BAYESTAR Rapid Localization (ligo.skymap.bayestar)

Rapid sky localization with BAYESTAR [1].



Singer & Price, 2016. “Rapid Bayesian position reconstruction for gravitational-wave transients.” PRD, 93, 024013. doi:10.1103/PhysRevD.93.024013

ligo.skymap.bayestar.localize(event, waveform='o2-uberbank', f_low=30.0, min_distance=None, max_distance=None, prior_distance_power=None, cosmology=False, mcmc=False, chain_dump=None, enable_snr_series=True, f_high_truncate=0.95, rescale_loglikelihood=0.83)[source] [edit on github]

Localize a compact binary signal using the BAYESTAR algorithm.


The event candidate.

waveformstr, optional

The name of the waveform approximant.

f_lowfloat, optional

The low frequency cutoff.

min_distance, max_distancefloat, optional

The limits of integration over luminosity distance, in Mpc (default: determine automatically from detector sensitivity).

prior_distance_powerint, optional

The power of distance that appears in the prior (default: 2, uniform in volume).

cosmology: bool, optional

Set to enable a uniform in comoving volume prior (default: false).

mcmcbool, optional

Set to use MCMC sampling rather than more accurate Gaussian quadrature.

chain_dumpstr, optional

Save posterior samples to this filename if mcmc is set.

enable_snr_seriesbool, optional

Set to False to disable SNR time series.

f_high_truncatefloat, optional

Truncate the noise power spectral densities at this factor times the highest sampled frequency to suppress artifacts caused by incorrect PSD conditioning by some matched filter pipelines.


A 3D sky map in multi-order HEALPix format.

ligo.skymap.bayestar.signal_amplitude_model(x1, x2, x3, x4, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj])

Supporting Modules