ROL
ROL_NonlinearCGStep.hpp
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43
44#ifndef ROL_NONLINEARCGSTEP_H
45#define ROL_NONLINEARCGSTEP_H
46
47#include "ROL_Types.hpp"
48#include "ROL_Step.hpp"
49#include "ROL_NonlinearCG.hpp"
50
57namespace ROL {
58
59template <class Real>
60class NonlinearCGStep : public Step<Real> {
61private:
62
63 ROL::Ptr<NonlinearCG<Real> > nlcg_;
66 const bool computeObj_;
67
68 std::string ncgName_;
69
70public:
71
72 using Step<Real>::initialize;
73 using Step<Real>::compute;
74 using Step<Real>::update;
75
85 NonlinearCGStep( ROL::ParameterList &parlist,
86 const ROL::Ptr<NonlinearCG<Real> > &nlcg = ROL::nullPtr,
87 const bool computeObj = true )
88 : Step<Real>(), nlcg_(nlcg), enlcg_(NONLINEARCG_USERDEFINED),
89 verbosity_(0), computeObj_(computeObj) {
90 // Parse ParameterList
91 verbosity_ = parlist.sublist("General").get("Print Verbosity",0);
92 // Initialize secant object
93 ROL::ParameterList& Llist = parlist.sublist("Step").sublist("Line Search");
94 if ( nlcg == ROL::nullPtr ) {
95 ncgName_ = Llist.sublist("Descent Method").get("Nonlinear CG Type","Oren-Luenberger");
96 enlcg_
98 nlcg_ = ROL::makePtr<NonlinearCG<Real>>(enlcg_);
99 }
100 else {
101 ncgName_ = Llist.sublist("Descent Method").get("User Defined Nonlinear CG Name",
102 "Unspecified User Define Nonlinear CG Method");
103 }
104 }
105
108 AlgorithmState<Real> &algo_state ) {
109 ROL::Ptr<StepState<Real> > step_state = Step<Real>::getState();
110 Real one(1);
111
112 // Compute search direction
113 nlcg_->run(s,*(step_state->gradientVec),x,obj);
114 s.scale(-one);
115 }
116
118 AlgorithmState<Real> &algo_state ) {
119 Real tol = std::sqrt(ROL_EPSILON<Real>());
120 ROL::Ptr<StepState<Real> > step_state = Step<Real>::getState();
121
122 // Update iterate
123 algo_state.iter++;
124 x.plus(s);
125 (step_state->descentVec)->set(s);
126 algo_state.snorm = s.norm();
127
128 // Compute new gradient
129 obj.update(x,true,algo_state.iter);
130 if ( computeObj_ ) {
131 algo_state.value = obj.value(x,tol);
132 algo_state.nfval++;
133 }
134 obj.gradient(*(step_state->gradientVec),x,tol);
135 algo_state.ngrad++;
136
137 // Update algorithm state
138 (algo_state.iterateVec)->set(x);
139 algo_state.gnorm = (step_state->gradientVec)->norm();
140 }
141
142 std::string printHeader( void ) const {
143 std::stringstream hist;
144
145 if( verbosity_>0 ) {
146 hist << std::string(109,'-') << "\n";
148 hist << " status output definitions\n\n";
149 hist << " iter - Number of iterates (steps taken) \n";
150 hist << " value - Objective function value \n";
151 hist << " gnorm - Norm of the gradient\n";
152 hist << " snorm - Norm of the step (update to optimization vector)\n";
153 hist << " #fval - Cumulative number of times the objective function was evaluated\n";
154 hist << " #grad - Number of times the gradient was computed\n";
155 hist << std::string(109,'-') << "\n";
156 }
157
158 hist << " ";
159 hist << std::setw(6) << std::left << "iter";
160 hist << std::setw(15) << std::left << "value";
161 hist << std::setw(15) << std::left << "gnorm";
162 hist << std::setw(15) << std::left << "snorm";
163 hist << std::setw(10) << std::left << "#fval";
164 hist << std::setw(10) << std::left << "#grad";
165 hist << "\n";
166 return hist.str();
167 }
168 std::string printName( void ) const {
169 std::stringstream hist;
170 hist << "\n" << ncgName_ << " "
172 return hist.str();
173 }
