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release/4.3a0
Richard Roberts 2012-05-14 18:32:54 +00:00
parent fdc4cc586d
commit 5f94e477a4
3 changed files with 92 additions and 91 deletions
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76
gtsam/nonlinear/DoglegOptimizer.h
View File

@ -22,6 +22,44 @@
namespace gtsam {
/** Parameters for Levenberg-Marquardt optimization. Note that this parameters
* class inherits from NonlinearOptimizerParams, which specifies the parameters
* common to all nonlinear optimization algorithms. This class also contains
* all of those parameters.
*/
class DoglegParams : public SuccessiveLinearizationParams {
public:
/** See DoglegParams::dlVerbosity */
enum DLVerbosity {
SILENT,
VERBOSE
};
double deltaInitial; ///< The initial trust region radius (default: 1.0)
DLVerbosity dlVerbosity; ///< The verbosity level for Dogleg (default: SILENT), see also NonlinearOptimizerParams::verbosity
DoglegParams() :
deltaInitial(1.0), dlVerbosity(SILENT) {}
virtual ~DoglegParams() {}
virtual void print(const std::string& str = "") const {
SuccessiveLinearizationParams::print(str);
std::cout << " deltaInitial: " << deltaInitial << "\n";
std::cout.flush();
}
};
/**
* State for DoglegOptimizer
*/
class DoglegState : public SuccessiveLinearizationState {
public:
double delta;
};
/**
* This class performs Dogleg nonlinear optimization
*/
@ -98,42 +136,4 @@ protected:
}
};
/** Parameters for Levenberg-Marquardt optimization. Note that this parameters
* class inherits from NonlinearOptimizerParams, which specifies the parameters
* common to all nonlinear optimization algorithms. This class also contains
* all of those parameters.
*/
class DoglegParams : public SuccessiveLinearizationParams {
public:
/** See DoglegParams::dlVerbosity */
enum DLVerbosity {
SILENT,
VERBOSE
};
double deltaInitial; ///< The initial trust region radius (default: 1.0)
DLVerbosity dlVerbosity; ///< The verbosity level for Dogleg (default: SILENT), see also NonlinearOptimizerParams::verbosity
DoglegParams() :
deltaInitial(1.0), dlVerbosity(SILENT) {}
virtual ~DoglegParams() {}
virtual void print(const std::string& str = "") const {
SuccessiveLinearizationParams::print(str);
std::cout << " deltaInitial: " << deltaInitial << "\n";
std::cout.flush();
}
};
/**
* State for DoglegOptimizer
*/
class DoglegState : public SuccessiveLinearizationState {
public:
double delta;
};
}

12
gtsam/nonlinear/GaussNewtonOptimizer.h
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@ -22,6 +22,12 @@
namespace gtsam {
/** Parameters for Gauss-Newton optimization, inherits from
* NonlinearOptimizationParams.
*/
class GaussNewtonParams : public SuccessiveLinearizationParams {
};
/**
* This class performs Gauss-Newton nonlinear optimization
*/
@ -98,10 +104,4 @@ protected:
};
/** Parameters for Gauss-Newton optimization, inherits from
* NonlinearOptimizationParams.
*/
class GaussNewtonParams : public SuccessiveLinearizationParams {
};
}

