Spright (/spraɪt/; Parviainen, Luque, and Palle, 2023) is a fast Bayesian radius-density-mass relation for small planets. The package allows one to predict planetary masses, densities, and RV semi-amplitudes given the planet's radius or planetary radii given the planet's mass.
The package offers an easy-to-use command line script for people not overly interested in coding and a nearly-as-easy-to-use set of Python classes for those who prefer to code. The command line script can directly create publication-quality plots, and the classes offer a full access to the predicted numerical distributions.
The package contains two relations: one for small planets orbiting M dwarfs (inferred from a updated SPTM catalogue by R. Luque) and another for planets orbiting FGK stars (inferred from a filtered TepCAT catalogue).
pip install spright
spright --predict mass --radius 1.8 0.1 --plot-distribution
from spright import RMRelation
rmr = RMRelation()
mds = rmr.predict_mass(radius=(1.8, 0.1))
mds.plot()
The radial velocity semi-amplitude can be predicted given the planet's radius, orbital period, orbital eccentricity (optional), and the host star mass.
from spright import RMRelation
rmr = RMRelation()
mds = rmr.predict_rv_semi_amplitude(radius=(1.8, 0.1), period=2.2, mstar=(0.5, 0.05), eccentricity=0.01)
mds.plot()
Here the RMRelation.predict_rv_semi_amplitude method can also be given the planet's orbital eccentricity (ecc),
and all the parameters (radius, period, mstar, and eccentricity) can either be floats, ufloats, or two-value tuples where the second value gives
the parameter uncertainty.
from spright import RMEstimator
rme = RMEstimator(names=names, radii=radii, masses=masses)
rme.optimize()
rme.sample()
rme.compute_maps()
rme.save('map_name.fits')
© 2023 Hannu Parviainen