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Added support for SPCG in matlab wrapper

release/4.3a0
Richard Roberts 2012-07-24 15:48:33 +00:00
parent 592fa95d66
commit 6bee17b603
6 changed files with 49 additions and 6 deletions
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15
gtsam.h
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@ -1209,13 +1209,22 @@ virtual class NonlinearOptimizerParams {
virtual class SuccessiveLinearizationParams : gtsam::NonlinearOptimizerParams {
SuccessiveLinearizationParams();
string getLinearSolverType() const;
void setLinearSolverType(string solver);
void setOrdering(const gtsam::Ordering& ordering);
bool isMultifrontal() const;
bool isSequential() const;
bool isCholmod() const;
bool isCG() const;
};
#include <gtsam/nonlinear/GaussNewtonOptimizer.h>
virtual class GaussNewtonParams : gtsam::SuccessiveLinearizationParams {
GaussNewtonParams();
};
#include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
virtual class LevenbergMarquardtParams : gtsam::SuccessiveLinearizationParams {
LevenbergMarquardtParams();
@ -1243,6 +1252,7 @@ virtual class DoglegParams : gtsam::SuccessiveLinearizationParams {
};
virtual class NonlinearOptimizer {
gtsam::Values optimize();
gtsam::Values optimizeSafely();
double error() const;
int iterations() const;
@ -1250,6 +1260,11 @@ virtual class NonlinearOptimizer {
void iterate() const;
};
virtual class GaussNewtonOptimizer : gtsam::NonlinearOptimizer {
GaussNewtonOptimizer(const gtsam::NonlinearFactorGraph& graph, const gtsam::Values& initialValues);
GaussNewtonOptimizer(const gtsam::NonlinearFactorGraph& graph, const gtsam::Values& initialValues, const gtsam::GaussNewtonParams& params);
};
virtual class DoglegOptimizer : gtsam::NonlinearOptimizer {
DoglegOptimizer(const gtsam::NonlinearFactorGraph& graph, const gtsam::Values& initialValues);
DoglegOptimizer(const gtsam::NonlinearFactorGraph& graph, const gtsam::Values& initialValues, const gtsam::DoglegParams& params);

1
gtsam/nonlinear/DoglegOptimizer.h
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@ -57,6 +57,7 @@ public:
void setDeltaInitial(double deltaInitial) { this->deltaInitial = deltaInitial; }
void setVerbosityDL(const std::string& verbosityDL) { this->verbosityDL = verbosityDLTranslator(verbosityDL); }
private:
VerbosityDL verbosityDLTranslator(const std::string& verbosityDL) const;
std::string verbosityDLTranslator(VerbosityDL verbosityDL) const;
};

2
gtsam/nonlinear/EasyFactorGraph.cpp
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@ -44,7 +44,7 @@ namespace gtsam {
size_t verbosity) const {
LevenbergMarquardtParams p;
p.verbosity = (NonlinearOptimizerParams::Verbosity) verbosity;
p.linearSolverType = SuccessiveLinearizationParams::CG;
p.linearSolverType = SuccessiveLinearizationParams::CONJUGATE_GRADIENT;
p.iterativeParams = boost::make_shared<SimpleSPCGSolverParameters>();
return optimizer(initialEstimate, p).optimizeSafely();
}

1
gtsam/nonlinear/LevenbergMarquardtOptimizer.h
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@ -61,6 +61,7 @@ public:
inline void setlambdaUpperBound(double value) { lambdaUpperBound = value; }
inline void setVerbosityLM(const std::string &s) { verbosityLM = verbosityLMTranslator(s); }
private:
VerbosityLM verbosityLMTranslator(const std::string &s) const;
std::string verbosityLMTranslator(VerbosityLM value) const;
};

1
gtsam/nonlinear/NonlinearOptimizer.h
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@ -63,6 +63,7 @@ public:
void setErrorTol(double value) { errorTol = value ; }
void setVerbosity(const std::string &src) { verbosity = verbosityTranslator(src); }
private:
Verbosity verbosityTranslator(const std::string &s) const;
std::string verbosityTranslator(Verbosity value) const;
};

35
gtsam/nonlinear/SuccessiveLinearizationOptimizer.h
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@ -31,7 +31,7 @@ public:
MULTIFRONTAL_QR,
SEQUENTIAL_CHOLESKY,
SEQUENTIAL_QR,
CG, /* Experimental Flag */
CONJUGATE_GRADIENT, /* Experimental Flag */
CHOLMOD, /* Experimental Flag */
};
@ -61,7 +61,7 @@ public:
case CHOLMOD:
std::cout << " linear solver type: CHOLMOD\n";
break;
case CG:
case CONJUGATE_GRADIENT:
std::cout << " linear solver type: CG\n";
break;
default:
@ -85,9 +85,7 @@ public:
inline bool isCholmod() const { return (linearSolverType == CHOLMOD); }
inline bool isCG() const { return (linearSolverType == CG); }
void setOrdering(const Ordering& ordering) { this->ordering = ordering; }
inline bool isCG() const { return (linearSolverType == CONJUGATE_GRADIENT); }
GaussianFactorGraph::Eliminate getEliminationFunction() {
switch (linearSolverType) {
@ -105,6 +103,33 @@ public:
break;
}
}
std::string getLinearSolverType() const { return linearSolverTranslator(linearSolverType); }
void setLinearSolverType(const std::string& solver) { linearSolverType = linearSolverTranslator(solver); }
void setOrdering(const Ordering& ordering) { this->ordering = ordering; }
private:
std::string linearSolverTranslator(LinearSolverType linearSolverType) const {
switch(linearSolverType) {
case MULTIFRONTAL_CHOLESKY: return "MULTIFRONTAL_CHOLESKY";
case MULTIFRONTAL_QR: return "MULTIFRONTAL_QR";
case SEQUENTIAL_CHOLESKY: return "SEQUENTIAL_CHOLESKY";
case SEQUENTIAL_QR: return "SEQUENTIAL_QR";
case CONJUGATE_GRADIENT: return "CONJUGATE_GRADIENT";
case CHOLMOD: return "CHOLMOD";
default: throw std::invalid_argument("Unknown linear solver type in SuccessiveLinearizationOptimizer");
}
}
LinearSolverType linearSolverTranslator(const std::string& linearSolverType) const {
if(linearSolverType == "MULTIFRONTAL_CHOLESKY") return MULTIFRONTAL_CHOLESKY;
if(linearSolverType == "MULTIFRONTAL_QR") return MULTIFRONTAL_QR;
if(linearSolverType == "SEQUENTIAL_CHOLESKY") return SEQUENTIAL_CHOLESKY;
if(linearSolverType == "SEQUENTIAL_QR") return SEQUENTIAL_QR;
if(linearSolverType == "CONJUGATE_GRADIENT") return CONJUGATE_GRADIENT;
if(linearSolverType == "CHOLMOD") return CHOLMOD;
throw std::invalid_argument("Unknown linear solver type in SuccessiveLinearizationOptimizer");
}
};
} /* namespace gtsam */