JUX

This project is concerned with processing and identification of features present in astronomical light data, often referred to as lightcurve data. It was created in response to 2 ocassions:

• ISRO Problem Statement: Inter-IIT Tech Meet 10.0
• XUVI: Summer Project, Astronomy Club IITK, 2022

How to install it?

pip install jux

Dependencies will build and you can proceed using it.

What all can it process?

Currently, feature detection is supported for:

• Exoplanet detection
  • Transit Photometry
  • Astrometry
• Solar Flare detection

How to use it?

Sample data can be downloaded here.

Exoplanet detection

1. Transit Photometry

import pandas as pd
from jux.exoplanet import TransitingExoplanet

R = 7e8

df = pd.read_csv('transit_data.csv')
time = df[df.columns[0]]
fraw = df[df.columns[1]]

exoplanet = TransitingExoplanet(time, fraw, R)
exoplanet.plot_raw_data()

exoplanet.correct_data(threshold_brightness=0.998)
exoplanet.plot_corrected_data()

print("Radius of the planet is {} km".format(int(exoplanet.radius / 1000)))
print("The planet orbits around it's host star every {} Earth days".format(round(exoplanet.orbital_period, 2)))
print("The transit duration of the exoplanet is {} hours".format(round(exoplanet.transit_duration, 2)))

2. Astrometry

import pandas as pd
from jux.exoplanet import Star

M = 1e30

df = pd.read_csv('astrometry_data.csv')
time = df[df.columns[0]]
vel = df[df.columns[1]]

star = Star(time, vel, M)
star.plot_raw_fourier_transform()

star.correct_fourier_transform(threshold_power=50)
star.plot_individual_planet_influence()

for i in range(len(star.planets)):
    star.print_planet_details(i)
    print("")

Solar Flare detection

from jux.sun import Flares, read_lc_file

path_to_lc = 'ch2_xsm_20200928_v1_level2.lc'
time, rate = read_lc_file(path_to_lc)

flares = Flares(time, rate)
flares.identified.plot()
flares.print_details()