ROL
ROL_PH_ProbObjective.hpp
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44#ifndef PH_PROBOBJECTIVE_H
45#define PH_PROBOBJECTIVE_H
46
47#include "ROL_Objective.hpp"
48
55namespace ROL {
56
57template <class Real>
58class PH_ProbObjective : public Objective<Real> {
59private:
60 const Ptr<Objective<Real>> obj_;
62 Real eps_;
63
65 Real val_;
66
69 Ptr<Vector<Real>> g_;
70
71 void getValue(const Vector<Real> &x, Real &tol) {
72 if (!isValueComputed_) {
73 val_ = obj_->value(x,tol);
74 isValueComputed_ = true;
75 }
76 }
77
78 void getGradient(const Vector<Real> &x, Real &tol) {
80 g_ = x.dual().clone();
82 }
84 obj_->gradient(*g_,x,tol);
86 }
87 }
88
89 Real smoothHeaviside(const Real x, const int deriv = 0) const {
90 const Real one(1), two(2);
91 Real val(0);
92 if (deriv == 0) {
93 Real ex = std::exp(-two*x/eps_);
94 val = one/(one+ex);
95 }
96 else if (deriv == 1) {
97 Real ex = std::exp(-two*x/eps_);
98 val = (two/eps_)*ex/std::pow(one+ex,2);
99 }
100 else if (deriv == 2) {
101 Real ex = std::exp(two*x/eps_);
102 val = std::pow(two/eps_,2)*ex*(one-ex)/std::pow(one+ex,3);
103 }
104 return val;
105 }
106
107public:
108
110 ParameterList &parlist)
111 : obj_(obj),
112 isValueComputed_(false),
114 isGradientComputed_(false) {
115 ParameterList &list = parlist.sublist("SOL").sublist("Probability").sublist("Smoothed POE");
116 threshold_ = list.get<Real>("Threshold");
117 eps_ = list.get<Real>("Smoothing Parameter");
118 }
119
120 void update( const Vector<Real> &x, bool flag = true, int iter = -1 ) {
121 obj_->update(x,flag,iter);
122 isValueComputed_ = false;
123 isGradientComputed_ = false;
124 }
125
126 Real value( const Vector<Real> &x, Real &tol ) {
127 getValue(x,tol);
128 Real prob = smoothHeaviside(val_-threshold_,0);
129 if (std::abs(prob) > ROL_EPSILON<Real>()) {
130 return prob;
131 }
132 return static_cast<Real>(0);
133 }
134
135 void gradient( Vector<Real> &g, const Vector<Real> &x, Real &tol ) {
136 getValue(x,tol);
137 Real prob = smoothHeaviside(val_-threshold_,1);
138 if (std::abs(prob) > ROL_EPSILON<Real>()) {
139 getGradient(x,tol);
140 g.set(*g_); g.scale(prob);
141 }
142 else {
143 g.zero();
144 }
145 }
146
147 void hessVec( Vector<Real> &hv, const Vector<Real> &v, const Vector<Real> &x, Real &tol ) {
148 getValue(x,tol);
149 Real prob1 = smoothHeaviside(val_-threshold_,1);
150 Real prob2 = smoothHeaviside(val_-threshold_,2);
151 if (std::abs(prob1) > ROL_EPSILON<Real>()) {
152 obj_->hessVec(hv,v,x,tol);
153 hv.scale(prob1);
154 }
155 else {
156 hv.zero();
157 }
158 if (std::abs(prob2) > ROL_EPSILON<Real>()) {
159 getGradient(x,tol);
160 //Real gv = v.dot(g_->dual());
161 Real gv = v.apply(*g_);
162 hv.axpy(prob2*gv,*g_);
163 }
164 }
165
166 void setParameter(const std::vector<Real> &param) {
167 obj_->setParameter(param);
169 }
170
171};
172
173}
174#endif
Provides the interface to evaluate objective functions.
virtual void setParameter(const std::vector< Real > &param)
Provides the interface for the progressive hedging probability objective.
Real smoothHeaviside(const Real x, const int deriv=0) const
void getValue(const Vector< Real > &x, Real &tol)
Real value(const Vector< Real > &x, Real &tol)
Compute value.
void getGradient(const Vector< Real > &x, Real &tol)
const Ptr< Objective< Real > > obj_
Ptr< Vector< Real > > g_
void update(const Vector< Real > &x, bool flag=true, int iter=-1)
Update objective function.
void setParameter(const std::vector< Real > &param)
void hessVec(Vector< Real > &hv, const Vector< Real > &v, const Vector< Real > &x, Real &tol)
Apply Hessian approximation to vector.
PH_ProbObjective(const Ptr< Objective< Real > > &obj, ParameterList &parlist)
void gradient(Vector< Real > &g, const Vector< Real > &x, Real &tol)
Compute gradient.
Defines the linear algebra or vector space interface.
virtual Real apply(const Vector< Real > &x) const
Apply to a dual vector. This is equivalent to the call .
virtual void set(const Vector &x)
Set where .
virtual void scale(const Real alpha)=0
Compute where .
virtual const Vector & dual() const
Return dual representation of , for example, the result of applying a Riesz map, or change of basis,...
virtual void zero()
Set to zero vector.
virtual ROL::Ptr< Vector > clone() const =0
Clone to make a new (uninitialized) vector.
virtual void axpy(const Real alpha, const Vector &x)
Compute where .