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fix iterative parameters

release/4.3a0
Yong-Dian Jian 2012-06-06 05:17:39 +00:00
parent 0f079b70f2
commit 0e4f2b414c
4 changed files with 31 additions and 147 deletions
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156
gtsam/linear/IterativeOptimizationParameters.h
View File

@ -17,125 +17,29 @@
#pragma once #pragma once
#include <string>
#include <iostream>
#include <boost/shared_ptr.hpp> #include <boost/shared_ptr.hpp>
#include <iostream>
#include <string>
namespace gtsam { namespace gtsam {
/* parameters for combinatorial preconditioner */
struct CombinatorialParameters {
enum Group { /* group of variables */
BLOCK = 0, /* utilize the inherent block structure */
SCALAR /* break the block variables into scalars */
} group_;
enum Type { /* subgraph specification */
JACOBI = 0, /* block diagonal */
SPTREE, /* spanning tree */
GSP, /* gspn, n = 0: all factors, n = 1: all unary factors, n = 2: spanning tree, etc .. */
KOUTIS, /* implement Koutis2011Focs */
} type_;
enum Weight { /* how to weigh the graph edges */
EQUAL = 0, /* 0: every block edge has equal weight */
RHS_2NORM, /* 1: use the 2-norm of the rhs */
LHS_FNORM, /* 2: use the frobenius norm of the lhs */
RAW, /* 3: use raw scalar weight for the scalar case */
} weight_ ;
int complexity_;/* a parameter for the subgraph complexity */
int hessian_; /* 0: do nothing, 1: use whole block hessian */
CombinatorialParameters(): group_(BLOCK), type_(JACOBI), weight_(EQUAL), complexity_(0), hessian_(1) {}
CombinatorialParameters(Group group, Type type, Weight weight, int complexity, int hessian)
: group_(group), type_(type), weight_(weight), complexity_(complexity), hessian_(hessian) {}
inline Group group() const { return group_; }
inline Type type() const { return type_; }
inline Weight weight() const { return weight_; }
inline int complexity() const { return complexity_; }
inline int hessian() const { return hessian_; }
inline bool isScalar() const { return group_ == SCALAR; }
inline bool isBlock() const { return group_ == BLOCK; }
inline bool isStatic() const { return (type_ == JACOBI || weight_ == EQUAL) ? true : false;}
inline bool isDynamic() const { return !isStatic(); }
inline void print() const {
const std::string groupStr[2] = {"block", "scalar"};
const std::string typeStr[4] = {"jacobi", "sptree", "gsp", "koutis"};
const std::string weightStr[4] = {"equal", "rhs-2norm", "lhs-form", "raw"};
std::cout << "CombinatorialParameters: "
<< "group = " << groupStr[group_]
<< ", type = " << typeStr[type_]
<< ", weight = " << weightStr[weight_]
<< ", complexity = " << complexity_
<< ", hessian = " << hessian_ << std::endl;
}
};
/* parameters for the preconditioner */
struct PreconditionerParameters {
typedef boost::shared_ptr<PreconditionerParameters> shared_ptr;
enum Kernel { /* Preconditioner Kernel */
GTSAM = 0, /* Jacobian Factor Graph of GTSAM */
CHOLMOD /* Cholmod Sparse */
} kernel_ ;
enum Type { /* preconditioner type */
Combinatorial = 0 /* combinatorial preconditioner */
} type_;
CombinatorialParameters combinatorial_;
enum Verbosity { SILENT = 0, COMPLEXITY = 1, ERROR = 2} verbosity_ ; /* Verbosity */
PreconditionerParameters(): kernel_(GTSAM), type_(Combinatorial), verbosity_(SILENT) {}
PreconditionerParameters(Kernel kernel, const CombinatorialParameters &combinatorial, Verbosity verbosity)
: kernel_(kernel), type_(Combinatorial), combinatorial_(combinatorial), verbosity_(verbosity) {}
/* general interface */
inline Kernel kernel() const { return kernel_; }
inline Type type() const { return type_; }
inline const CombinatorialParameters & combinatorial() const { return combinatorial_; }
inline Verbosity verbosity() const { return verbosity_; }
void print() const {
const std::string kernelStr[2] = {"gtsam", "cholmod"};
const std::string typeStr[1] = {"combinatorial"};
std::cout << "PreconditionerParameters: "
<< "kernel = " << kernelStr[kernel_]
<< ", type = " << typeStr[type_]
<< ", verbosity = " << verbosity_
<< std::endl;
combinatorial_.print();
}
};
/* parameters for the conjugate gradient method */ /* parameters for the conjugate gradient method */
struct ConjugateGradientParameters { struct ConjugateGradientParameters {
size_t minIterations_; /* minimum number of cg iterations */ size_t minIterations_; ///< minimum number of cg iterations
size_t maxIterations_; /* maximum number of cg iterations */ size_t maxIterations_; ///< maximum number of cg iterations
size_t reset_; /* number of iterations before reset */ size_t reset_; ///< number of iterations before reset
double epsilon_rel_; /* threshold for relative error decrease */ double epsilon_rel_; ///< threshold for relative error decrease
double epsilon_abs_; /* threshold for absolute error decrease */ double epsilon_abs_; ///< threshold for absolute error decrease
enum BLASKernel { /* Matrix Operation Kernel */ /* Matrix Operation Kernel */
GTSAM = 0, /* Jacobian Factor Graph of GTSAM */ enum BLASKernel {
