/TESS-Localize

Code for localizing variable star signatures in TESS Photometry

Primary LanguagePythonGNU General Public License v3.0GPL-3.0

TESS-Localize

Code for localizing variable star signatures in TESS Photometry.

The primary use of this package is to identify the location on the TPF where sources of variablity found in the aperture originate. The user only needs to provide a list of frequencies found in the aperture that belong to the same source and the number of principal components needed to be removed from the light curve to ensure it is free of systematic trends.

Installation

To install use

pip install TESS_Localize

Or clone this repository and run

cd TESS_Localize
pip install .

Usage

import TESS_Localize as tl
import lightkurve as lk
import astropy.units as u

frequency_list = [9.51112996, 19.02225993, 28.53338989, 38.04451986, 47.55564982, 57.06677979, 66.57790975, 76.08903972]

search_result = lk.search_targetpixelfile('TIC117070953')
tpf = search_result.download(quality_bitmask='default')

tutorial_example = tl.Localize(targetpixelfile=tpf, gaia=True, magnitude_limit=18,
                                  frequencies=frequency_list, frequnit=u.uHz, principal_components = 3)

Useful Functions:

tutorial_example.pca()

Result: Plots of the individual prinicpal components and plots of the lightcurve before and after removing them.

pca

tutorial_example.info()

Result: Gaia sources filtered by their distance from the fitted location of the source, and the fit statistics.

result1

tutorial_example.plot(save='Composite_Amplitude_Heatmap.png',figuresize=(8,8))

Result: An image of the composite heat map created from the contributions of the amplitudes of each frequency at every pixel. The white dots are Gaia sources, and the black 'X' is the best fit location of the source.

Plot