distributions

The distributions module contains continuous and discrete stochastic distribution functions that are typically used in simulation. The distributions are all integrated with the stream and seed management from the streams.py module. The continuous distributions can return information about their probability distribution, and the discrete distributions can return the probability of a certain observation.

Users can create new distributions (or wrap for instance NumPy distributions) by extending the Distribution Abstract Base Class. By doing so, the newly created distributions will automatically be integrated with DSOL’s stream and seed management.

Click below for the API of a specific output statistic type.

Generic Abstract Classes

• Distribution
  • Distribution
    • Distribution.__init__()
    • Distribution.draw()
    • Distribution.stream
• DistContinuous
  • DistContinuous
    • DistContinuous.__init__()
    • DistContinuous.probability_density()
    • DistContinuous.draw()
    • DistContinuous.stream
• DistDiscrete
  • DistDiscrete
    • DistDiscrete.__init__()
    • DistDiscrete.probability()
    • DistDiscrete.draw()
    • DistDiscrete.stream

Discrete Distribution Classes

• DistBernoulli
  • DistBernoulli
    • DistBernoulli.__init__()
    • DistBernoulli.draw()
    • DistBernoulli.probability()
    • DistBernoulli.p
    • DistBernoulli.stream
• DistBinomial
  • DistBinomial
    • DistBinomial.__init__()
    • DistBinomial.draw()
    • DistBinomial.probability()
    • DistBinomial.p
    • DistBinomial.n
    • DistBinomial.stream
• DistDiscreteUniform
  • DistDiscreteUniform
    • DistDiscreteUniform.__init__()
    • DistDiscreteUniform.draw()
    • DistDiscreteUniform.probability()
    • DistDiscreteUniform.lo
    • DistDiscreteUniform.hi
    • DistDiscreteUniform.stream
• DistGeometric
  • DistGeometric
    • DistGeometric.__init__()
    • DistGeometric.draw()
    • DistGeometric.probability()
    • DistGeometric.p
    • DistGeometric.stream
• DistNegBinomial
  • DistNegBinomial
    • DistNegBinomial.__init__()
    • DistNegBinomial.draw()
    • DistNegBinomial.probability()
    • DistNegBinomial.p
    • DistNegBinomial.s
    • DistNegBinomial.stream
• DistPoisson
  • DistPoisson
    • DistPoisson.__init__()
    • DistPoisson.draw()
    • DistPoisson.probability()
    • DistPoisson.rate
    • DistPoisson.stream

Continuous Distribution Classes

• DistBeta
  • DistBeta
    • DistBeta.__init__()
    • DistBeta.draw()
    • DistBeta.probability_density()
    • DistBeta.alpha1
    • DistBeta.alpha2
    • DistBeta.stream
• DistConstant
  • DistConstant
    • DistConstant.__init__()
    • DistConstant.draw()
    • DistConstant.probability_density()
    • DistConstant.constant
    • DistConstant.stream
• DistErlang
  • DistErlang
    • DistErlang.GAMMATHRESHOLD
    • DistErlang.__init__()
    • DistErlang.draw()
    • DistErlang.probability_density()
    • DistErlang.scale
    • DistErlang.k
    • DistErlang.stream
• DistExponential
  • DistExponential
    • DistExponential.__init__()
    • DistExponential.draw()
    • DistExponential.probability_density()
    • DistExponential.mean
    • DistExponential.stream
• DistGamma
  • DistGamma
    • DistGamma.__init__()
    • DistGamma.draw()
    • DistGamma.probability_density()
    • DistGamma.shape
    • DistGamma.scale
    • DistGamma.stream
• DistLogNormal
  • DistLogNormal
    • DistLogNormal.__init__()
    • DistLogNormal.draw()
    • DistLogNormal.probability_density()
    • DistLogNormal.cumulative_probability()
    • DistLogNormal.inverse_cumulative_probability()
    • DistLogNormal.mu
    • DistLogNormal.sigma
    • DistLogNormal.stream
• DistNormal
  • DistNormal
    • DistNormal.__init__()
    • DistNormal.draw()
    • DistNormal.probability_density()
    • DistNormal.cumulative_probability()
    • DistNormal.inverse_cumulative_probability()
    • DistNormal.mu
    • DistNormal.sigma
    • DistNormal.stream
• DistNormalTrunc
  • DistNormalTrunc
    • DistNormalTrunc.__init__()
    • DistNormalTrunc.draw()
    • DistNormalTrunc.probability_density()
    • DistNormalTrunc.cumulative_probability()
    • DistNormalTrunc.cumulative_probability_not_truncated()
    • DistNormalTrunc.inverse_cumulative_probability()
    • DistNormalTrunc.inverse_cumulative_probability_not_truncated()
    • DistNormalTrunc.mu
    • DistNormalTrunc.sigma
    • DistNormalTrunc.lo
    • DistNormalTrunc.hi
    • DistNormalTrunc.stream
• DistPearson5
  • DistPearson5
    • DistPearson5.__init__()
    • DistPearson5.draw()
    • DistPearson5.probability_density()
    • DistPearson5.alpha
    • DistPearson5.beta
    • DistPearson5.stream
• DistPearson6
  • DistPearson6
    • DistPearson6.__init__()
    • DistPearson6.draw()
    • DistPearson6.probability_density()
    • DistPearson6.alpha1
    • DistPearson6.alpha2
    • DistPearson6.beta
    • DistPearson6.stream
• DistTriangular
  • DistTriangular
    • DistTriangular.__init__()
    • DistTriangular.draw()
    • DistTriangular.probability_density()
    • DistTriangular.lo
    • DistTriangular.mode
    • DistTriangular.hi
    • DistTriangular.stream
• DistUniform
  • DistUniform
    • DistUniform.__init__()
    • DistUniform.draw()
    • DistUniform.probability_density()
    • DistUniform.lo
    • DistUniform.hi
    • DistUniform.stream
• DistWeibull
  • DistWeibull
    • DistWeibull.__init__()
    • DistWeibull.draw()
    • DistWeibull.probability_density()
    • DistWeibull.alpha
    • DistWeibull.beta
    • DistWeibull.stream