testHeterodyneSearch_flat_evidence_default.py File Reference

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Namespaces
namespace	testHeterodyneSearch_flat_evidence_default

Variables
bool	testHeterodyneSearch_flat_evidence_default.doplot = True
int	testHeterodyneSearch_flat_evidence_default.exit_code = 0
string	testHeterodyneSearch_flat_evidence_default.execu = "./lalpulsar_parameter_estimation_nested"
string	testHeterodyneSearch_flat_evidence_default.parfile
string	testHeterodyneSearch_flat_evidence_default.parf = "test.par"
	testHeterodyneSearch_flat_evidence_default.f = open(parf, "w")
string	testHeterodyneSearch_flat_evidence_default.datafile = "data.txt.gz"
int	testHeterodyneSearch_flat_evidence_default.dlen = 1440
int	testHeterodyneSearch_flat_evidence_default.dt = 600
float	testHeterodyneSearch_flat_evidence_default.startgps = 900000000.0
float	testHeterodyneSearch_flat_evidence_default.endgps = startgps + dt * (dlen - 1)
	testHeterodyneSearch_flat_evidence_default.ds = np.zeros((dlen, 3))
int	testHeterodyneSearch_flat_evidence_default.noisesigma = 1e-24
float	testHeterodyneSearch_flat_evidence_default.ulest = 10.8 * np.sqrt(noisesigma**2 / dlen)
	testHeterodyneSearch_flat_evidence_default.fmt
	testHeterodyneSearch_flat_evidence_default.h0uls = np.logspace(np.log10(5.0 * ulest), np.log10(500.0 * ulest), 6)
string	testHeterodyneSearch_flat_evidence_default.dets = "H1"
int	testHeterodyneSearch_flat_evidence_default.Nlive = 100
int	testHeterodyneSearch_flat_evidence_default.Nmcmcinitial = 0
string	testHeterodyneSearch_flat_evidence_default.outfile = "test.hdf"
string	testHeterodyneSearch_flat_evidence_default.outfile_SNR = "test_SNR"
string	testHeterodyneSearch_flat_evidence_default.outfile_Znoise = "test_Znoise"
list	testHeterodyneSearch_flat_evidence_default.proposals = ["", "--ensembleWalk 1 --uniformprop 0"]
list	testHeterodyneSearch_flat_evidence_default.labels = ["Default", "Walk"]
list	testHeterodyneSearch_flat_evidence_default.pcolor = ["b", "r"]
list	testHeterodyneSearch_flat_evidence_default.max_nsigma = [2.0, 3.0]
int	testHeterodyneSearch_flat_evidence_default.Ntests = 15
	testHeterodyneSearch_flat_evidence_default.fig
	testHeterodyneSearch_flat_evidence_default.ax
	testHeterodyneSearch_flat_evidence_default.walltime = time.time()
list	testHeterodyneSearch_flat_evidence_default.odds_prior = []
list	testHeterodyneSearch_flat_evidence_default.std_odds_prior = []
list	testHeterodyneSearch_flat_evidence_default.logpriors = []
string	testHeterodyneSearch_flat_evidence_default.priorfile = "H0 uniform 0 %e\n" % h0ul
string	testHeterodyneSearch_flat_evidence_default.priorf = "test.prior"
	testHeterodyneSearch_flat_evidence_default.logprior = -np.log(h0ul * np.pi * 2.0 * (np.pi / 2.0))
list	testHeterodyneSearch_flat_evidence_default.hodds = []
	testHeterodyneSearch_flat_evidence_default.elapsed_walltime = time.time() - walltime
	testHeterodyneSearch_flat_evidence_default.flush
tuple	testHeterodyneSearch_flat_evidence_default.commandline
	testHeterodyneSearch_flat_evidence_default.shell
	testHeterodyneSearch_flat_evidence_default.a = f["lalinference"]["lalinference_nest"]
	testHeterodyneSearch_flat_evidence_default.ns = np.array(odds_prior)
	testHeterodyneSearch_flat_evidence_default.p
	testHeterodyneSearch_flat_evidence_default.stdchi
	testHeterodyneSearch_flat_evidence_default.nsigma = np.abs(p - 1.0) / stdchi
	testHeterodyneSearch_flat_evidence_default.yerr
	testHeterodyneSearch_flat_evidence_default.label
	testHeterodyneSearch_flat_evidence_default.color