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class Explorer( object )	Source

Explorer is a helper class of NestedSampler, which contains and runs the diffusion engines.

It uses Threads to parallelise the diffusion engines.

Attributes

• walkers : WalkerList
       walkers to be explored
• engines : [engine]
       list of engines to be used
• errdis : ErrorDistribution
       to be used
• rng : numpy.random.RandomState
       random number generator
• rate : float (1.0)
       governs processing speed (vs precision)
• maxtrials : int (5)
       number of trials
• verbose : int (0)
       level of blabbering
• lowLhood : float
       present low likelihood level
• iteration : int
       counting explorer calls

Author Do Kester.

Explorer( ns, threads=False )

Construct Explorer from a NestedSampler object.

Parameters

• ns : NestedSampler
       the calling NestedSampler. It provides the attributes.

explore( worst, lowLhood, iteration )

Explore the likelihood function, using threads.

Parameters

• worst : [int]
       list of walkers to be explored/updated
• lowLhood : float
       level of the low likelihood

exploreWalker( kw, lowLhood, engines, rng )

Move the walker around until it is randomly distributed over the prior and higher in logL then lowLhood

Parameters

• kw : int
       index in walkerlist, of the walker to be explored
• lowLhood : float
       minimum value for the log likelihood
• engine : list of Engine
       to be used
• rng : RandomState
       random number generator

selEngines( iteration )

Select engines with slowly changing parameters once per so many iterations.

Parameter

• iteration : int
       iteration number

allEngines( iteration )

Always use all engines.

Parameters

• iteration : int
       iteration number

checkWalkers( )

Perform logLcheck() on all walkers.

logLcheck( walker )

Sanity check when no moves are found, if the LogL is still the same as the stored logL.

Parameters

• walker : Walker
       the one with the stored logL

Raises

ValueError at inconsistency.