Intrepid
Intrepid_AdaptiveSparseGridInterfaceDef.hpp
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43
49namespace Intrepid {
50
51template<class Scalar, class UserVector>
53 int dimension,
54 std::vector<EIntrepidBurkardt> rule1D,
55 std::vector<EIntrepidGrowth> growth1D,
56 int maxLevel,
57 bool isNormalized) {
58
59 TEUCHOS_TEST_FOR_EXCEPTION((dimension!=(int)rule1D.size()||
60 dimension!=(int)growth1D.size()),std::out_of_range,
61 ">>> ERROR (AdaptiveSparseGridInterface): Dimension mismatch for inputs.");
62
63 dimension_ = dimension;
64 rule1D_ = rule1D;
65 growth1D_ = growth1D;
66 maxLevel_ = maxLevel;
67 isNormalized_ = isNormalized;
68}
69
70template<class Scalar, class UserVector>
72 std::vector<int> index(dimension_,1);
73 CubatureTensorSorted<Scalar> cubRule(
74 dimension_,index,rule1D_,growth1D_,isNormalized_);
75
76 // Evaluate the initial contribution to the integral
77 initialDiff_ = 1.0;
78 output.Update(-1.0,output);
79 eval_cubature(output,cubRule);
80
81 // Compute the initial error indicator
82 initialDiff_ = error_indicator(output);
83 if (std::abs(initialDiff_)<INTREPID_TOL)
84 initialDiff_ = 1.0;
85}
86
87template<class Scalar, class UserVector>
89 std::vector<int> index) {
90 int dimension = (int)index.size();
91 int sum = 0;
92 for (int i=0; i<dimension; i++) {
93 sum += index[i];
94 }
95 if (sum <= maxLevel_ + dimension - 1)
96 return true;
97 return false;
98}
99
100template<class Scalar, class UserVector>
102 UserVector & output,
103 CubatureTensorSorted<Scalar> & cubRule) {
104
105 //int dimf = 0; // Dimension of the integrand
106 Scalar weight = 0.0;
107 std::vector<Scalar> point(dimension_,(Scalar)0.0);
108 //std::vector<Scalar> f(1,0.0);
109 Teuchos::RCP<UserVector> f = output.Create(); output.Update(-1.0,output);
110
111 typename std::map<std::vector<Scalar>,int>::iterator it;
112 for (it=cubRule.begin(); it!=cubRule.end(); it++) {
113 // Evaluate Function
114 point.assign((it->first).begin(),(it->first).end()); // Extract point
115 f->Update(-1.0,*f);
116 eval_integrand(*f,point); // Evaluate Integrand at point
117
118 // Update integral
119 weight = cubRule.getWeight(it->second);
120 output.Update(weight,*f);
121 }
122}
123
124template<class Scalar, class UserVector>
126 std::vector<EIntrepidBurkardt> & rule1D) {
127 rule1D.clear();
128 rule1D.resize(rule1D_.size());
129 rule1D = rule1D_;
130}
131
132template<class Scalar, class UserVector>
134 std::vector<EIntrepidGrowth> & growth1D) {
135 growth1D.clear();
136 growth1D.resize(growth1D_.size());
137 growth1D = growth1D_;
138}
139
140template<class Scalar, class UserVector>
144
145template<class Scalar, class UserVector>
149
150template<class Scalar, class UserVector>
154
155} // end Intrepid namespace
156
157
158
int getDimension()
Return dimension of integration domain.
virtual bool max_level(std::vector< int > index)
User defined test for maximum level of cubature.
AdaptiveSparseGridInterface(int dimension, std::vector< EIntrepidBurkardt > rule1D, std::vector< EIntrepidGrowth > growth1D, int maxLevel, bool isNormalized)
Constructor starts with index [1,...,1].
void init(UserVector &output)
Compute initial quantities for sparse grid adaptation.
void getGrowth(std::vector< EIntrepidGrowth > &growth1D)
Return user defined 1D growth rules.
bool isNormalized()
Return whether or not cubature weights are normalized.
void getRule(std::vector< EIntrepidBurkardt > &rule1D)
Return user defined 1D quadrature rules.
virtual void eval_cubature(UserVector &output, CubatureTensorSorted< Scalar > &cubRule)
Evaluate the cubature rule.