LevenbergMarquardtParams.h

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/* ----------------------------------------------------------------------------
 
 * GTSAM Copyright 2010, Georgia Tech Research Corporation,
 * Atlanta, Georgia 30332-0415
 * All Rights Reserved
 * Authors: Frank Dellaert, et al. (see THANKS for the full author list)
 
 * See LICENSE for the license information
 
 * -------------------------------------------------------------------------- */
 
#pragma once
 
#include <gtsam/nonlinear/NonlinearOptimizerParams.h>
#include <gtsam/nonlinear/NonlinearFactorGraph.h>
 
namespace gtsam {
 
class LevenbergMarquardtOptimizer;
 
class GTSAM_EXPORT LevenbergMarquardtParams: public NonlinearOptimizerParams {
 
public:
  enum VerbosityLM {
    SILENT = 0, SUMMARY, TERMINATION, LAMBDA, TRYLAMBDA, TRYCONFIG, DAMPED, TRYDELTA
  };
 
  static VerbosityLM verbosityLMTranslator(const std::string &s);
  static std::string verbosityLMTranslator(VerbosityLM value);
  using OptimizerType = LevenbergMarquardtOptimizer;
 
public:
 
  double lambdaInitial; 
  double lambdaFactor; 
  double lambdaUpperBound; 
  double lambdaLowerBound; 
  VerbosityLM verbosityLM; 
  double minModelFidelity; 
  std::string logFile; 
  bool diagonalDamping; 
  bool useFixedLambdaFactor; 
  double minDiagonal; 
  double maxDiagonal; 
 
  LevenbergMarquardtParams()
      : verbosityLM(SILENT),
        diagonalDamping(false),
        minDiagonal(1e-6),
        maxDiagonal(1e32) {
    SetLegacyDefaults(this);
  }
 
  static void SetLegacyDefaults(LevenbergMarquardtParams* p) {
    // Relevant NonlinearOptimizerParams:
    p->maxIterations = 100;
    p->relativeErrorTol = 1e-5;
    p->absoluteErrorTol = 1e-5;
    // LM-specific:
    p->lambdaInitial = 1e-5;
    p->lambdaFactor = 10.0;
    p->lambdaUpperBound = 1e5;
    p->lambdaLowerBound = 0.0;
    p->minModelFidelity = 1e-3;
    p->diagonalDamping = false;
    p->useFixedLambdaFactor = true;
  }
 
  // these do seem to work better for SFM
  static void SetCeresDefaults(LevenbergMarquardtParams* p) {
    // Relevant NonlinearOptimizerParams:
    p->maxIterations = 50;
    p->absoluteErrorTol = 0;     // No corresponding option in CERES
    p->relativeErrorTol = 1e-6;  // This is function_tolerance
    // LM-specific:
    p->lambdaUpperBound = 1e32;
    p->lambdaLowerBound = 1e-16;
    p->lambdaInitial = 1e-04;
    p->lambdaFactor = 2.0;
    p->minModelFidelity = 1e-3;  // options.min_relative_decrease in CERES
    p->diagonalDamping = true;
    p->useFixedLambdaFactor = false;  // This is important
  }
 
  static LevenbergMarquardtParams LegacyDefaults() {
    LevenbergMarquardtParams p;
    SetLegacyDefaults(&p);
    return p;
  }
 
  static LevenbergMarquardtParams CeresDefaults() {
    LevenbergMarquardtParams p;
    SetCeresDefaults(&p);
    return p;
  }
 
  static LevenbergMarquardtParams EnsureHasOrdering(LevenbergMarquardtParams params,
                                                    const NonlinearFactorGraph& graph) {
    if (!params.ordering)
      params.ordering = Ordering::Create(params.orderingType, graph);
    return params;
  }
 
  static LevenbergMarquardtParams ReplaceOrdering(LevenbergMarquardtParams params,
                                                  const Ordering& ord) {
    params.ordering = ord;
    return params;
  }
 
  ~LevenbergMarquardtParams() override {}
  void print(const std::string& str = "") const override;
 
  bool getDiagonalDamping() const { return diagonalDamping; }
  double getlambdaFactor() const { return lambdaFactor; }
  double getlambdaInitial() const { return lambdaInitial; }
  double getlambdaLowerBound() const { return lambdaLowerBound; }
  double getlambdaUpperBound() const { return lambdaUpperBound; }
  bool getUseFixedLambdaFactor() { return useFixedLambdaFactor; }
  std::string getLogFile() const { return logFile; }
  std::string getVerbosityLM() const { return verbosityLMTranslator(verbosityLM);}
  
  void setDiagonalDamping(bool flag) { diagonalDamping = flag; }
  void setlambdaFactor(double value) { lambdaFactor = value; }
  void setlambdaInitial(double value) { lambdaInitial = value; }
  void setlambdaLowerBound(double value) { lambdaLowerBound = value; }
  void setlambdaUpperBound(double value) { lambdaUpperBound = value; }
  void setUseFixedLambdaFactor(bool flag) { useFixedLambdaFactor = flag;}
  void setLogFile(const std::string& s) { logFile = s; }
  void setVerbosityLM(const std::string& s) { verbosityLM = verbosityLMTranslator(s);}
  // @}
 
  std::shared_ptr<NonlinearOptimizerParams> clone() const {
    return std::shared_ptr<NonlinearOptimizerParams>(new LevenbergMarquardtParams(*this));
  }
 
};
 
}