1#ifndef SimTK_SIMMATH_OPTIMIZER_H_
2#define SimTK_SIMMATH_OPTIMIZER_H_
74 numEqualityConstraints(0),
75 numInequalityConstraints(0),
76 numLinearEqualityConstraints(0),
77 numLinearInequalityConstraints(0),
85 setNumParameters(nParameters);
99 bool new_parameters,
Real& f )
const {
106 bool new_parameters,
Vector &gradient )
const {
112 bool new_parameters,
Vector & constraints )
const {
118 bool new_parameters,
Matrix& jac )
const {
124 bool new_parameters,
Vector &gradient)
const {
130 if( nParameters < 1 ) {
131 const char* where =
" OptimizerSystem Constructor";
132 const char* szName =
"number of parameters";
135 numParameters = nParameters;
141 const char* where =
" OptimizerSystem setNumEqualityConstraints";
142 const char* szName =
"number of equality constraints";
145 numEqualityConstraints = n;
151 const char* where =
" OptimizerSystem setNumInequalityConstraints";
152 const char* szName =
"number of inequality constraints";
155 numInequalityConstraints = n;
160 if( n < 0 || n > numEqualityConstraints ) {
161 const char* where =
" OptimizerSystem setNumLinearEqualityConstraints";
162 const char* szName =
"number of linear equality constraints";
165 numLinearEqualityConstraints = n;
170 if( n < 0 || n > numInequalityConstraints ) {
171 const char* where =
" OptimizerSystem setNumLinearInequalityConstraints";
172 const char* szName =
"number of linear inequality constraints";
175 numLinearInequalityConstraints = n;
180 if( upper.
size() != numParameters && upper.
size() != 0) {
181 const char* where =
" OptimizerSystem setParametersLimits";
182 const char* szName =
"upper limits length";
185 if( lower.
size() != numParameters && lower.
size() != 0 ) {
186 const char* where =
" OptimizerSystem setParametersLimits";
187 const char* szName =
"lower limits length";
197 if( upper.
size() == 0 ) {
200 lowerLimits =
new Vector( lower );
201 upperLimits =
new Vector( upper );
230 *lower = &(*lowerLimits)[0];
231 *upper = &(*upperLimits)[0];
236 int numEqualityConstraints;
237 int numInequalityConstraints;
238 int numLinearEqualityConstraints;
239 int numLinearInequalityConstraints;
500 Real estimatedAccuracyOfObjective = SignificantReal);
514 Real estimatedAccuracyOfConstraints = SignificantReal);
538 const OptimizerRep& getRep()
const {assert(rep);
return *rep;}
539 OptimizerRep& updRep() {assert(rep);
return *rep;}
This is the header file that user code should include to pick up the SimTK Simmath numerical differen...
#define SimTK_THROW2(exc, a1, a2)
Definition Exception.h:318
#define SimTK_THROW5(exc, a1, a2, a3, a4, a5)
Definition Exception.h:324
#define SimTK_THROW3(exc, a1, a2, a3)
Definition Exception.h:320
#define SimTK_THROW4(exc, a1, a2, a3, a4)
Definition Exception.h:322
Includes internal headers providing declarations for the basic SimTK Core classes,...
This is the header file that every Simmath compilation unit should include first.
#define SimTK_SIMMATH_EXPORT
Definition SimTKmath/include/simmath/internal/common.h:64
Method
Definition Differentiator.h:92
Definition SimTKmath/include/simmath/internal/common.h:122
Definition Exception.h:175
Definition Exception.h:190
Definition Exception.h:248
Definition Exception.h:205
Abstract class which defines an objective/cost function which is optimized by and Optimizer object.
Definition Optimizer.h:71
void setNumEqualityConstraints(const int n)
Sets the number of equality constraints.
Definition Optimizer.h:139
void getParameterLimits(Real **lower, Real **upper) const
Returns the limits on the allowed values of each parameter, as an array of lower bounds and an array ...
Definition Optimizer.h:229
int getNumConstraints() const
Returns the total number of constraints.
Definition Optimizer.h:210
virtual int hessian(const Vector ¶meters, bool new_parameters, Vector &gradient) const
Computes Hessian of the objective function; return 0 when successful.
Definition Optimizer.h:123
void setNumParameters(const int nParameters)
Sets the number of parameters in the objective function.
Definition Optimizer.h:129
int getNumLinearEqualityConstraints() const
Returns the number of linear equality constraints.
Definition Optimizer.h:216
int getNumLinearInequalityConstraints() const
Returns the number of linear inequality constraints.
Definition Optimizer.h:220
int getNumInequalityConstraints() const
Returns the number of inequality constraints.
Definition Optimizer.h:214
void setNumInequalityConstraints(const int n)
Sets the number of inequality constraints.
Definition Optimizer.h:149
void setNumLinearEqualityConstraints(const int n)
Sets the number of lineaer equality constraints.
Definition Optimizer.h:159
void setNumLinearInequalityConstraints(const int n)
Sets the number of lineaer inequality constraints.
Definition Optimizer.h:169
OptimizerSystem()
Definition Optimizer.h:73
virtual int constraintJacobian(const Vector ¶meters, bool new_parameters, Matrix &jac) const
Computes Jacobian of the constraints; return 0 when successful.
Definition Optimizer.h:117
void setParameterLimits(const Vector &lower, const Vector &upper)
Set the upper and lower bounds on the parameters.
Definition Optimizer.h:179
virtual ~OptimizerSystem()
Definition Optimizer.h:88
bool getHasLimits() const
Returns true if there are limits on the parameters.
