SG++
python.uq.dists.Dist.Dist Class Reference
Inheritance diagram for python.uq.dists.Dist.Dist:

Public Member Functions

def cdf (self, p, args, kws)
 
def corrcoeff (self, covMatrix=None)
 
def cov (self)
 
def crossEntropy (self, samples)
 
def fromJson (cls, jsonObject)
 
def getBounds (self)
 
def getDim (self)
 
def klDivergence (self, dist, testSamplesUnit=None, testSamplesProb=None, n=1e4)
 
def l2error (self, dist, testSamplesUnit=None, testSamplesProb=None, n=1e4, dtype=SampleType.ACTIVEPROBABILISTIC)
 
def mean (self)
 
def pdf (self, p, args, kws)
 
def ppf (self, p, args, kws)
 
def rvs (self, n=1)
 
def std (self)
 
def var (self)
 

Detailed Description

The Dist class, which is the super class for all
distributions of this package

Member Function Documentation

def python.uq.dists.Dist.Dist.cdf (   self,
  p,
  args,
  kws 
)
Cumulative distribution function
@param p: (tuple) of floats
@return: cumulative distribution value
def python.uq.dists.Dist.Dist.corrcoeff (   self,
  covMatrix = None 
)
def python.uq.dists.Dist.Dist.crossEntropy (   self,
  samples 
)
this measure computes the cross entropy with respect
to some unknown probability distribution from which only samples
are available. This measure is known to minimize the kl divergence.

@param samples: numpy array

References python.uq.dists.Dist.Dist.l2error(), python.uq.dists.CorrBeta.CorrBeta.pdf(), python.uq.dists.Dist.Dist.pdf(), python.uq.dists.Corr.Corr.pdf(), python.uq.dists.Beta.Beta.pdf(), python.uq.dists.DataDist.DataDist.pdf(), sgpp::combigrid::ProbabilityDensityFunction1D.pdf(), and sgpp::combigrid::OrthogonalPolynomialBasis1D.pdf().

def python.uq.dists.Dist.Dist.getBounds (   self)
Get the distribution's intervals
@return: numpy array [dim, 2]

Referenced by python.uq.dists.Dist.Dist.l2error().

def python.uq.dists.Dist.Dist.getDim (   self)
Get number of marginal distributions
@return: int number of marginal distributions

Referenced by python.uq.dists.Dist.Dist.cov(), python.uq.parameters.ParameterSet.ParameterSet.extractActiveSubset(), and python.uq.uq_setting.UQSetting.UQSetting.getDim().

def python.uq.dists.Dist.Dist.mean (   self)
def python.uq.dists.Dist.Dist.pdf (   self,
  p,
  args,
  kws 
)
Probability distribution function
@param p: (tuple) of floats
@return: probability distribution value

Referenced by python.uq.dists.Dist.Dist.crossEntropy(), python.uq.dists.Dist.Dist.klDivergence(), and python.uq.dists.Dist.Dist.l2error().

def python.uq.dists.Dist.Dist.ppf (   self,
  p,
  args,
  kws 
)
Point percentile function
@param p: (tuple) of floats
@return: point percentile value
def python.uq.dists.Dist.Dist.rvs (   self,
  n = 1 
)
Generates n random numbers w.r.t. the marginal distributions
@param n: int number of random values
@return: numpy array [n, dim]
def python.uq.dists.Dist.Dist.std (   self)
@return: standard deviation

References python.uq.dists.Beta.Beta.var(), python.uq.dists.Dist.Dist.var(), sgpp::combigrid::BsplineStochasticCollocation.var, sgpp::combigrid::PolynomialStochasticCollocation.var, python.uq.dists.DataDist.DataDist.var(), and python.uq.analysis.Analysis.Analysis.var().


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