ROL
ROL_NewtonStep.hpp
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1 // @HEADER
2 // *****************************************************************************
3 // Rapid Optimization Library (ROL) Package
4 //
5 // Copyright 2014 NTESS and the ROL contributors.
6 // SPDX-License-Identifier: BSD-3-Clause
7 // *****************************************************************************
8 // @HEADER
9 
10 #ifndef ROL_NEWTONSTEP_H
11 #define ROL_NEWTONSTEP_H
12 
13 #include "ROL_Types.hpp"
14 #include "ROL_Step.hpp"
15 
22 namespace ROL {
23 
24 template <class Real>
25 class NewtonStep : public Step<Real> {
26 private:
27 
29  const bool computeObj_;
30 
31 public:
32 
34  using Step<Real>::compute;
35  using Step<Real>::update;
36 
44  NewtonStep( ROL::ParameterList &parlist, const bool computeObj = true )
45  : Step<Real>(), verbosity_(0), computeObj_(computeObj) {
46  // Parse ParameterList
47  verbosity_ = parlist.sublist("General").get("Print Verbosity",0);
48  }
49 
50  void compute( Vector<Real> &s, const Vector<Real> &x,
52  AlgorithmState<Real> &algo_state ) {
53  ROL::Ptr<StepState<Real> > step_state = Step<Real>::getState();
54  Real tol = std::sqrt(ROL_EPSILON<Real>()), one(1);
55 
56  // Compute unconstrained step
57  obj.invHessVec(s,*(step_state->gradientVec),x,tol);
58  s.scale(-one);
59  }
60 
62  AlgorithmState<Real> &algo_state ) {
63  Real tol = std::sqrt(ROL_EPSILON<Real>());
64  ROL::Ptr<StepState<Real> > step_state = Step<Real>::getState();
65 
66  // Update iterate
67  algo_state.iter++;
68  x.plus(s);
69  (step_state->descentVec)->set(s);
70  algo_state.snorm = s.norm();
71 
72  // Compute new gradient
73  obj.update(x,true,algo_state.iter);
74  if ( computeObj_ ) {
75  algo_state.value = obj.value(x,tol);
76  algo_state.nfval++;
77  }
78  obj.gradient(*(step_state->gradientVec),x,tol);
79  algo_state.ngrad++;
80 
81  // Update algorithm state
82  (algo_state.iterateVec)->set(x);
83  algo_state.gnorm = (step_state->gradientVec)->norm();
84  }
85 
86  std::string printHeader( void ) const {
87  std::stringstream hist;
88 
89  if( verbosity_>0 ) {
90  hist << std::string(109,'-') << "\n";
92  hist << " status output definitions\n\n";
93  hist << " iter - Number of iterates (steps taken) \n";
94  hist << " value - Objective function value \n";
95  hist << " gnorm - Norm of the gradient\n";
96  hist << " snorm - Norm of the step (update to optimization vector)\n";
97  hist << " #fval - Cumulative number of times the objective function was evaluated\n";
98  hist << " #grad - Number of times the gradient was computed\n";
99  hist << std::string(109,'-') << "\n";
100  }
101 
102  hist << " ";
103  hist << std::setw(6) << std::left << "iter";
104  hist << std::setw(15) << std::left << "value";
105  hist << std::setw(15) << std::left << "gnorm";
106  hist << std::setw(15) << std::left << "snorm";
107  hist << std::setw(10) << std::left << "#fval";
108  hist << std::setw(10) << std::left << "#grad";
109  hist << "\n";
110  return hist.str();
111  }
112  std::string printName( void ) const {
113  std::stringstream hist;
114  hist << "\n" << EDescentToString(DESCENT_NEWTON) << "\n";
115  return hist.str();
116  }
117  std::string print( AlgorithmState<Real> &algo_state, bool print_header = false ) const {
118  std::stringstream hist;
119  hist << std::scientific << std::setprecision(6);
120  if ( algo_state.iter == 0 ) {
121  hist << printName();
122  }
123  if ( print_header ) {
124  hist << printHeader();
125  }
126  if ( algo_state.iter == 0 ) {
127  hist << " ";
128  hist << std::setw(6) << std::left << algo_state.iter;
129  hist << std::setw(15) << std::left << algo_state.value;
130  hist << std::setw(15) << std::left << algo_state.gnorm;
131  hist << "\n";
132  }
133  else {
134  hist << " ";
135  hist << std::setw(6) << std::left << algo_state.iter;
136  hist << std::setw(15) << std::left << algo_state.value;
137  hist << std::setw(15) << std::left << algo_state.gnorm;
138  hist << std::setw(15) << std::left << algo_state.snorm;
139  hist << std::setw(10) << std::left << algo_state.nfval;
140  hist << std::setw(10) << std::left << algo_state.ngrad;
141  hist << "\n";
142  }
143  return hist.str();
144  }
145 }; // class Step
146 
147 } // namespace ROL
148 
149 #endif
Provides the interface to evaluate objective functions.
NewtonStep(ROL::ParameterList &parlist, const bool computeObj=true)
Constructor.
virtual void scale(const Real alpha)=0
Compute where .
virtual void plus(const Vector &x)=0
Compute , where .
virtual Real value(const Vector< Real > &x, Real &tol)=0
Compute value.
Provides the interface to compute optimization steps.
Definition: ROL_Step.hpp:34
Contains definitions of custom data types in ROL.
std::string EDescentToString(EDescent tr)
Definition: ROL_Types.hpp:386
Defines the linear algebra or vector space interface.
Definition: ROL_Vector.hpp:46
virtual void update(const Vector< Real > &x, UpdateType type, int iter=-1)
Update objective function.
std::string printName(void) const
Print step name.
Provides the interface to compute optimization steps with Newton&#39;s method globalized using line searc...
State for algorithm class. Will be used for restarts.
Definition: ROL_Types.hpp:109
virtual void gradient(Vector< Real > &g, const Vector< Real > &x, Real &tol)
Compute gradient.
ROL::Ptr< StepState< Real > > getState(void)
Definition: ROL_Step.hpp:39
void compute(Vector< Real > &s, const Vector< Real > &x, Objective< Real > &obj, BoundConstraint< Real > &bnd, AlgorithmState< Real > &algo_state)
Compute step.
ROL::Ptr< Vector< Real > > iterateVec
Definition: ROL_Types.hpp:123
virtual void invHessVec(Vector< Real > &hv, const Vector< Real > &v, const Vector< Real > &x, Real &tol)
Apply inverse Hessian approximation to vector.
Provides the interface to apply upper and lower bound constraints.
void update(Vector< Real > &x, const Vector< Real > &s, Objective< Real > &obj, BoundConstraint< Real > &con, AlgorithmState< Real > &algo_state)
Update step, if successful.
virtual Real norm() const =0
Returns where .
std::string print(AlgorithmState< Real > &algo_state, bool print_header=false) const
Print iterate status.
const bool computeObj_
std::string printHeader(void) const
Print iterate header.