Definition Optimizer.h:225
int getNumEqualityConstraints() const
Returns the number of equality constraints.
Definition Optimizer.h:212
OptimizerSystem(int nParameters)
Definition Optimizer.h:83
virtual int gradientFunc(const Vector ¶meters, bool new_parameters, Vector &gradient) const
Computes the gradient of the objective function; return 0 when successful.
Definition Optimizer.h:105
virtual int constraintFunc(const Vector ¶meters, bool new_parameters, Vector &constraints) const
Computes the value of the constraints; return 0 when successful.
Definition Optimizer.h:111
int getNumNonlinearInequalityConstraints() const
Returns the number of linear inequality constraints.
Definition Optimizer.h:222
int getNumParameters() const
Returns the number of parameters, that is, the number of variables that the Optimizer may adjust whil...
Definition Optimizer.h:208
int getNumNonlinearEqualityConstraints() const
Returns the number of nonlinear equality constraints.
Definition Optimizer.h:218
virtual int objectiveFunc(const Vector ¶meters, bool new_parameters, Real &f) const
Objective/cost function which is to be optimized; return 0 when successful.
Definition Optimizer.h:98
Definition OptimizerRep.h:63
API for SimTK Simmath's optimizers.
Definition Optimizer.h:421
void setOptimizerSystem(const OptimizerSystem &sys)
bool setAdvancedVectorOption(const char *option, const Vector value)
Set the value of an advanced option specified by an Vector value.
Real getEstimatedAccuracyOfObjective() const
Return the estimated accuracy last specified in useNumericalGradient().
Real getEstimatedAccuracyOfConstraints() const
Return the estimated accuracy last specified in useNumericalJacobian().
static bool isAlgorithmAvailable(OptimizerAlgorithm algorithm)
BestAvailable, UnknownAlgorithm, and UserSuppliedAlgorithm are treated as never available.
void setConstraintTolerance(Real tolerance)
Sets the absolute tolerance used to determine whether constraint violation is acceptable.
bool setAdvancedBoolOption(const char *option, const bool value)
Set the value of an advanced option specified by an boolean value.
Real optimize(Vector &)
Compute optimization.
Optimizer(const OptimizerSystem &sys)
void setConvergenceTolerance(Real accuracy)
Sets the relative accuracy used determine if the problem has converged.
void setOptimizerSystem(const OptimizerSystem &sys, OptimizerAlgorithm algorithm)
Differentiator::Method getDifferentiatorMethod() const
Return the differentiation method last supplied in a call to setDifferentiatorMethod(),...
bool isUsingNumericalGradient() const
Indicate whether the Optimizer is currently set to use a numerical gradient.
const OptimizerSystem & getOptimizerSystem() const
Return a reference to the OptimizerSystem currently associated with this Optimizer.
void useNumericalGradient(bool flag, Real estimatedAccuracyOfObjective=SignificantReal)
Enable numerical calculation of gradient, with optional estimation of the accuracy to which the objec...
bool setAdvancedIntOption(const char *option, const int value)
Set the value of an advanced option specified by an integer value.
void setMaxIterations(int iter)
Set the maximum number of iterations allowed of the optimization method's outer stepping loop.
bool setAdvancedRealOption(const char *option, const Real value)
Set the value of an advanced option specified by a real value.
bool setAdvancedStrOption(const char *option, const char *value)
Set the value of an advanced option specified by a string.
OptimizerAlgorithm getAlgorithm() const
Return the algorithm used for the optimization.
void setLimitedMemoryHistory(int history)
Set the maximum number of previous hessians used in a limited memory hessian approximation.
Optimizer(const OptimizerSystem &sys, OptimizerAlgorithm algorithm)
void setDiagnosticsLevel(int level)
Set the level of debugging info displayed.
bool isUsingNumericalJacobian() const
Indicate whether the Optimizer is currently set to use a numerical Jacobian.
void setDifferentiatorMethod(Differentiator::Method method)
Set which numerical differentiation algorithm is to be used for the next useNumericalGradient() or us...
void useNumericalJacobian(bool flag, Real estimatedAccuracyOfConstraints=SignificantReal)
Enable numerical calculation of the constraint Jacobian, with optional estimation of the accuracy to ...
int size() const
Definition VectorBase.h:396
This is the top-level SimTK namespace into which all SimTK names are placed to avoid collision with o...
Definition Assembler.h:37
OptimizerAlgorithm
The available Optimizer algorithms.
Definition Optimizer.h:40
@ InteriorPoint
IpOpt algorithm (https://projects.coin-or.org/ipopt); gradient descent.
Definition Optimizer.h:45
@ CMAES
Covariance matrix adaptation, evolution strategy (https://github.com/cma-es/c-cmaes); this is a rando...
Definition Optimizer.h:60
@ UserSuppliedOptimizerAlgorithm
An algorithm that is implemented outside of Simmath.
Definition Optimizer.h:63
@ BestAvailable
Simmath will select best Optimizer based on problem type.
Definition Optimizer.h:42
@ LBFGS
Limited-memory Broyden-Fletcher-Goldfarb-Shanno algorithm; gradient descent.
Definition Optimizer.h:48
@ LBFGSB
LBFGS with simple bound constraints; gradient descent.
Definition Optimizer.h:51
@ UnknownOptimizerAlgorithm
Definition Optimizer.h:61
@ CFSQP
C implementation of sequential quadratic programming (requires external library: ftp://frcatel....
Definition Optimizer.h:56
SimTK_Real Real
This is the default compiled-in floating point type for SimTK, either float or double.
Definition SimTKcommon/include/SimTKcommon/internal/common.h:606