bilby.gw.conversion.generate_all_bns_parameters

bilby.gw.conversion.generate_all_bns_parameters(sample, likelihood=None, priors=None, npool=1)

From either a single sample or a set of samples fill in all missing BNS parameters, in place.

Since we assume BNS waveforms are aligned, component spins won’t be calculated.

Parameters:

sample: dict or pandas.DataFrame

Samples to fill in with extra parameters, this may be either an injection or posterior samples.

likelihood: bilby.gw.likelihood.GravitationalWaveTransient, optional

GravitationalWaveTransient used for sampling, used for waveform and likelihood.interferometers.

priors: dict, optional

Dictionary of prior objects, used to fill in non-sampled parameters.

npool: int, (default=1)

If given, perform generation (where possible) using a multiprocessing pool