SG++
python.uq.refinement.RefinementStrategy.VarianceBFRanking Class Reference
Inheritance diagram for python.uq.refinement.RefinementStrategy.VarianceBFRanking:
python.uq.refinement.RefinementStrategy.Ranking

Public Member Functions

def __init__ (self, strategy)
 
def rank (self, grid, gp, alphas, params, args, kws)
 
def update (self, grid, v, admissibleSet)
 
- Public Member Functions inherited from python.uq.refinement.RefinementStrategy.Ranking
def __init__ (self)
 
def getKnowledgeType (self)
 
def rank (self, grid, gp, alphas, params, t=0, args, kws)
 
def update (self, grid, v, gpi, params)
 

Constructor & Destructor Documentation

def python.uq.refinement.RefinementStrategy.VarianceBFRanking.__init__ (   self,
  strategy 
)

References python.uq.refinement.RefinementStrategy.Ranking._ranking, and python.uq.refinement.RefinementStrategy.VarianceBFRanking._strategy.

Member Function Documentation

def python.uq.refinement.RefinementStrategy.VarianceBFRanking.rank (   self,
  grid,
  gp,
  alphas,
  params,
  args,
  kws 
)

References python.uq.refinement.RefinementStrategy.Ranking._ranking.

def python.uq.refinement.RefinementStrategy.VarianceBFRanking.update (   self,
  grid,
  v,
  admissibleSet 
)

References python.uq.refinement.RefinementStrategy.VarianceBFRanking.__computeRanking(), python.uq.refinement.RefinementStrategy.Ranking._ranking, python.uq.operations.sparse_grid.estimateSurplus(), and python.uq.operations.sparse_grid.getBasis().


The documentation for this class was generated from the following file: