Plot the lightcurve of a star with faculae

This example plots the lightcurve caused by a

photosphere covered in faculae.

from pathlib import Path
from astropy import units as u
import matplotlib.pyplot as plt
import libpypsg

from VSPEC import ObservationModel, PhaseAnalyzer
from VSPEC import params
from VSPEC.params.gcm import vspec_to_pygcm

SEED = 24
libpypsg.docker.set_url_and_run()

Saved settings to /home/runner/.libpypsg/settings.json
Reloading settings...

Initialize the VSPEC run parameters

For this example, we will create the parameter objects explicitly. This can also be done using a YAML file.

header = params.Header(
    data_path=Path('.vspec/faclae_lightcurve'),
    spec_grid = params.VSPECGridParameters(
        max_teff=3900*u.K,min_teff=2300*u.K,
        impl_bin='rust',impl_interp='scipy',fail_on_missing=False
    ),
    seed=SEED, verbose=0
)
star = params.StarParameters(
    psg_star_template='M',
    teff=3000*u.K,
    mass=0.1*u.M_sun,
    radius=0.15*u.R_sun,
    period=10*u.day,
    misalignment_dir=0*u.deg,
    misalignment=0*u.deg,
    ld=params.LimbDarkeningParameters.solar(),
    faculae=params.FaculaParameters(
        distribution='iso',
        equillibrium_coverage=0.01,
        burn_in=2*u.day,
        mean_radius=0.01*u.R_sun,
        logsigma_radius=0.3,
        depth=0.01*u.R_sun,
        mean_timescale=1*u.day,
        logsigma_timescale=0.2,
        floor_teff_slope=0*u.K/u.km,
        floor_teff_min_rad=100*u.km,
        floor_teff_base_dteff=-100*u.K,
        wall_teff_slope=0*u.K/u.km,
        wall_teff_intercept=100*u.K
    ),
    spots=params.SpotParameters.none(),
    flares=params.FlareParameters.none(),
    granulation=params.GranulationParameters.none(),
    grid_params=10000,
)

planet = params.PlanetParameters.std(
    init_phase=180*u.deg, init_substellar_lon=0*u.deg)
system = params.SystemParameters(
    distance=1.3*u.pc,
    inclination=30*u.deg,
    phase_of_periastron=0*u.deg
)
observation = params.ObservationParameters(
    observation_time=3*u.day,
    integration_time=30*u.min
)
psg_params = params.psgParameters(
    gcm_binning=200,
    phase_binning=1,
    use_molecular_signatures=True,
    use_continuum_stellar=True,
    nmax=0,
    lmax=0,
    continuum=['Rayleigh', 'Refraction', 'CIA_all'],
)
instrument = params.InstrumentParameters.niriss_soss()

def gcm_getter():
    return vspec_to_pygcm(
        shape=(30,30,30),
        epsilon=7,
        star_teff=3800*u.K,
        r_star=0.2*u.R_sun,
        r_orbit=0.05*u.AU,
        lat_redistribution=0.0,
        p_surf=1*u.bar,
        p_stop=1e-5*u.bar,
        wind_u=0*u.km/u.s,
        wind_v=0*u.km/u.s,
        albedo=0.3,
        emissivity=1.0,
        gamma=1.4,
        molecules={'CO2':1e-4}
    )
gcm = params.gcmParameters(
    gcm_getter=gcm_getter,
    mean_molec_weight=28,
    is_static=True
)


parameters = params.InternalParameters(
    header=header,
    star=star,
    planet=planet,
    system=system,
    obs=observation,
    psg=psg_params,
    inst=instrument,
    gcm=gcm
)

Run the simulation

model = ObservationModel(params=parameters)
model.build_planet()
model.build_spectra()

Creating interpolators:
thermal
thermal, combined
thermal, combined, stellar
thermal, combined, stellar, photon noise
thermal, combined, stellar, photon noise, detector noise
thermal, combined, stellar, photon noise, detector noise, telescope noise
thermal, combined, stellar, photon noise, detector noise, telescope noise, background noise
thermal, combined, stellar, photon noise, detector noise, telescope noise, background noise, transit
Finished!

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Load in the data

We can use VSPEC to read in the synthetic data we just created.

data = PhaseAnalyzer(model.directories['all_model'])

Get the lightcurve

We will look in a few different wavelengths.

wl_pixels = [0, 300, 500, 700]
time = data.time.to(u.day)
for i in wl_pixels:
    wl = data.wavelength[i]
    lc = data.lightcurve(
        source='star',
        pixel=i,
        normalize=0
    )
    plt.plot(time, lc, label=f'{wl:.1f}')
plt.legend()
plt.xlabel(f'time ({time.unit})')
_ = plt.ylabel('Flux (normalized)')