ROL
ROL_SecantStep.hpp
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43 
44 #ifndef ROL_SECANTSTEP_H
45 #define ROL_SECANTSTEP_H
46 
47 #include "ROL_Types.hpp"
48 #include "ROL_Step.hpp"
49 #include "ROL_Secant.hpp"
50 
57 namespace ROL {
58 
59 template <class Real>
60 class SecantStep : public Step<Real> {
61 private:
62 
63  ROL::Ptr<Secant<Real> > secant_;
65  ROL::Ptr<Vector<Real> > gp_;
66  int verbosity_;
68 
69  std::string secantName_;
70 
71 public:
72 
74  using Step<Real>::compute;
75  using Step<Real>::update;
76 
86  SecantStep( ROL::ParameterList &parlist,
87  const ROL::Ptr<Secant<Real> > &secant = ROL::nullPtr,
88  const bool computeObj = true )
89  : Step<Real>(), secant_(secant), esec_(SECANT_USERDEFINED),
90  gp_(ROL::nullPtr), verbosity_(0), computeObj_(computeObj) {
91  // Parse ParameterList
92  verbosity_ = parlist.sublist("General").get("Print Verbosity",0);
93  // Initialize secant object
94  if ( secant == ROL::nullPtr ) {
95  secantName_ = parlist.sublist("General").sublist("Secant").get("Type","Limited-Memory BFGS");
97  secant_ = SecantFactory<Real>(parlist);
98  }
99  else {
100  secantName_ = parlist.sublist("General").sublist("Secant").get("User Defined Secant Name",
101  "Unspecified User Defined Secant Method");
102  }
103  }
104 
105  void initialize( Vector<Real> &x, const Vector<Real> &s, const Vector<Real> &g,
107  AlgorithmState<Real> &algo_state ) {
108  Step<Real>::initialize(x,s,g,obj,con,algo_state);
109  gp_ = g.clone();
110  }
111 
112  void compute( Vector<Real> &s, const Vector<Real> &x,
114  AlgorithmState<Real> &algo_state ) {
115  Real one(1);
116  ROL::Ptr<StepState<Real> > step_state = Step<Real>::getState();
117 
118  // Compute search direction
119  secant_->applyH(s,*(step_state->gradientVec));
120  s.scale(-one);
121  }
122 
124  AlgorithmState<Real> &algo_state ) {
125  Real tol = std::sqrt(ROL_EPSILON<Real>());
126  ROL::Ptr<StepState<Real> > step_state = Step<Real>::getState();
127 
128  // Update iterate
129  algo_state.iter++;
130  x.plus(s);
131  (step_state->descentVec)->set(s);
132  algo_state.snorm = s.norm();
133 
134  // Compute new gradient
135  gp_->set(*(step_state->gradientVec));
136  obj.update(x,true,algo_state.iter);
137  if ( computeObj_ ) {
138  algo_state.value = obj.value(x,tol);
139  algo_state.nfval++;
140  }
141  obj.gradient(*(step_state->gradientVec),x,tol);
142  algo_state.ngrad++;
143 
144  // Update Secant Information
145  secant_->updateStorage(x,*(step_state->gradientVec),*gp_,s,algo_state.snorm,algo_state.iter+1);
146 
147  // Update algorithm state
148  (algo_state.iterateVec)->set(x);
149  algo_state.gnorm = (step_state->gradientVec)->norm();
150  }
151 
152  std::string printHeader( void ) const {
153  std::stringstream hist;
154 
155  if( verbosity_>0 ) {
156  hist << std::string(109,'-') << "\n";
158  hist << " status output definitions\n\n";
159  hist << " iter - Number of iterates (steps taken) \n";
160  hist << " value - Objective function value \n";
161  hist << " gnorm - Norm of the gradient\n";
162  hist << " snorm - Norm of the step (update to optimization vector)\n";
163  hist << " #fval - Cumulative number of times the objective function was evaluated\n";
164  hist << " #grad - Number of times the gradient was computed\n";
165  hist << std::string(109,'-') << "\n";
166  }
167 
168  hist << " ";
169  hist << std::setw(6) << std::left << "iter";
170  hist << std::setw(15) << std::left << "value";
171  hist << std::setw(15) << std::left << "gnorm";
172  hist << std::setw(15) << std::left << "snorm";
173  hist << std::setw(10) << std::left << "#fval";
174  hist << std::setw(10) << std::left << "#grad";
175  hist << "\n";
176  return hist.str();
177  }
178  std::string printName( void ) const {
179  std::stringstream hist;