174 std::string print( AlgorithmState<Real> &algo_state, bool print_header = false ) const {
175 std::stringstream hist;
176 hist << std::scientific << std::setprecision(6);
177 if ( algo_state.iter == 0 ) {
178 hist << printName();
179 }
180 if ( print_header ) {
181 hist << printHeader();
182 }
183 if ( algo_state.iter == 0 ) {
184 hist << " ";
185 hist << std::setw(6) << std::left << algo_state.iter;
186 hist << std::setw(15) << std::left << algo_state.value;
187 hist << std::setw(15) << std::left << algo_state.gnorm;
188 hist << "\n";
189 }
190 else {
191 hist << " ";
192 hist << std::setw(6) << std::left << algo_state.iter;
193 hist << std::setw(15) << std::left << algo_state.value;
194 hist << std::setw(15) << std::left << algo_state.gnorm;
195 hist << std::setw(15) << std::left << algo_state.snorm;
196 hist << std::setw(10) << std::left << algo_state.nfval;
197 hist << std::setw(10) << std::left << algo_state.ngrad;
198 hist << "\n";
199 }
200 return hist.str();
201 }
202}; // class NonlinearCGStep
203
204} // namespace ROL
205
206#endif
Contains definitions of custom data types in ROL.
Provides the interface to apply upper and lower bound constraints.
Provides the interface to compute optimization steps with nonlinear CG.
int verbosity_
Verbosity setting.
std::string printName(void) const
Print step name.
void update(Vector< Real > &x, const Vector< Real > &s, Objective< Real > &obj, BoundConstraint< Real > &con, AlgorithmState< Real > &algo_state)
Update step, if successful.
void compute(Vector< Real > &s, const Vector< Real > &x, Objective< Real > &obj, BoundConstraint< Real > &bnd, AlgorithmState< Real > &algo_state)
Compute step.
std::string print(AlgorithmState< Real > &algo_state, bool print_header=false) const
Print iterate status.
std::string printHeader(void) const
Print iterate header.
NonlinearCGStep(ROL::ParameterList &parlist, const ROL::Ptr< NonlinearCG< Real > > &nlcg=ROL::nullPtr, const bool computeObj=true)
Constructor.
ROL::Ptr< NonlinearCG< Real > > nlcg_
NonlinearCG object (used for quasi-Newton)
Provides the interface to evaluate objective functions.
virtual void gradient(Vector< Real > &g, const Vector< Real > &x, Real &tol)
Compute gradient.
virtual Real value(const Vector< Real > &x, Real &tol)=0
Compute value.
virtual void update(const Vector< Real > &x, UpdateType type, int iter=-1)
Update objective function.
Provides the interface to compute optimization steps.
Definition: ROL_Step.hpp:68
virtual void initialize(Vector< Real > &x, const Vector< Real > &g, Objective< Real > &obj, BoundConstraint< Real > &con, AlgorithmState< Real > &algo_state)
Initialize step with bound constraint.
Definition: ROL_Step.hpp:88
ROL::Ptr< StepState< Real > > getState(void)
Definition: ROL_Step.hpp:73
Defines the linear algebra or vector space interface.
Definition: ROL_Vector.hpp:84
virtual Real norm() const =0
Returns where .
virtual void scale(const Real alpha)=0
Compute where .
virtual void plus(const Vector &x)=0
Compute , where .
ENonlinearCG
Definition: ROL_Types.hpp:566
@ NONLINEARCG_USERDEFINED
Definition: ROL_Types.hpp:576
@ DESCENT_NONLINEARCG
Definition: ROL_Types.hpp:413
std::string EDescentToString(EDescent tr)
Definition: ROL_Types.hpp:420
ENonlinearCG StringToENonlinearCG(std::string s)
Definition: ROL_Types.hpp:638
State for algorithm class. Will be used for restarts.
Definition: ROL_Types.hpp:143
ROL::Ptr< Vector< Real > > iterateVec
Definition: ROL_Types.hpp:157