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#ifndef SimTK_SIMMATH_OPTIMIZER_REP_H_
#define SimTK_SIMMATH_OPTIMIZER_REP_H_
/* -------------------------------------------------------------------------- *
* Simbody(tm): SimTKmath *
* -------------------------------------------------------------------------- *
* This is part of the SimTK biosimulation toolkit originating from *
* Simbios, the NIH National Center for Physics-Based Simulation of *
* Biological Structures at Stanford, funded under the NIH Roadmap for *
* Medical Research, grant U54 GM072970. See https://simtk.org/home/simbody. *
* *
* Portions copyright (c) 2006-13 Stanford University and the Authors. *
* Authors: Jack Middleton *
* Contributors: Michael Sherman *
* *
* Licensed under the Apache License, Version 2.0 (the "License"); you may *
* not use this file except in compliance with the License. You may obtain a *
* copy of the License at http://www.apache.org/licenses/LICENSE-2.0. *
* *
* Unless required by applicable law or agreed to in writing, software *
* distributed under the License is distributed on an "AS IS" BASIS, *
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. *
* See the License for the specific language governing permissions and *
* limitations under the License. *
* -------------------------------------------------------------------------- */
#include "SimTKcommon.h"
#include "simmath/Optimizer.h"
#include "simmath/Differentiator.h"
#include <map>
namespace SimTK {
/* class for Diff jacobian */
class SysObjectiveFunc : public Differentiator::GradientFunction {
public:
SysObjectiveFunc(int ny, const OptimizerSystem* sysPtr )
: Differentiator::GradientFunction(ny) { sysp = sysPtr; }
// Must provide this pure virtual function.
int f(const Vector& y, Real& fy) const override {
return(sysp->objectiveFunc(y, true, fy)); // class user's objectiveFunc
}
const OptimizerSystem* sysp;
};
/* class for Diff gradient */
class SysConstraintFunc : public Differentiator::JacobianFunction {
public:
SysConstraintFunc(int nf, int ny, const OptimizerSystem* sysPtr)
: Differentiator::JacobianFunction(nf,ny) { sysp = sysPtr; }
// Must provide this pure virtual function.
int f(const Vector& y, Vector& fy) const override {
return(sysp->constraintFunc(y, true, fy)); // calls user's contraintFunc
}
const OptimizerSystem* sysp;
};
class SimTK_SIMMATH_EXPORT Optimizer::OptimizerRep {
public:
virtual ~OptimizerRep();
OptimizerRep(const OptimizerSystem& sys)
: sysp(&sys),
myHandle(0),
cf(0),
of(0),
jacDiff(0),
gradDiff(0),
convergenceTolerance(Real(1e-3)),
constraintTolerance(Real(1e-4)),
maxIterations(1000),
limitedMemoryHistory(50),
diagnosticsLevel(0),
diffMethod(Differentiator::CentralDifference),
objectiveEstimatedAccuracy(SignificantReal),
constraintsEstimatedAccuracy(SignificantReal),
numericalGradient(false),
numericalJacobian(false)
{
}
OptimizerRep()
: sysp(0),
myHandle(0),
cf(0),
of(0),
jacDiff(0),
gradDiff(0),
convergenceTolerance(Real(1e-3)),
constraintTolerance(Real(1e-4)),
maxIterations(1000),
limitedMemoryHistory(50),
diagnosticsLevel(0),
diffMethod(Differentiator::CentralDifference),
objectiveEstimatedAccuracy(SignificantReal),
constraintsEstimatedAccuracy(SignificantReal),
numericalGradient(false),
numericalJacobian(false)
{
}
virtual OptimizerRep* clone() const { return 0; };
static bool isAvailable() { return true; }
virtual Real optimize( Vector &results ) = 0;
const OptimizerSystem& getOptimizerSystem() const {return *sysp;}
void setDiagnosticsLevel( const int level );
void setConvergenceTolerance( Real accuracy );
void setConstraintTolerance( Real tolerance );
void setMaxIterations( const int iter );
void setLimitedMemoryHistory( const int history );
bool setAdvancedStrOption( const std::string &option, const std::string &value );
bool setAdvancedRealOption( const std::string &option, const Real value );
bool setAdvancedIntOption( const std::string &option, const int value );
