SG++
python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge Class Reference
Inheritance diagram for python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge:

Public Member Functions

def __init__ (self)
 
def __str__ (self)
 
def clearAlphas (self)
 
def createMemento (self)
 
def fromJson (cls, jsonObject)
 
def getAlpha (self, qoi='_', t=0, dtype=KnowledgeTypes.SIMPLE, iteration=None)
 
def getAlphas (self)
 
def getAlphasByQoI (self, qoi='_', dtype=KnowledgeTypes.SIMPLE, iteration=None)
 
def getAvailableIterations (self)
 
def getAvailableKnowledgeTypes (self)
 
def getAvailableQoI (self)
 
def getAvailableTimeSteps (self)
 
def getGrid (self, qoi='_', iteration=None)
 
def getGrids (self)
 
def getIteration (self)
 
def getSparseGridFunction (self, qoi='_', t=0, dtype=KnowledgeTypes.SIMPLE, iteration=None)
 
def hasAlpha (self, iteration, qoi, t, dtype)
 
def hasGrid (self, iteration, qoi)
 
def initWithStandardValues (cls, grid, alpha)
 
def setAlphas (self, alphas)
 
def setGrids (self, grids)
 
def setIteration (self, iteration)
 
def setMemento (self, memento)
 
def toJson (self)
 
def update (self, grid, alpha, qoi, t, dtype, iteration)
 
def writeToFile (self, filename)
 

Detailed Description

The ASGC knowledge class

Constructor & Destructor Documentation

def python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.__init__ (   self)
Constructor

References python.learner.LearnedKnowledge.LearnedKnowledge.__alphas, python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.__alphas, python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.__grids, and python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.__iteration.

Member Function Documentation

def python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.__str__ (   self)

References python.learner.LearnedKnowledge.LearnedKnowledge.__alphas, python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.__alphas, python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.__grids, and python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.__iteration.

def python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.clearAlphas (   self)

References python.learner.LearnedKnowledge.LearnedKnowledge.__alphas, and python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.__alphas.

def python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.createMemento (   self)
def python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.fromJson (   cls,
  jsonObject 
)
Restores the ASGC object from the json object with its
attributes.
@param jsonObject: json object
@return: the restored ASGC object

Referenced by python.uq.sampler.asgc.ASGCSampler.ASGCSampler.setMemento(), python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.setMemento(), python.uq.learner.Learner.Learner.setMemento(), and python.uq.uq_setting.UQSetting.UQSetting.setMemento().

def python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.getAlpha (   self,
  qoi = '_',
  t = 0,
  dtype = KnowledgeTypes.SIMPLE,
  iteration = None 
)
Get the coefficient vector for the given configuration
@param qoi: string quantity of interest
@param t: float time step
@param dtype: KnowledgeType
@param iteration: int, iteration number

References python.learner.LearnedKnowledge.LearnedKnowledge.__alphas, python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.__alphas, python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.__iteration, python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.getAlphasByQoI(), and python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.hasAlpha().

Referenced by python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.getGrid(), and python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.getSparseGridFunction().

def python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.getAlphas (   self)

References python.learner.LearnedKnowledge.LearnedKnowledge.__alphas, and python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.__alphas.

def python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.getAlphasByQoI (   self,
  qoi = '_',
  dtype = KnowledgeTypes.SIMPLE,
  iteration = None 
)
Get all coefficient vectors for the given quantity of interest
@param qoi: string quantity of interest
@param iteration: int, iteration number

References python.learner.LearnedKnowledge.LearnedKnowledge.__alphas, python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.__alphas, python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.__iteration, and python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.getSparseGridFunction().

Referenced by python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.getAlpha().

def python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.getAvailableIterations (   self)
get available iterations
@return: sorted list of integes
def python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.getAvailableKnowledgeTypes (   self)
@return list of available KnowledgeTypes

References python.learner.LearnedKnowledge.LearnedKnowledge.__alphas, and python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.__alphas.

def python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.getAvailableQoI (   self)
get available quantities of interest
@return: list of strings identifying the quantities of interest

References python.learner.LearnedKnowledge.LearnedKnowledge.__alphas, and python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.__alphas.

Referenced by python.uq.uq_setting.UQSetting.UQSetting.getResult(), and python.uq.uq_setting.UQSetting.UQSetting.getTimeDependentResults().

def python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.getAvailableTimeSteps (   self)
get available time steps
@return: sorted list of floats

References python.learner.LearnedKnowledge.LearnedKnowledge.__alphas, python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.__alphas, and python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.__iteration.

def python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.getGrid (   self,
  qoi = '_',
  iteration = None 
)
def python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.getGrids (   self)

References python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.__grids.

def python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.getIteration (   self)
get current iteration number

References python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.__iteration.

def python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.getSparseGridFunction (   self,
  qoi = '_',
  t = 0,
  dtype = KnowledgeTypes.SIMPLE,
  iteration = None 
)
Get the sparse grid function (grid, alpha) for the given setting
@param qoi: string quantity of interest
@param t: float time step
@param dtype: KnowledgeType
@param iteration: int, iteration number

References python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.__iteration, python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.getAlpha(), python.uq.analysis.asgc.ASGCAnalysis.ASGCAnalysis.getGrid(), python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.getGrid(), python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.hasAlpha(), and python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.hasGrid().

Referenced by python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.getAlphasByQoI().

def python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.hasAlpha (   self,
  iteration,
  qoi,
  t,
  dtype 
)
Check if there is a coefficient vector for the given
configuration.
@param iteration: int iteration number
@param qoi: string quantity of interest
@param t: float time step
@param dtype: KnowledgeType

References python.learner.LearnedKnowledge.LearnedKnowledge.__alphas, and python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.__alphas.

Referenced by python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.getAlpha(), and python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.getSparseGridFunction().

def python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.hasGrid (   self,
  iteration,
  qoi 
)
Check if there is a grid available for the given configuration
@param iteration: int iteration number
@param qoi: string quantity of interest

References python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.__grids.

Referenced by python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.getGrid(), and python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.getSparseGridFunction().

def python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.initWithStandardValues (   cls,
  grid,
  alpha 
)
def python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.setAlphas (   self,
  alphas 
)

References python.learner.LearnedKnowledge.LearnedKnowledge.__alphas, and python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.__alphas.

def python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.setGrids (   self,
  grids 
)

References python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.__grids.

def python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.setIteration (   self,
  iteration 
)
set current iteration number

References python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.__iteration.

def python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.update (   self,
  grid,
  alpha,
  qoi,
  t,
  dtype,
  iteration 
)
Update the knowledge
@param grid: Grid
@param alpha: numpy array surplus vector
@param qoi: string quantity of interest
@param t: float time step
@param dtype: KnowledgeType
@param iteration: int iteration number

References python.learner.LearnedKnowledge.LearnedKnowledge.__alphas, python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.__alphas, python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.__grids, and python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge.__iteration.

Referenced by python.uq.refinement.RefinementStrategy.Ranking.rank().


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