Plot the spectrum of a transiting planet

This example runs VSPEC with a transiting planet scenario.

from pathlib import Path
import numpy as np
import matplotlib.pyplot as plt
import pypsg

from VSPEC import ObservationModel,PhaseAnalyzer

try:
    CFG_PATH = Path(__file__).parent / 'transit_spectrum.yaml'
except NameError:
    CFG_PATH = Path('transit_spectrum.yaml')

pypsg.docker.set_url_and_run()

Saved settings to /home/ted/.pypsg/settings.json
Reloading settings...

Initialize the VSPEC run

We read in the config file and run the model.

model = ObservationModel.from_yaml(CFG_PATH)
model.build_planet()
model.build_spectra()

/home/ted/github/VSPEC/VSPEC/gcm/heat_transfer.py:538: RuntimeWarning: Energy balance off by -9.6 %. eps = 6.0, T0 = 0.7
  warnings.warn(msg, RuntimeWarning)
Starting at phase 178.8 deg, observe for 1.5 h in 18 steps
Phases = [178.8  178.92 179.05 179.18 179.3  179.42 179.55 179.68 179.8  179.92
 180.05 180.17 180.3  180.42 180.55 180.67 180.8  180.92 181.05] deg

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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'])

Calculate the transit depth

Since this star model has no limb darkeing, no spots, and no noise, we don’t need to fit a model to our data to extract the transit depth.

cmb_data = data.total
continuum = cmb_data[:,0] # the first epoch
data_min = np.min(cmb_data,axis=1)
transit_depth = (continuum-data_min)/continuum
rp_rs = np.sqrt(transit_depth)
wavelength = data.wavelength

plt.plot(wavelength,rp_rs*100)
plt.xlabel(f'Wavelength {wavelength.unit}')
plt.ylabel(r'$\frac{R_p}{R_*}$ (%)')

Text(16.222222222222214, 0.5, '$\\frac{R_p}{R_*}$ (%)')