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Toolkit for Adaptive Stochastic Modeling and Non-Intrusive ApproximatioN: Tasmanian v8.2 (development)
tsgSequenceOptimizer.hpp
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30 
31 #ifndef __TASMANIAN_SPARSE_GRID_SEQUENCE_OPTIMIZER_HPP
32 #define __TASMANIAN_SPARSE_GRID_SEQUENCE_OPTIMIZER_HPP
33 
34 #include "tsgEnumerates.hpp"
35 
62 namespace TasGrid{
63 
64 namespace Optimizer{
65 
72  double node;
74  double value;
75 };
76 
81 template<TypeOneDRule rule> double getNextNode(std::vector<double> const &nodes);
82 
90 std::vector<double> getPrecomputedMinLebesgueNodes();
98 std::vector<double> getPrecomputedMinDeltaNodes();
99 
104 template<TypeOneDRule rule> std::vector<double> getGreedyNodes(int n);
105 
106 }
107 
108 }
109 
110 #endif
std::vector< double > getPrecomputedMinLebesgueNodes()
Get the hard-coded pre-computed nodes.
Definition: tsgSequenceOptimizer.cpp:422
std::vector< double > getGreedyNodes(int n)
Get n nodes for the given sequence rule, either compute or use pre-computed.
Definition: tsgSequenceOptimizer.cpp:550
double getNextNode(std::vector< double > const &nodes)
For the given rule and set of nodes, compute the next node using the greedy procedure.
Definition: tsgSequenceOptimizer.cpp:540
std::vector< double > getPrecomputedMinDeltaNodes()
Get the hard-coded pre-computed nodes.
Definition: tsgSequenceOptimizer.cpp:475
Encapsulates the Tasmanian Sparse Grid module.
Definition: TasmanianSparseGrid.hpp:68
Simple pair of numbers for the node and the value of the functional at the node.
Definition: tsgSequenceOptimizer.hpp:70
double node
Node where the functional was evaluated.
Definition: tsgSequenceOptimizer.hpp:72
double value
Value of the functional.
Definition: tsgSequenceOptimizer.hpp:74
Omnipresent enumerate types.