Data structure for a table of posterior samples .
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__init__(self,
commonResultsFormatData,
SimInspiralTableEntry=None,
inj_spin_frame='OrbitalL',
injFref=100,
SnglInpiralList=None,
name=None,
description=None,
votfile=None)
Constructor. |
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extend_posterior(self)
Add some usefule derived parameters (such as tilt angles, time
delays, etc) in the Posterior object |
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Posterior
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bootstrap(self)
Returns a new Posterior object that contains a bootstrap sample of
self. |
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DIC(self)
Returns the Deviance Information Criterion estimated from the
posterior samples. |
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glue.ligolw.lsctables.SimInspiral
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list
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number
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longest_chain_cycles(self)
Returns the number of cycles in the longest chain |
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_getinjpar(self,
paramname)
Map parameter names to parameters in a SimInspiralTable . |
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_gettrigpar(self,
paramname)
Map parameter names to parameters in a SnglInspiral. |
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forward(self)
Generate a forward iterator (in sense of list of names) over
Posterior with name,one_d_pos. |
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bySample(self)
Generate a forward iterator over the list of samples corresponding to
the data stored within the Posterior instance. |
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name(self)
Return qualified string containing the 'name' of the Posterior
instance. |
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append_mapping(self,
new_param_names,
func,
post_names)
Append posteriors pos1,pos2,...=func(post_names) |
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_average_posterior(self,
samples,
post_name)
Returns the average value of the 'post_name' column of the given
samples. |
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_average_posterior_like_prior(self,
samples,
logl_name,
prior_name,
log_bias=0)
Returns the average value of the posterior assuming that the
'logl_name' column contains log(L) and the 'prior_name' column
contains the prior (un-logged). |
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_bias_factor(self)
Returns a sensible bias factor for the evidence so that integrals are
representable as doubles. |
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di_evidence(self,
boxing=64)
Returns the log of the direct-integration evidence for the posterior
samples. |
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elliptical_subregion_evidence(self)
Returns an approximation to the log(evidence) obtained by fitting an
ellipse around the highest-posterior samples and performing the
harmonic mean approximation within the ellipse. |
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harmonic_mean_evidence(self)
Returns the log of the harmonic mean evidence for the set of
posterior samples. |
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maxL(self)
Return the maximum likelihood probability and the corresponding set
of parameters. |
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maxP(self)
Return the maximum a posteriori probability and the corresponding set
of parameters. |
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samples(self)
Return an (M,N) numpy.array of posterior samples; M = len(self); N =
dim(self) . |
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write_to_file(self,
fname)
Dump the posterior table to a file in the 'common format'. |
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healpix_map(self,
resol,
nest=True)
Returns a healpix map in the pixel ordering that represents the
posterior density (per square degree) on the sky. |
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__str__(self)
Define a string representation of the Posterior class ; returns a
html formatted table of various properties of posteriors. |
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write_vot_info(self)
Writes the information stored in the VOTtree if there is one |
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number
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number
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number
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number
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Inherited from object :
__delattr__ ,
__format__ ,
__getattribute__ ,
__hash__ ,
__new__ ,
__reduce__ ,
__reduce_ex__ ,
__repr__ ,
__setattr__ ,
__sizeof__ ,
__subclasshook__
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