CONAN.models.TTV_Model#
- CONAN.models.TTV_Model(tarr, rho_star=None, dur=None, T0_list=None, RpRs=None, b=None, per=None, sesinw=[0], secosw=[0], ddf=0, occ=0, Fn=None, delta=None, A_ev=0, f1_ev=0, A_db=0, q1=0, q2=0, split_conf=None, ss=None, vcont=0, Rstar=None, grprs=0, custom_LCfunc=None, cst_pars={})#
computes the TTV model for a given set of parameters along with the baseline
- Parameters:
tarr (array-like) – The timestamps of the lightcurve
rho_star (float) – Stellar density [g/cm^3]
dur (float) – Duration of the transit [days]
T0_list (list) – transit times in each chunk of the data
RpRs (list) – Planet-to-star radius ratio
b (list) – Impact parameter
per (list) – Orbital period [days]
sesinw (list) – sqrt(ecc)*sin(omega)
secosw (list) – sqrt(ecc)*cos(omega)
ddf (float) – if ddf is not 0, then depth variation is being used and this value is added to the base rprs, gr
occ (float) – Occultation depth in ppm
Fn (float) – nightside flux ratio in ppm
delta (float) – hotspot shift of the atmospheric variation in degrees
A_ev (float) – semi-Amplitude of the ellipsoidal variation in ppm
f1_ev (float;) – fractional constant of the EV model
A_db (float) – semi-Amplitude of the Doppler boosting in ppm
q1 (float) – LD coefficient 1
q2 (float) – LD coefficient 2
split_conf (SimpleNamespace) – The configuration for the split data
ss (SimpleNamespace) – The configuration for the supersampling
vcont (float) – contamination factor
Rstar (float) – Stellar radius in Rsun. used to calculate light travel time correction. Default: None to not perform light travel time correction
custom_LCfunc (SimpleNamespace) – object containing the custom light curve function to be added to the model. Default: None
cst_pars (dict) – additional parameters for the custom light curve function. Default: {}
- Returns:
mm (array-like) – The lightcurve model for the given parameters
model_components (dict) – The components of the model for each planet in a system
Examples
>>> from CONAN.models import TTV_Model >>> from CONAN.utils import split_transits >>> import numpy as np >>> spt = split_transits(t, P=[0.9414526], t_ref=[1375.1698], flux=f) >>> trans_mod,_ = TTV_Model(t, rho_star = rho_star, T0=spt.t0_list, RpRs=[RpRs], b =[b], >>> per=[per], sesinw=sesinw, secosw=secosw, q1=q1, q2=q2, split_conf=spt)