TESS Aperture Photometry Pollution eStimator

Note: this module is not yet fully developed. For commercial use, please wait for v1.0.0. It is expected to be in development for at least another month.

Description

A python module that calculates a contamination factor in the aperture region of a tpf based on the relative flux of the background stars and the target.

Full documentation is available here. Below is some useful information, taken from the documentation.

Installation

Prerequisites

• numpy (>=1.21.2): to make all calculations
• scipy (>=1.7.2): to integrate the gaussian function
• astropy (>=5.0): to build data used in this module
• astroquery (>=0.4.6): to find stars in the target's region
• matplotlib (>=3.5): to plot the result (shows aperture mask with a caption at the bottom)
• lightkurve (>=2.0): to fetch and load tpf files

Python >=3.10 is required. More information about dependencies can be found here.

Install with pip install tessapps.

Running the module

Running from a notebook

A tpf is needed to run this module. If no tpf is supplied, the default is a file with HAT-P-1 (the example picture above). Here is the minimal example:

import tessapps

tessapps.run()

>>> [0.57675, 0.00191]

The first number is the contamination factor, and the second is its error. Here is a more realistic example:

import tessapps as tapps
from tessapps.search_parameters_to_tpf import find_tpf

tpf = find_tpf(TIC=346338552, mission="TESS", sector=84, exptime=120)  # HAT-P-1
contamination, error = tapps.run(tpf, result=True)

>>> The background contributes (57.675 ± 0.191)% of the total flux in the aperture region.

More information about usage in here.

Running from a terminal

Alternatively, from a terminal you can run this module as:

tapps --tpf star_tpf
python3 -m tessapps --tpf star_tpf

Authors

Leonidas Liponis

Links

PyPI page: https://pypi.org/project/tessapps/

Codeberg page: https://codeberg.org/leolip128/tessapps

Email (for contact): lliponis (at) physics.auth.gr

AI Disclosure

No LLMs were used in the making of this project. All code was generated and verified by humans, so it will only contain human-made mistakes. All commits made by bots will be refused, and commits made by humans will be checked: published code should be fully understandable by the authors.

To-Do list

• add description
• redo the examples since they reference the flux instead of the contamination factor
• add the scoring function
• add more stuff in this to-do list