cbcBayesPostProc Namespace Reference

Functions
def	email_notify (address, path)
def	pickle_to_file (obj, fname)
	Pickle/serialize 'obj' into 'fname'. More...
def	oneD_dict_to_file (dict, fname)
def	multipleFileCB (opt, opt_str, value, parser)
def	dict2html (d, parent=None)
def	extract_hdf5_metadata (h5grp, parent=None)
def	cbcBayesPostProc (outdir, data, oneDMenus, twoDGreedyMenu, GreedyRes, confidence_levels, twoDplots, injfile=None, eventnum=None, trigfile=None, trignum=None, skyres=None, dievidence=False, boxing=64, difactor=1.0, ellevidence=False, bayesfactornoise=None, bayesfactorcoherent=None, snrfactor=None, ns_flag=False, ns_Nlive=None, ss_flag=False, ss_spin_flag=False, li_flag=False, deltaLogP=None, fixedBurnins=None, nDownsample=None, oldMassConvention=False, fm_flag=False, inj_spin_frame='OrbitalL', noacf=False, twodkdeplots=False, RconvergenceTests=False, savepdfs=True, covarianceMatrices=None, meanVectors=None, header=None, psd_files=None, greedy=True ## If true will use greedy bin for 1-d credible regions. Otherwise use 2-steps KDE)
	This is a demonstration script for using the functionality/data structures contained in lalinference.bayespputils . More...

Variables
int	fig_width_pt = 246
float	inches_per_pt = 1.0/72.27
tuple	golden_mean = (2.236-1.0)/2.0
int	fig_width = fig_width_pt*inches_per_pt
int	fig_height = fig_width*golden_mean
list	fig_size = [fig_width,fig_height]
	parser = OptionParser(USAGE)
	dest
	help
	metavar
	action
	callback
	multipleFileCB
	default
	None
	type
	False
	True
	opts
	args
list	datafiles = []
list	fixedBurnins = [int(opts.fixedBurnin[0]) for df in datafiles]
dictionary	oneDMenus = {'Masses':None,'SourceFrame':None,'Timing':None,'Extrinsic':None,'Spins':None,'StrongField':None,'Others':None}
list	ifos_menu = ['h1','l1','v1']
list	twoDGreedyMenu = []
	greedyBinSizes = bppu.greedyBinSizes
	deltaLogP = opts.deltaLogL
	confidenceLevels = bppu.confidenceLevels
list	twoDplots = twoDGreedyMenu
	injfile
	eventnum
	trigfile
	trignum
	skyres
	dievidence
	boxing
	difactor
	ellevidence
	bayesfactornoise
	bsn
	bayesfactorcoherent
	snrfactor
	ns_flag
	ns
	ns_Nlive
	ss_flag
	ss
	ss_spin_flag
	li_flag
	lalinfmcmc
	nDownsample
	downsample
	oldMassConvention
	fm_flag
	inj_spin_frame
	noacf
	twodkdeplots
	RconvergenceTests
	savepdfs
	covarianceMatrices
	meanVectors
	header
	psd_files
	greedy

Function Documentation

email_notify()

def cbcBayesPostProc.email_notify	(		address,
			path
	)

Definition at line 86 of file cbcBayesPostProc.py.

pickle_to_file()

def cbcBayesPostProc.pickle_to_file	(		obj,
			fname
	)

Pickle/serialize 'obj' into 'fname'.

Definition at line 106 of file cbcBayesPostProc.py.

oneD_dict_to_file()

def cbcBayesPostProc.oneD_dict_to_file	(		dict,
			fname
	)

Definition at line 111 of file cbcBayesPostProc.py.

multipleFileCB()

def cbcBayesPostProc.multipleFileCB	(		opt,
			opt_str,
			value,
			parser
	)

Definition at line 116 of file cbcBayesPostProc.py.

dict2html()

def cbcBayesPostProc.dict2html	(		d,
			parent = None
	)

Definition at line 143 of file cbcBayesPostProc.py.

extract_hdf5_metadata()

def cbcBayesPostProc.extract_hdf5_metadata	(		h5grp,
			parent = None
	)

Definition at line 155 of file cbcBayesPostProc.py.

