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NLPInterfacePack_NLPObjGrad.cpp
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41 
44 
45 namespace {
46  const char name_Gf[] = "Gf";
47 } // end namespace
48 
49 namespace NLPInterfacePack {
50 
51 // constructors
52 
54  : Gf_(NULL)
55 {}
56 
57 void NLPObjGrad::initialize(bool test_setup) {
58  num_Gf_evals_ = 0;
59  NLP::initialize(test_setup);
60 }
61 
62 // Information
63 
65 {
66  return true;
67 }
68 
70 {
71  return false;
72 }
73 
74 // <<std aggr>> members for Gf
75 
76 void NLPObjGrad::set_Gf(VectorMutable* Gf)
77 {
78  Gf_ = Gf;
79 }
80 
82 {
84 }
85 
87 {
89 }
90 
92 {
94 }
95 
97 {
99  Gf_ = NULL;
100 }
101 
102 // calculations
103 
104 void NLPObjGrad::calc_Gf(const Vector& x, bool newx) const
105 {
107  imp_calc_Gf(x,newx,obj_grad_info());
108  num_Gf_evals_++;
109 }
110 
111 value_type NLPObjGrad::calc_Gf_prod(const Vector& x, const Vector& d, bool newx) const
112 {
114  true,std::logic_error
115  ,"Error, the function calc_Gf_prod(...) is not implemented for the class "
116  << typeName(*this) << "!"
117  );
118 
119  //execution should never reach this point, but compilers expect a non-void
120  //function to return something. So we'll create a dummy value to use in a
121  //return statement.
122  //(a better design would not require function bodies for unimplemented
123  //functions like this...)
124  value_type* dummy = NULL;
125  return(*dummy);
126 }
127 
129 {
130  return num_Gf_evals_;
131 }
132 
133 } // end namespace NLPInterfacePack
void initialize(bool test_setup)
Initialize the NLP for its first use.
void unset_quantities()
Call to unset all storage quantities (both in this class and all subclasses).
AbstractLinAlgPack::size_type size_type
std::string typeName(const T &t)
Abstract interface for immutable, finite dimensional, coordinate vectors {abstract}.
virtual size_type num_Gf_evals() const
Objective gradient evaluations count.
#define TEUCHOS_TEST_FOR_EXCEPTION(throw_exception_test, Exception, msg)
const ObjGradInfo obj_grad_info() const
Return objective gradient and zero order information.
NLPObjGrad()
Initialize to no reference set to calculation quanities.
virtual VectorMutable * get_Gf()
Return pointer passed to this->set_Gf().
virtual void unset_quantities()
Call to unset all storage quantities (both in this class and all subclasses).
ContainedClass * get_role_name(ContainedClass *role_name_, bool owns_role_name_, const char name[])
virtual bool supports_Gf_prod() const
Determine if the objective gradient product is supported or not.
virtual void imp_calc_Gf(const Vector &x, bool newx, const ObjGradInfo &obj_grad_info) const =0
Overridden to compute f(x) and perhaps c(x) (if multiple calculaiton = true).
void assert_role_name_set(const ContainedClass *role_name_, const char func_name[], const char name[])
Assert that the reference is set.
ContainedClass & role_name(ContainedClass *role_name_, bool owns_role_name_, const char name[])
AbstractLinAlgPack::value_type value_type
Abstract interface for mutable coordinate vectors {abstract}.
virtual VectorMutable & Gf()
Returns non-const *this->get_Gf().
virtual void initialize(bool test_setup=false)
Initialize the NLP before it is used.
virtual void set_Gf(VectorMutable *Gf)
Set a pointer to a vector to be updated when this->calc_Gf() is called.
virtual void calc_Gf(const Vector &x, bool newx=true) const
Update the vector for Gf at the point x and put it in the stored reference.
virtual bool supports_Gf() const
Determine if the objective gradient is supported or not.
virtual value_type calc_Gf_prod(const Vector &x, const Vector &d, bool newx=true) const
Calculate the inner product Gf(x)'*d at the point x and put it in the stored reference.