bool setAdvancedBoolOption( const std::string &option, const bool value );
bool setAdvancedVectorOption( const std::string &option, const Vector value );
bool getAdvancedStrOption( const std::string &option, std::string &value ) const;
bool getAdvancedRealOption( const std::string &option, Real &value ) const;
bool getAdvancedIntOption( const std::string &option, int &value ) const;
bool getAdvancedBoolOption( const std::string &option, bool &value ) const;
bool getAdvancedVectorOption( const std::string &option, Vector &value ) const;
void setMyHandle(Optimizer& cp) {myHandle = &cp;}
const Optimizer& getMyHandle() const {assert(myHandle); return *myHandle;}
void clearMyHandle() {myHandle=0;}
void useNumericalGradient(bool flag, Real objEstAccuracy);
void useNumericalJacobian(bool flag, Real consEstAccuracy);
void setDifferentiatorMethod( Differentiator::Method method);
bool isUsingNumericalGradient() const { return numericalGradient; }
bool isUsingNumericalJacobian() const { return numericalJacobian; }
Differentiator::Method getDifferentiatorMethod() const {return diffMethod;}
Real getEstimatedAccuracyOfObjective() const
{ return objectiveEstimatedAccuracy; }
Real getEstimatedAccuracyOfConstraints() const
{ return constraintsEstimatedAccuracy; }
const Differentiator& getGradientDifferentiator() const {
assert(gradDiff);
return *gradDiff;
}
const Differentiator& getJacobianDifferentiator() const {
assert(jacDiff);
return *jacDiff;
}
virtual OptimizerAlgorithm getAlgorithm() const {
return UnknownOptimizerAlgorithm;
}
static int numericalGradient_static( const OptimizerSystem&, const Vector & parameters, const bool new_parameters, Vector &gradient );
static int numericalJacobian_static(const OptimizerSystem&,
const Vector& parameters, const bool new_parameters, Matrix& jacobian );
protected:
// These methods are to be called by derived classes as an interface
// to the OptimizerSystem virtuals. The signature must match that required by
// IpOpt's matching callbacks. We're using the "user data" argument to pass in
// the current OptimizerRep, making these behave like non-static members.
static int objectiveFuncWrapper ( int n, const Real* x, int new_x, Real* f, void* rep);
static int gradientFuncWrapper ( int n, const Real* x, int new_x, Real* gradient, void* rep);
static int constraintFuncWrapper( int n, const Real* x, int new_x, int m, Real* g, void* rep);
static int constraintJacobianWrapper( int n, const Real* x, int new_x,int m, int nele_jac,
int* iRow, int* jCol, Real* values, void* rep);
static int hessianWrapper( int n, const Real* x, int new_x, Real obj_factor,
int m, Real* lambda, int new_lambda,
int nele_hess, int* iRow, int* jCol,
Real* values, void* rep);
int diagnosticsLevel;
Real convergenceTolerance;
Real constraintTolerance;
int maxIterations;
int limitedMemoryHistory;
Differentiator::Method diffMethod;
Real objectiveEstimatedAccuracy;
Real constraintsEstimatedAccuracy;
private:
const OptimizerSystem* sysp;
bool numericalGradient; // true if optimizer will compute an numerical gradient
bool numericalJacobian; // true if optimizer will compute an numerical Jacobian
Differentiator *gradDiff;
Differentiator *jacDiff;
SysObjectiveFunc *of;
SysConstraintFunc *cf;
std::map<std::string, std::string> advancedStrOptions;
std::map<std::string, Real> advancedRealOptions;
std::map<std::string, int> advancedIntOptions;
std::map<std::string, bool> advancedBoolOptions;
std::map<std::string, Vector> advancedVectorOptions;
friend class Optimizer;
Optimizer* myHandle; // The owner handle of this Rep.
}; // end class OptimizerRep
class DefaultOptimizer: public Optimizer::OptimizerRep {
Real optimize( Vector &results ) override;
OptimizerRep* clone() const override;
OptimizerAlgorithm getAlgorithm() const override;
};
} // namespace SimTK
#endif // SimTK_SIMMATH_OPTIMIZER_REP_H_
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