ROL
ROL_CoherentEntropicRisk.hpp
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43
44#ifndef ROL_COHERENTEXPUTILITY_HPP
45#define ROL_COHERENTEXPUTILITY_HPP
46
48
64namespace ROL {
65
66template<class Real>
68private:
69 Real dval1_;
70 Real dval2_;
71 Real dval3_;
72
73 using RandVarFunctional<Real>::val_;
74 using RandVarFunctional<Real>::gv_;
75 using RandVarFunctional<Real>::g_;
76 using RandVarFunctional<Real>::hv_;
78
80
85
86public:
88 dval1_(0), dval2_(0), dval3_(0) {}
89
90 void initialize(const Vector<Real> &x) {
92 Real zero(0);
94 }
95
97 const Vector<Real> &x,
98 const std::vector<Real> &xstat,
99 Real &tol) {
100 Real val = computeValue(obj,x,tol);
101 val_ += weight_ * std::exp(val/xstat[0]);
102 }
103
104 Real getValue(const Vector<Real> &x,
105 const std::vector<Real> &xstat,
106 SampleGenerator<Real> &sampler) {
107 Real ev(0);
108 sampler.sumAll(&val_,&ev,1);
109 return xstat[0]*std::log(ev);
110 }
111
113 const Vector<Real> &x,
114 const std::vector<Real> &xstat,
115 Real &tol) {
116 Real val = computeValue(obj,x,tol);
117 Real ev = std::exp(val/xstat[0]);
118 val_ += weight_ * ev;
119 gv_ += weight_ * ev * val;
120 computeGradient(*dualVector_,obj,x,tol);
121 g_->axpy(weight_*ev,*dualVector_);
122 }
123
125 std::vector<Real> &gstat,
126 const Vector<Real> &x,
127 const std::vector<Real> &xstat,
128 SampleGenerator<Real> &sampler) {
129 const Real one(1);
130 // Perform sum over batches
131 std::vector<Real> myval(2,0), val(2,0);
132 myval[0] = val_;
133 myval[1] = gv_;
134 sampler.sumAll(&myval[0],&val[0],2);
135
136 sampler.sumAll(*g_,g);
137 g.scale(one/val[0]);
138 gstat[0] = std::log(val[0]) - val[1]/(val[0]*xstat[0]);
139 }
140
142 const Vector<Real> &v,
143 const std::vector<Real> &vstat,
144 const Vector<Real> &x,
145 const std::vector<Real> &xstat,
146 Real &tol) {
147 Real val = computeValue(obj,x,tol);
148 Real ev = std::exp(val/xstat[0]);
149 val_ += weight_ * ev;
150
151 Real gv = computeGradVec(*dualVector_,obj,v,x,tol);
152 gv_ += weight_ * ev * gv;
153 g_->axpy(weight_*ev,*dualVector_);
154 hv_->axpy(weight_*ev*(gv-val*vstat[0]/xstat[0])/xstat[0],*dualVector_);
155
156 dval1_ += weight_ * ev * val;
157 dval2_ += weight_ * ev * val * val;
158 dval3_ += weight_ * ev * val * gv;
159
160 computeHessVec(*dualVector_,obj,v,x,tol);
161 hv_->axpy(weight_*ev,*dualVector_);
162 }
163
165 std::vector<Real> &hvstat,
166 const Vector<Real> &v,
167 const std::vector<Real> &vstat,
168 const Vector<Real> &x,
169 const std::vector<Real> &xstat,
170 SampleGenerator<Real> &sampler) {
171 const Real one(1);
172 std::vector<Real> myval(5,0), val(5,0);
173 myval[0] = val_;
174 myval[1] = gv_;
175 myval[2] = dval1_;
176 myval[3] = dval2_;
177 myval[4] = dval3_;
178 sampler.sumAll(&myval[0],&val[0],5);
179
180 Real xs2 = xstat[0]*xstat[0];
181 Real xs3 = xs2*xstat[0];
182 Real v02 = val[0]*val[0];
183 Real h11 = (val[3]*val[0] - val[2]*val[2])/(v02*xs3) * vstat[0];
184 Real h12 = (val[1]*val[2] - val[4]*val[0])/(v02*xs2);
185 hvstat[0] = h11+h12;
186 sampler.sumAll(*hv_,hv);
187 hv.scale(one/val[0]);
188
189 dualVector_->zero();
190 sampler.sumAll(*g_,*dualVector_);
191 hv.axpy((vstat[0]*val[2]/xs2-val[1]/xstat[0])/v02,*dualVector_);
192 }
193};
194
195}
196
197#endif
Objective_SerialSimOpt(const Ptr< Obj > &obj, const V &ui) z0_ zero()
Provides the interface for the coherent entropic risk measure.
Real getValue(const Vector< Real > &x, const std::vector< Real > &xstat, SampleGenerator< Real > &sampler)
Return risk measure value.
void getGradient(Vector< Real > &g, std::vector< Real > &gstat, const Vector< Real > &x, const std::vector< Real > &xstat, SampleGenerator< Real > &sampler)
Return risk measure (sub)gradient.
void getHessVec(Vector< Real > &hv, std::vector< Real > &hvstat, const Vector< Real > &v, const std::vector< Real > &vstat, const Vector< Real > &x, const std::vector< Real > &xstat, SampleGenerator< Real > &sampler)
Return risk measure Hessian-times-a-vector.
void updateHessVec(Objective< Real > &obj, const Vector< Real > &v, const std::vector< Real > &vstat, const Vector< Real > &x, const std::vector< Real > &xstat, Real &tol)
Update internal risk measure storage for Hessian-time-a-vector computation.
void updateGradient(Objective< Real > &obj, const Vector< Real > &x, const std::vector< Real > &xstat, Real &tol)
Update internal risk measure storage for gradient computation.
void initialize(const Vector< Real > &x)
Initialize temporary variables.
void updateValue(Objective< Real > &obj, const Vector< Real > &x, const std::vector< Real > &xstat, Real &tol)
Update internal storage for value computation.
Provides the interface to evaluate objective functions.
Provides the interface to implement any functional that maps a random variable to a (extended) real n...
Real computeValue(Objective< Real > &obj, const Vector< Real > &x, Real &tol)
Ptr< Vector< Real > > g_
virtual void initialize(const Vector< Real > &x)
Initialize temporary variables.
void computeHessVec(Vector< Real > &hv, Objective< Real > &obj, const Vector< Real > &v, const Vector< Real > &x, Real &tol)
Ptr< Vector< Real > > hv_
void computeGradient(Vector< Real > &g, Objective< Real > &obj, const Vector< Real > &x, Real &tol)
Ptr< Vector< Real > > dualVector_
Real computeGradVec(Vector< Real > &g, Objective< Real > &obj, const Vector< Real > &v, const Vector< Real > &x, Real &tol)
void sumAll(Real *input, Real *output, int dim) const
Defines the linear algebra or vector space interface.
Definition: ROL_Vector.hpp:84
virtual void scale(const Real alpha)=0
Compute where .
virtual void axpy(const Real alpha, const Vector &x)
Compute where .
Definition: ROL_Vector.hpp:153