JASMINE: Joint Analysis of Simulation for Microlensing INterested Events
pip installable as jasmine-sis
pip install jasmine-sis
- Make sure you downloaded the
master_file.txtandwfirstColumnNumbers.txtfrom the data challenge folder:
https://github.com/microlensing-data-challenge/data-challenge-1/tree/master/Answers - Run
python jasmine/files_organizer/data_challenge_prep.py, changing path as needed. It splits master file and create 4 new files:- binary_star.csv
- bound_planet.csv
- cataclysmic_variables.csv
- single_lens.csv
import jasmine.files_organizer.lightcurve_cls as lc
the_lightcurve = lc.LightcurveEvent(2) # Binary star # Call the lightcurve class
vars(the_lightcurve).keys() # See what are the available attributes and subclasses
the_lightcurve.lens # subclass
lightcurve_datapoints = the_lightcurve.lightcurve_data(filter_='W149', folder_path_='../data') # Get the lightcurve datapoints
See notebook analysis/getting_information_about_a_lightcurve.ipynb for details.
If you opt to not use a class. You can use the functions below:
See notebook analysis/reading_the_data_challenge.ipynb for more details.
Call the function you need, and it returns a pandas dataframe:
import jasmine.files_organizer.data_challenge_reader as dcr
dataframe = dcr.binary_star_master_reader()dataframe = dcr.bound_planet_master_reader()dataframe = dcr.cataclysmic_variables_master_reader()dataframe = dcr.single_lens_master_reader()
Obs: The column you are looking for is: data_challenge_lc_number.
The function lightcurve_data_reader reads the light curve files and returns a pandas dataframe with BJD, Magnitude, Error and days (days = BJD - 2450000) ':
import jasmine.files_organizer.data_challenge_reader as dcr
lightcurve_df = dcr.lightcurve_data_reader(data_challenge_lc_number_=5, folder_path_='../data')