cbcBayesPostProc()

def cbcBayesPostProc.cbcBayesPostProc	(		outdir,
			data,
			oneDMenus,
			twoDGreedyMenu,
			GreedyRes,
			confidence_levels,
			twoDplots,
			injfile = None,
			eventnum = None,
			trigfile = None,
			trignum = None,
			skyres = None,
			dievidence = False,
			boxing = 64,
			difactor = 1.0,
			ellevidence = False,
			bayesfactornoise = None,
			bayesfactorcoherent = None,
			snrfactor = None,
			ns_flag = False,
			ns_Nlive = None,
			ss_flag = False,
			ss_spin_flag = False,
			li_flag = False,
			deltaLogP = None,
			fixedBurnins = None,
			nDownsample = None,
			oldMassConvention = False,
			fm_flag = False,
			inj_spin_frame = 'OrbitalL',
			noacf = False,
			twodkdeplots = False,
			RconvergenceTests = False,
			savepdfs = True,
			covarianceMatrices = None,
			meanVectors = None,
			header = None,
			psd_files = None,
			greedy = True ## If true will use greedy bin for 1-d credible regions. Otherwise use 2-steps KDE
	)

This is a demonstration script for using the functionality/data structures contained in lalinference.bayespputils .

It will produce a webpage from a file containing posterior samples generated by the parameter estimation codes with 1D/2D plots and stats from the marginal posteriors for each parameter/set of parameters.

Definition at line 172 of file cbcBayesPostProc.py.

Variable Documentation

fig_width_pt

int cbcBayesPostProc.fig_width_pt = 246

Definition at line 50 of file cbcBayesPostProc.py.

inches_per_pt

float cbcBayesPostProc.inches_per_pt = 1.0/72.27

Definition at line 51 of file cbcBayesPostProc.py.

golden_mean

tuple cbcBayesPostProc.golden_mean = (2.236-1.0)/2.0

Definition at line 52 of file cbcBayesPostProc.py.

fig_width

int cbcBayesPostProc.fig_width = fig_width_pt*inches_per_pt

Definition at line 53 of file cbcBayesPostProc.py.

fig_height

int cbcBayesPostProc.fig_height = fig_width*golden_mean

Definition at line 54 of file cbcBayesPostProc.py.

fig_size

list cbcBayesPostProc.fig_size = [fig_width,fig_height]

Definition at line 55 of file cbcBayesPostProc.py.

parser

cbcBayesPostProc.parser = OptionParser(USAGE)

Definition at line 1095 of file cbcBayesPostProc.py.

dest

cbcBayesPostProc.dest

Definition at line 1096 of file cbcBayesPostProc.py.

help

cbcBayesPostProc.help

Definition at line 1096 of file cbcBayesPostProc.py.

metavar

cbcBayesPostProc.metavar

Definition at line 1096 of file cbcBayesPostProc.py.

action

cbcBayesPostProc.action

Definition at line 1097 of file cbcBayesPostProc.py.

callback

cbcBayesPostProc.callback

Definition at line 1097 of file cbcBayesPostProc.py.

multipleFileCB

cbcBayesPostProc.multipleFileCB

Definition at line 1097 of file cbcBayesPostProc.py.

default

cbcBayesPostProc.default

Definition at line 1099 of file cbcBayesPostProc.py.

None

cbcBayesPostProc.None

Definition at line 1102 of file cbcBayesPostProc.py.

type

cbcBayesPostProc.type

Definition at line 1102 of file cbcBayesPostProc.py.

False

cbcBayesPostProc.False

Definition at line 1107 of file cbcBayesPostProc.py.

True

cbcBayesPostProc.True

Definition at line 1138 of file cbcBayesPostProc.py.

opts

cbcBayesPostProc.opts

Definition at line 1146 of file cbcBayesPostProc.py.

args

cbcBayesPostProc.args

Definition at line 1146 of file cbcBayesPostProc.py.

datafiles

list cbcBayesPostProc.datafiles = []

Definition at line 1148 of file cbcBayesPostProc.py.

fixedBurnins

list cbcBayesPostProc.fixedBurnins = [int(opts.fixedBurnin[0]) for df in datafiles]

Definition at line 1157 of file cbcBayesPostProc.py.

oneDMenus

dictionary cbcBayesPostProc.oneDMenus = {'Masses':None,'SourceFrame':None,'Timing':None,'Extrinsic':None,'Spins':None,'StrongField':None,'Others':None}

Definition at line 1165 of file cbcBayesPostProc.py.

ifos_menu

list cbcBayesPostProc.ifos_menu = ['h1','l1','v1']

Definition at line 1178 of file cbcBayesPostProc.py.

twoDGreedyMenu

list cbcBayesPostProc.twoDGreedyMenu = []

Definition at line 1183 of file cbcBayesPostProc.py.

greedyBinSizes

cbcBayesPostProc.greedyBinSizes = bppu.greedyBinSizes

Definition at line 1271 of file cbcBayesPostProc.py.

