from EXOSIMS.PlanetPopulation.KeplerLike1 import KeplerLike1
from EXOSIMS.util.InverseTransformSampler import InverseTransformSampler
import astropy.units as u
class KeplerLike2(KeplerLike1):
"""
Population based on Kepler radius distribution with RV-like semi-major axis
distribution with exponential decay.
NOTE: This is an exact clone of KeplerLike1, but uses (approximate)
inverse transform sampling instead of simple rejection sampling for
performance improvements.
Args:
\*\*specs:
user specified values
Attributes:
smaknee (float):
Location (in AU) of semi-major axis decay point (knee).
Not an astropy quantity.
esigma (float):
Sigma value of Rayleigh distribution for eccentricity.
Notes:
1. The gen_mass function samples the Radius and calculates the mass from
there. Any user-set mass limits are ignored.
2. The gen_albedo function samples the sma, and then calculates the albedos
from there. Any user-set albedo limits are ignored.
3. The Rprange is fixed to (1,22.6) R_Earth and cannot be overwritten by user
settings (the JSON input will be ignored)
4. The radius piece-wise distribution provides the normalization required to
get the proper overall eta. The gen_radius method provided here normalizes
in order to return exactly the number of samples requested. A second method
(gen_radius_nonorm) is provided for generating the simulated universe
population. The latter assumes a poisson distribution for occurences in each
bin.
5. Eccentricity is assumed to be Rayleigh distributed with a user-settable
sigma parameter (defaults to 0.25).
"""
def __init__(self, smaknee=30, esigma=0.25, **specs):
KeplerLike1.__init__(self, smaknee=smaknee, esigma=esigma, **specs)
# unitless sma range
ar = self.arange.to('AU').value
self.sma_sampler = InverseTransformSampler(self.dist_sma, ar[0], ar[1])
def gen_sma(self, n):
"""Generate semi-major axis values in AU
Samples a power law distribution with exponential turn-off
determined by class attribute smaknee
Args:
n (integer):
Number of samples to generate
Returns:
a (astropy Quantity array):
Semi-major axis in units of AU
"""
n = self.gen_input_check(n)
a = self.sma_sampler(n)*u.AU
return a