95
gtsam/nonlinear/LevenbergMarquardtOptimizer.h
View File

@ -22,6 +22,52 @@
namespace gtsam {
/** Parameters for Levenberg-Marquardt optimization. Note that this parameters
* class inherits from NonlinearOptimizerParams, which specifies the parameters
* common to all nonlinear optimization algorithms. This class also contains
* all of those parameters.
*/
class LevenbergMarquardtParams : public SuccessiveLinearizationParams {
public:
/** See LevenbergMarquardtParams::lmVerbosity */
enum LMVerbosity {
SILENT,
LAMBDA,
TRYLAMBDA,
TRYCONFIG,
TRYDELTA,
DAMPED
};
double lambdaInitial; ///< The initial Levenberg-Marquardt damping term (default: 1e-5)
double lambdaFactor; ///< The amount by which to multiply or divide lambda when adjusting lambda (default: 10.0)
double lambdaUpperBound; ///< The maximum lambda to try before assuming the optimization has failed (default: 1e5)
LMVerbosity lmVerbosity; ///< The verbosity level for Levenberg-Marquardt (default: SILENT), see also NonlinearOptimizerParams::verbosity
LevenbergMarquardtParams() :
lambdaInitial(1e-5), lambdaFactor(10.0), lambdaUpperBound(1e5), lmVerbosity(SILENT) {}
virtual ~LevenbergMarquardtParams() {}
virtual void print(const std::string& str = "") const {
SuccessiveLinearizationParams::print(str);
std::cout << " lambdaInitial: " << lambdaInitial << "\n";
std::cout << " lambdaFactor: " << lambdaFactor << "\n";
std::cout << " lambdaUpperBound: " << lambdaUpperBound << "\n";
std::cout.flush();
}
};
/**
* State for LevenbergMarquardtOptimizer
*/
class LevenbergMarquardtState : public NonlinearOptimizerState {
public:
double lambda;
};
/**
* This class performs Levenberg-Marquardt nonlinear optimization
*/
@ -44,7 +90,8 @@ public:
*/
LevenbergMarquardtOptimizer(const NonlinearFactorGraph& graph, const Values& initialValues,
const LevenbergMarquardtParams& params = LevenbergMarquardtParams()) :
NonlinearOptimizer(graph), params_(ensureHasOrdering(params)), state_(graph, initialValues), dimensions_(initialValues.dims(*params_.ordering)) {}
NonlinearOptimizer(graph), params_(ensureHasOrdering(params)),
state_(graph, initialValues), dimensions_(initialValues.dims(*params_.ordering)) {}
/** Standard constructor, requires a nonlinear factor graph, initial
* variable assignments, and optimization parameters. For convenience this
@ -100,50 +147,4 @@ protected:
}
};
/** Parameters for Levenberg-Marquardt optimization. Note that this parameters
* class inherits from NonlinearOptimizerParams, which specifies the parameters
* common to all nonlinear optimization algorithms. This class also contains
* all of those parameters.
*/
class LevenbergMarquardtParams : public SuccessiveLinearizationParams {
public:
/** See LevenbergMarquardtParams::lmVerbosity */
enum LMVerbosity {
SILENT,
LAMBDA,
TRYLAMBDA,
TRYCONFIG,
TRYDELTA,
DAMPED
};
double lambdaInitial; ///< The initial Levenberg-Marquardt damping term (default: 1e-5)
double lambdaFactor; ///< The amount by which to multiply or divide lambda when adjusting lambda (default: 10.0)
double lambdaUpperBound; ///< The maximum lambda to try before assuming the optimization has failed (default: 1e5)
LMVerbosity lmVerbosity; ///< The verbosity level for Levenberg-Marquardt (default: SILENT), see also NonlinearOptimizerParams::verbosity
LevenbergMarquardtParams() :
lambdaInitial(1e-5), lambdaFactor(10.0), lambdaUpperBound(1e5), lmVerbosity(SILENT) {}
virtual ~LevenbergMarquardtParams() {}
virtual void print(const std::string& str = "") const {
SuccessiveLinearizationParams::print(str);
std::cout << " lambdaInitial: " << lambdaInitial << "\n";
std::cout << " lambdaFactor: " << lambdaFactor << "\n";
std::cout << " lambdaUpperBound: " << lambdaUpperBound << "\n";
std::cout.flush();
}
};
/**
* State for LevenbergMarquardtOptimizer
*/
class LevenbergMarquardtState : public NonlinearOptimizerState {
public:
double lambda;
};
}