SBM, /* Sparse Block Matrix */ GTSAM = 0, ///< Jacobian Factor Graph of GTSAM
SBM_MT /* Sparse Block Matrix Multithreaded */ SBM, ///< Sparse Block Matrix
SBM_MT ///< Sparse Block Matrix Multithreaded
} blas_kernel_; } blas_kernel_;
size_t degree_; /* the maximum degree of the vertices to be eliminated before doing cg */ size_t degree_; ///< the maximum degree of the vertices to be eliminated before doing cg
enum Verbosity { SILENT = 0, COMPLEXITY = 1, ERROR = 2} verbosity_ ; /* Verbosity */ enum Verbosity { SILENT = 0, COMPLEXITY = 1, ERROR = 2} verbosity_ ; /* Verbosity */
@ -160,7 +64,7 @@ struct ConjugateGradientParameters {
inline Verbosity verbosity() const { return verbosity_; } inline Verbosity verbosity() const { return verbosity_; }
void print() const { void print() const {
const std::string blasStr[4] = {"gtsam", "sbm", "sbm-mt"}; const std::string blasStr[3] = {"gtsam", "sbm", "sbm-mt"};
std::cout << "ConjugateGradientParameters: " std::cout << "ConjugateGradientParameters: "
<< "blas = " << blasStr[blas_kernel_] << "blas = " << blasStr[blas_kernel_]
<< ", minIter = " << minIterations_ << ", minIter = " << minIterations_
@ -175,42 +79,34 @@ struct ConjugateGradientParameters {
}; };
/* parameters for iterative linear solvers */ /* parameters for iterative linear solvers */
struct IterativeOptimizationParameters { class IterativeOptimizationParameters {
public: public:
typedef boost::shared_ptr<IterativeOptimizationParameters> shared_ptr; typedef boost::shared_ptr<IterativeOptimizationParameters> shared_ptr;
PreconditionerParameters preconditioner_; ConjugateGradientParameters cg_; ///< Parameters for the Conjugate Gradient Method
ConjugateGradientParameters cg_;
enum Kernel { PCG = 0, LSPCG = 1 } kernel_ ; ///< Iterative Method Kernel enum Kernel { PCG = 0, LSPCG = 1 } kernel_ ; ///< Iterative Method Kernel
enum Verbosity { SILENT = 0, COMPLEXITY = 1, ERROR = 2} verbosity_ ; ///< Verbosity enum Verbosity { SILENT = 0, COMPLEXITY = 1, ERROR = 2} verbosity_ ; ///< Verbosity
public: public:
IterativeOptimizationParameters() IterativeOptimizationParameters() : cg_(), kernel_(LSPCG), verbosity_(SILENT) {}
: preconditioner_(), cg_(), kernel_(LSPCG), verbosity_(SILENT) {}
IterativeOptimizationParameters(const IterativeOptimizationParameters &p) : IterativeOptimizationParameters(const IterativeOptimizationParameters &p)
preconditioner_(p.preconditioner_), cg_(p.cg_), kernel_(p.kernel_), verbosity_(p.verbosity_) {} : cg_(p.cg_), kernel_(p.kernel_), verbosity_(p.verbosity_) {}
IterativeOptimizationParameters( IterativeOptimizationParameters(const ConjugateGradientParameters &c, Kernel kernel = LSPCG, Verbosity verbosity = SILENT)
const PreconditionerParameters &p, const ConjugateGradientParameters &c, Kernel kernel = PCG, Verbosity verbosity = SILENT) : cg_(c), kernel_(kernel), verbosity_(verbosity) {}
: preconditioner_(p), cg_(c), kernel_(kernel), verbosity_(verbosity) {}
virtual ~IterativeOptimizationParameters() {}
/* general interface */ /* general interface */
inline Kernel kernel() const { return kernel_; } inline Kernel kernel() const { return kernel_; }
inline Verbosity verbosity() const { return verbosity_; } inline Verbosity verbosity() const { return verbosity_; }
/* utility */
inline const PreconditionerParameters& preconditioner() const { return preconditioner_; }
inline const ConjugateGradientParameters& cg() const { return cg_; }
/* interface to preconditioner parameters */
inline PreconditionerParameters::Kernel preconditioner_kernel() const { return preconditioner_.kernel(); }
inline PreconditionerParameters::Type type() const { return preconditioner_.type(); }
/* interface to cg parameters */ /* interface to cg parameters */
inline const ConjugateGradientParameters& cg() const { return cg_; }
inline size_t minIterations() const { return cg_.minIterations(); } inline size_t minIterations() const { return cg_.minIterations(); }
inline size_t maxIterations() const { return cg_.maxIterations(); } inline size_t maxIterations() const { return cg_.maxIterations(); }
inline size_t reset() const { return cg_.reset(); } inline size_t reset() const { return cg_.reset(); }
@ -220,15 +116,13 @@ public:
inline size_t degree() const { return cg_.degree(); } inline size_t degree() const { return cg_.degree(); }
inline ConjugateGradientParameters::BLASKernel blas_kernel() const { return cg_.blas_kernel(); } inline ConjugateGradientParameters::BLASKernel blas_kernel() const { return cg_.blas_kernel(); }
void print(const std::string &s="") const { virtual void print(const std::string &s="") const {
const std::string kernelStr[2] = {"pcg", "lspcg"}; const std::string kernelStr[2] = {"pcg", "lspcg"};
std::cout << s << std::endl std::cout << s << std::endl
<< "IterativeOptimizationParameters: " << "IterativeOptimizationParameters: "
<< "kernel = " << kernelStr[kernel_] << "kernel = " << kernelStr[kernel_]
<< ", verbosity = " << verbosity_ << std::endl; << ", verbosity = " << verbosity_ << std::endl;
cg_.print(); cg_.print();
preconditioner_.print();
} }
}; };

