ROL
ROL_LinearRegression.hpp
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43 
44 #ifndef ROL_LINEARREGRESSION_H
45 #define ROL_LINEARREGRESSION_H
46 
47 #include "ROL_RegressionError.hpp"
48 #include "ROL_SampleGenerator.hpp"
54 
63 namespace ROL {
64 
65 template <class Real>
67 private:
68  const Ptr<RegressionError<Real>> error_;
69  const Ptr<SampleGenerator<Real>> data_;
70 
71  Ptr<RandVarFunctional<Real>> em_;
72  Ptr<StochasticObjective<Real>> obj_;
73  Ptr<std::vector<Real>> cdata_;
74  Ptr<RiskVector<Real>> c_;
75 
76  Ptr<std::vector<Real>> lower_;
77  Ptr<std::vector<Real>> upper_;
78  Ptr<BoundConstraint<Real>> bnd_;
79  Ptr<RiskBoundConstraint<Real>> rbnd_;
80 
82 
83 public:
85  : error_(makePtr<RegressionError<Real>>()), data_(data),
86  lower_(nullPtr), upper_(nullPtr), bnd_(nullPtr), rbnd_(nullPtr),
87  initialized_(false) {
88  int dim = data_->getMyPoint(0).size();
89  cdata_ = makePtr<std::vector<Real>>(dim,0);
90  c_ = makePtr<RiskVector<Real>>(makePtr<StdVector<Real>>(cdata_));
91  }
92 
93  void setErrorMeasure(ROL::ParameterList &parlist, bool reset = false) {
94  if (!initialized_ || reset) {
95  em_ = ErrorMeasureFactory<Real>(parlist);
96  obj_ = makePtr<StochasticObjective<Real>>(error_,em_,data_);
97  initialized_ = true;
98  }
99  }
100 
101  void setLowerBound(const std::vector<Real> &lower) {
102  lower_ = makePtr<std::vector<Real>>(lower);
103  }
104 
105  void setUpperBound(const std::vector<Real> &upper) {
106  upper_ = makePtr<std::vector<Real>>(upper);
107  }
108 
109  void reset(void) {
110  c_->zero();
111  initialized_ = false;
112  }
113 
114  const Ptr<OptimizationProblem<Real>> getOptimizationProblem(void) {
115  if (!initialized_) {
116  throw Exception::NotImplemented("ROL::LinearRegression::getOptimizationProblem : setErrorMeasure was not called!");
117  }
118  if (lower_ != nullPtr && upper_ == nullPtr) {
119  bnd_ = makePtr<StdBoundConstraint<Real>>(*lower_,true);
120  }
121  if (lower_ == nullPtr && upper_ != nullPtr) {
122  bnd_ = makePtr<StdBoundConstraint<Real>>(*upper_,false);
123  }
124  if (lower_ != nullPtr && upper_ != nullPtr) {
125  bnd_ = makePtr<StdBoundConstraint<Real>>(*lower_,*upper_);
126  }
127  if (bnd_ != nullPtr) {
128  rbnd_ = makePtr<RiskBoundConstraint<Real>>(bnd_);
129  return makePtr<OptimizationProblem<Real>>(obj_,c_,rbnd_);
130  }
131  return makePtr<OptimizationProblem<Real>>(obj_,c_);
132  }
133 
134  const Ptr<std::vector<Real>> getCoefficients(void) const {
135  return cdata_;
136  }
137 
138  void print(std::ostream &out = std::cout, const std::string delim = " ") const {
139  int dim = cdata_->size();
140  out << std::endl;
141  for (int i = 0; i < dim; ++i) {
142  out << delim << (*cdata_)[i];
143  }
144  out << std::endl << std::endl;
145  }
146 }; // class LinearRegression
147 
148 } // namespace ROL
149 
150 #endif
Contains definitions for std::vector bound constraints.
void setUpperBound(const std::vector< Real > &upper)
Provides the interface to evaluate linear regression error.
Ptr< RiskVector< Real > > c_
Ptr< BoundConstraint< Real > > bnd_
Ptr< RiskBoundConstraint< Real > > rbnd_
void print(std::ostream &out=std::cout, const std::string delim=" ") const
Provides the interface to construct linear regression problem.
Ptr< std::vector< Real > > upper_
void setLowerBound(const std::vector< Real > &lower)
Ptr< std::vector< Real > > cdata_
void setErrorMeasure(ROL::ParameterList &parlist, bool reset=false)
Ptr< std::vector< Real > > lower_
const Ptr< OptimizationProblem< Real > > getOptimizationProblem(void)
const Ptr< RegressionError< Real > > error_
LinearRegression(const Ptr< SampleGenerator< Real >> &data)
const Ptr< SampleGenerator< Real > > data_
const Ptr< std::vector< Real > > getCoefficients(void) const
Ptr< StochasticObjective< Real > > obj_
Ptr< RandVarFunctional< Real > > em_