Senior Thesis Program

Installation

Prerequisites

• Python 3.9+
• Numpy
• Matplotlib
• Astropy
• Photometry-plus
• Photutils
• Django
• Statistics

Install prerequisites

pip install numpy matplotlib astropy photutils django statistics

Primary files

git clone --recurse-submodules https://github.com/blpearson44/automated-lightcurves.git

Usage

This script is a wrapper around photometryplus to gather magnitude data on a target star. From the command line, for a description of all the commands, run

path/to/python path/to/dir/photometry_app.py --help

Each command has flags that can be set, check them with

path/to/python path/to/dir/photometry_app.py command --help

For a more detailed description of how to use this application, see section 4.4 of the senior thesis paper included in this repository.

Run over bulk data

Though the application comes with a built in bulk run, depending on the use case it may make more sense to use a separate run script. run.sh and photometry_app.py should be modified to have accurate filepaths (for logging and calibration) and then Stars_List.csv should be modified to the stars being observed. Note that the name of the star is how the program finds the directory (located in run_wcs.py) for the star. If running over data that does not have WCS data (this can generally be checked through the FITS header) then use run_non_wcs.sh and update run_non_wcs.py. In this case, ensure that ./token.txt exists and contains your API key from Astrometry. Note that data without WCS may be lower in quality, and this may cause the program to fail even if it does successfully get the WCS from Astrometry.net.