180  hist << "\n" << EDescentToString(DESCENT_SECANT);
181  hist << " with " << secantName_ << "\n";
182  return hist.str();
183  }
184  std::string print( AlgorithmState<Real> &algo_state, bool print_header = false ) const {
185  std::stringstream hist;
186  hist << std::scientific << std::setprecision(6);
187  if ( algo_state.iter == 0 ) {
188  hist << printName();
189  }
190  if ( print_header ) {
191  hist << printHeader();
192  }
193  if ( algo_state.iter == 0 ) {
194  hist << " ";
195  hist << std::setw(6) << std::left << algo_state.iter;
196  hist << std::setw(15) << std::left << algo_state.value;
197  hist << std::setw(15) << std::left << algo_state.gnorm;
198  hist << "\n";
199  }
200  else {
201  hist << " ";
202  hist << std::setw(6) << std::left << algo_state.iter;
203  hist << std::setw(15) << std::left << algo_state.value;
204  hist << std::setw(15) << std::left << algo_state.gnorm;
205  hist << std::setw(15) << std::left << algo_state.snorm;
206  hist << std::setw(10) << std::left << algo_state.nfval;
207  hist << std::setw(10) << std::left << algo_state.ngrad;
208  hist << "\n";
209  }
210  return hist.str();
211  }
212 }; // class SecantStep
213 
214 } // namespace ROL
215 
216 #endif
Provides the interface to evaluate objective functions.
void initialize(Vector< Real > &x, const Vector< Real > &s, const Vector< Real > &g, Objective< Real > &obj, BoundConstraint< Real > &con, AlgorithmState< Real > &algo_state)
Initialize step with bound constraint.
std::string secantName_
virtual void scale(const Real alpha)=0
Compute where .
virtual ROL::Ptr< Vector > clone() const =0
Clone to make a new (uninitialized) vector.
void update(Vector< Real > &x, const Vector< Real > &s, Objective< Real > &obj, BoundConstraint< Real > &con, AlgorithmState< Real > &algo_state)
Update step, if successful.
virtual void plus(const Vector &x)=0
Compute , where .
SecantStep(ROL::ParameterList &parlist, const ROL::Ptr< Secant< Real > > &secant=ROL::nullPtr, const bool computeObj=true)
Constructor.
virtual Real value(const Vector< Real > &x, Real &tol)=0
Compute value.
Provides the interface to compute optimization steps.
Definition: ROL_Step.hpp:69
Contains definitions of custom data types in ROL.
ESecant StringToESecant(std::string s)
Definition: ROL_Types.hpp:541
std::string EDescentToString(EDescent tr)
Definition: ROL_Types.hpp:418
Defines the linear algebra or vector space interface.
Definition: ROL_Vector.hpp:80
State for algorithm class. Will be used for restarts.
Definition: ROL_Types.hpp:143
virtual void gradient(Vector< Real > &g, const Vector< Real > &x, Real &tol)
Compute gradient.
ESecant
Enumeration of secant update algorithms.
Definition: ROL_Types.hpp:484
std::string printHeader(void) const
Print iterate header.
ROL::Ptr< StepState< Real > > getState(void)
Definition: ROL_Step.hpp:74
Provides interface for and implements limited-memory secant operators.
Definition: ROL_Secant.hpp:70
ROL::Ptr< Vector< Real > > iterateVec
Definition: ROL_Types.hpp:157
std::string printName(void) const
Print step name.
void compute(Vector< Real > &s, const Vector< Real > &x, Objective< Real > &obj, BoundConstraint< Real > &bnd, AlgorithmState< Real > &algo_state)
Compute step.
Provides the interface to apply upper and lower bound constraints.
int verbosity_
Verbosity setting.
ROL::Ptr< Secant< Real > > secant_
Secant object (used for quasi-Newton)
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:89
std::string print(AlgorithmState< Real > &algo_state, bool print_header=false) const
Print iterate status.
virtual Real norm() const =0
Returns where .
ROL::Ptr< Vector< Real > > gp_
Additional vector storage.
virtual void update(const Vector< Real > &x, bool flag=true, int iter=-1)
Update objective function.
Provides the interface to compute optimization steps with a secant method.