16
gtsam/linear/IterativeSolver.h
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@ -20,23 +20,11 @@ class IterativeSolver {
public: public:
typedef IterativeOptimizationParameters Parameters; IterativeSolver(){}
protected:
Parameters parameters_ ;
public:
IterativeSolver(): parameters_() {}
IterativeSolver(const IterativeSolver &solver) : parameters_(solver.parameters_) {}
IterativeSolver(const Parameters &parameters) : parameters_(parameters) {}
virtual ~IterativeSolver() {} virtual ~IterativeSolver() {}
virtual VectorValues::shared_ptr optimize () = 0; virtual VectorValues::shared_ptr optimize () = 0;
virtual const IterativeOptimizationParameters& _params() const = 0;
inline const Parameters& parameters() const { return parameters_ ; }
}; };
} }

2
gtsam/linear/SimpleSPCGSolver.cpp
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@ -43,7 +43,7 @@ std::vector<size_t> extractColSpec_(const FactorGraph<GaussianFactor>& gfg, cons
} }
SimpleSPCGSolver::SimpleSPCGSolver(const GaussianFactorGraph &gfg, const Parameters &parameters) SimpleSPCGSolver::SimpleSPCGSolver(const GaussianFactorGraph &gfg, const Parameters &parameters)
: Base(parameters) : Base(), parameters_(parameters)
{ {
std::vector<size_t> colSpec = extractColSpec_(gfg, VariableIndex(gfg)); std::vector<size_t> colSpec = extractColSpec_(gfg, VariableIndex(gfg));

4
gtsam/linear/SimpleSPCGSolver.h
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@ -39,6 +39,7 @@ class SimpleSPCGSolver : public IterativeSolver {
public: public:
typedef IterativeSolver Base; typedef IterativeSolver Base;
typedef IterativeOptimizationParameters Parameters;
typedef boost::shared_ptr<IterativeSolver> shared_ptr; typedef boost::shared_ptr<IterativeSolver> shared_ptr;
protected: protected:
@ -52,12 +53,14 @@ protected:
VectorValues::shared_ptr by_; ///< \f$ [\bar{b_y} ; 0 ] \f$ VectorValues::shared_ptr by_; ///< \f$ [\bar{b_y} ; 0 ] \f$
VectorValues::shared_ptr tmpY_; ///< buffer for the column vectors VectorValues::shared_ptr tmpY_; ///< buffer for the column vectors
VectorValues::shared_ptr tmpB_; ///< buffer for the row vectors VectorValues::shared_ptr tmpB_; ///< buffer for the row vectors
Parameters parameters_; ///< Parameters for iterative method
public: public:
SimpleSPCGSolver(const GaussianFactorGraph &gfg, const Parameters &parameters); SimpleSPCGSolver(const GaussianFactorGraph &gfg, const Parameters &parameters);
virtual ~SimpleSPCGSolver() {} virtual ~SimpleSPCGSolver() {}
virtual VectorValues::shared_ptr optimize () {return optimize(*y0_);} virtual VectorValues::shared_ptr optimize () {return optimize(*y0_);}
virtual const IterativeOptimizationParameters& _params() const { return parameters_; }
protected: protected:
@ -85,7 +88,6 @@ protected:
* Note: This function has to be refined for your graph/application */ * Note: This function has to be refined for your graph/application */
boost::tuple<GaussianFactorGraph::shared_ptr, FactorGraph<JacobianFactor>::shared_ptr> boost::tuple<GaussianFactorGraph::shared_ptr, FactorGraph<JacobianFactor>::shared_ptr>
splitGraph(const GaussianFactorGraph &gfg); splitGraph(const GaussianFactorGraph &gfg);
}; };
} }