizer iterate() const;
/**
* Optimize a solution for a non linear factor graph
* @param relativeTreshold
* @param absoluteTreshold
* @param verbosity Integer specifying how much output to provide
*/
///
///Optimize a solution for a non linear factor graph
///param relativeTreshold
///@param absoluteTreshold
///@param verbosity Integer specifying how much output to provide
///
// suggested interface
NonlinearOptimizer gaussNewton() const;
@ -252,31 +252,31 @@ public:
*/
NonlinearOptimizer iterateLM();
/**
* Optimize using Levenberg-Marquardt. Really Levenberg's
* algorithm at this moment, as we just add I*\lambda to Hessian
* H'H. The probabilistic explanation is very simple: every
* variable gets an extra Gaussian prior that biases staying at
* current value, with variance 1/lambda. This is done very easily
* (but perhaps wastefully) by adding a prior factor for each of
* the variables, after linearization.
*
* @param relativeThreshold
* @param absoluteThreshold
* @param verbosity Integer specifying how much output to provide
* @param lambdaFactor Factor by which to decrease/increase lambda
*/
///
///Optimize using Levenberg-Marquardt. Really Levenberg's
///algorithm at this moment, as we just add I*\lambda to Hessian
///H'H. The probabilistic explanation is very simple: every
///variable gets an extra Gaussian prior that biases staying at
///current value, with variance 1/lambda. This is done very easily
///(but perhaps wastefully) by adding a prior factor for each of
///the variables, after linearization.
///
///@param relativeThreshold
///@param absoluteThreshold
///@param verbosity Integer specifying how much output to provide
///@param lambdaFactor Factor by which to decrease/increase lambda
///
NonlinearOptimizer levenbergMarquardt();
// static interfaces to LM and GN optimization techniques
/**
* Static interface to LM optimization using default ordering and thresholds
* @param graph Nonlinear factor graph to optimize
* @param values Initial values
* @param verbosity Integer specifying how much output to provide
* @return an optimized values structure
*/
///
///Static interface to LM optimization using default ordering and thresholds
///@param graph Nonlinear factor graph to optimize
///@param values Initial values
///@param verbosity Integer specifying how much output to provide
///@return an optimized values structure
///
static shared_values optimizeLM(shared_graph graph,
shared_values values,
shared_parameters parameters = boost::make_shared<Parameters>()) {
@ -317,13 +317,13 @@ public:
verbosity);
}
/**
* Static interface to GN optimization using default ordering and thresholds
* @param graph Nonlinear factor graph to optimize
* @param values Initial values
* @param verbosity Integer specifying how much output to provide
* @return an optimized values structure
*/
///
///Static interface to GN optimization using default ordering and thresholds
///@param graph Nonlinear factor graph to optimize
///@param values Initial values
///@param verbosity Integer specifying how much output to provide
///@return an optimized values structure
///
static shared_values optimizeGN(shared_graph graph,
shared_values values,
shared_parameters parameters = boost::make_shared<Parameters>()) {