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class ExponentialPrior( LaplacePrior )	Source

Exponential prior distribution.

  Pr( x ) = exp( -x / scale )

By default scale = 1.

The domain is [0,+Inf]. In computational practice the domain is limited to about [0,36] scale units

Wrapper for LaplacePrior( center=0, scale=scale, limits=[0, hilim] )

Examples

pr = ExponentialPrior()                     # scale=1.0
pr = ExponentialPrior( scale=5.0 )          # scale=5

Attributes

• scale : float
       scale of the exponential

Attributes from Prior

lowLimit, highLimit, deltaP, _lowDomain, _highDomain

Author: Do Kester.

ExponentialPrior( scale=1.0, hilimit=math.inf, prior=None )

Constructor.

Parameters

• scale : float
       of the exponential
• hilimit : float
       high limit
• prior : ExponentialPrior
       prior to copy (with new scale if applicable)

copy( )

Copy the prior

shortName( )

Return a short name

Methods inherited from LaplacePrior

• domain2Unit( dval )
• unit2Domain( uval )
• result( x )
• logResult( x )
• partialLog( x )
• isBound( )

Methods inherited from Prior

• limitedIntegral( center=0, circular=False, limits=None )
• setLimits( limits=None )
• setPriorAttributes( limits, circular )
• isCircular( )
• limitedDomain2Unit( dval )
• limitedUnit2Domain( uval )
• circularDomain2Unit( dval )
• circularUnit2Domain( uval )
• unsetLimits( )
• setAttributes( limits=None, scale=None )
• isOutOfLimits( par )
• checkLimit( par )
• stayInLimits( par )
• hasLowLimit( )
• hasHighLimit( )
• hasLimits( )
• getLimits( )
• getIntegral( )
• getRange( )
• partialDomain2Unit( p )
• numPartialDomain2Unit( dval )
• numPartialLog( p )