RelativeBinning optimisation doesn't account for Constraint priors
When using the RelativeBinningGravitationalWaveTransient
I've specified the fiducial waveform in terms of {"chirp_mass": 3.163, "mass_ratio": 0.383, etc}
. This is a NSBH injection, that I want to analyse using the SEOBNRv4_ROM_NRTidalv2_NSBH
waveform.
When the likelihood is initialised, it by default does the update_fiducal_parameters step, and with the setup I used (optimising over the prior, since I hadn't specified any dedicated parameter_bounds
) it "only" looks to optimise over chirp_mass
and mass_ratio
.
The problem is that the SEOBNRv4_ROM_NRTidalv2_NSBH
model is only supported for 1 < mass_2 < 3
. I account for this in the actual Bilby configuration by having a mass_2 = Constraint(name='mass_2', minimum=1.0, maximum=3.0)
in my prior, but since mass_2
isn't in the self.parameters_to_be_updated
list (see here) that Constraint will not be accounted for, and the optimisation will fail since it'll try to evaluate SEOBNRv4_ROM_NRTidalv2_NSBH
at a point that's nominally inside the chirp_mass
and mass_ratio
priors, but has a too-high NS mass.