deltaLogP

cbcBayesPostProc.deltaLogP = opts.deltaLogL

Definition at line 1282 of file cbcBayesPostProc.py.

confidenceLevels

cbcBayesPostProc.confidenceLevels = bppu.confidenceLevels

Definition at line 1286 of file cbcBayesPostProc.py.

twoDplots

list cbcBayesPostProc.twoDplots = twoDGreedyMenu

Definition at line 1289 of file cbcBayesPostProc.py.

injfile

cbcBayesPostProc.injfile

Definition at line 1294 of file cbcBayesPostProc.py.

eventnum

cbcBayesPostProc.eventnum

Definition at line 1294 of file cbcBayesPostProc.py.

trigfile

cbcBayesPostProc.trigfile

Definition at line 1295 of file cbcBayesPostProc.py.

trignum

cbcBayesPostProc.trignum

Definition at line 1295 of file cbcBayesPostProc.py.

skyres

cbcBayesPostProc.skyres

Definition at line 1296 of file cbcBayesPostProc.py.

dievidence

cbcBayesPostProc.dievidence

Definition at line 1298 of file cbcBayesPostProc.py.

boxing

cbcBayesPostProc.boxing

Definition at line 1298 of file cbcBayesPostProc.py.

difactor

cbcBayesPostProc.difactor

Definition at line 1298 of file cbcBayesPostProc.py.

ellevidence

cbcBayesPostProc.ellevidence

Definition at line 1300 of file cbcBayesPostProc.py.

bayesfactornoise

cbcBayesPostProc.bayesfactornoise

Definition at line 1302 of file cbcBayesPostProc.py.

bsn

cbcBayesPostProc.bsn

Definition at line 1302 of file cbcBayesPostProc.py.

bayesfactorcoherent

cbcBayesPostProc.bayesfactorcoherent

Definition at line 1302 of file cbcBayesPostProc.py.

snrfactor

cbcBayesPostProc.snrfactor

Definition at line 1304 of file cbcBayesPostProc.py.

ns_flag

cbcBayesPostProc.ns_flag

Definition at line 1306 of file cbcBayesPostProc.py.

ns

cbcBayesPostProc.ns

Definition at line 1306 of file cbcBayesPostProc.py.

ns_Nlive

cbcBayesPostProc.ns_Nlive

Definition at line 1306 of file cbcBayesPostProc.py.

ss_flag

cbcBayesPostProc.ss_flag

Definition at line 1308 of file cbcBayesPostProc.py.

ss

cbcBayesPostProc.ss

Definition at line 1308 of file cbcBayesPostProc.py.

ss_spin_flag

cbcBayesPostProc.ss_spin_flag

Definition at line 1308 of file cbcBayesPostProc.py.

li_flag

cbcBayesPostProc.li_flag

Definition at line 1310 of file cbcBayesPostProc.py.

lalinfmcmc

cbcBayesPostProc.lalinfmcmc

Definition at line 1310 of file cbcBayesPostProc.py.

nDownsample

cbcBayesPostProc.nDownsample

Definition at line 1310 of file cbcBayesPostProc.py.

downsample

cbcBayesPostProc.downsample

Definition at line 1310 of file cbcBayesPostProc.py.

oldMassConvention

cbcBayesPostProc.oldMassConvention

Definition at line 1310 of file cbcBayesPostProc.py.

fm_flag

cbcBayesPostProc.fm_flag

Definition at line 1312 of file cbcBayesPostProc.py.

inj_spin_frame

cbcBayesPostProc.inj_spin_frame

Definition at line 1314 of file cbcBayesPostProc.py.

noacf

cbcBayesPostProc.noacf

Definition at line 1316 of file cbcBayesPostProc.py.

twodkdeplots

cbcBayesPostProc.twodkdeplots

Definition at line 1318 of file cbcBayesPostProc.py.

RconvergenceTests

cbcBayesPostProc.RconvergenceTests

Definition at line 1320 of file cbcBayesPostProc.py.

savepdfs

cbcBayesPostProc.savepdfs

Definition at line 1322 of file cbcBayesPostProc.py.

covarianceMatrices

cbcBayesPostProc.covarianceMatrices

Definition at line 1324 of file cbcBayesPostProc.py.

meanVectors

cbcBayesPostProc.meanVectors

Definition at line 1326 of file cbcBayesPostProc.py.

header

cbcBayesPostProc.header

Definition at line 1328 of file cbcBayesPostProc.py.

psd_files

cbcBayesPostProc.psd_files

Definition at line 1330 of file cbcBayesPostProc.py.

greedy

cbcBayesPostProc.greedy

Definition at line 1331 of file cbcBayesPostProc.py.