pyPETaL: A Pipeline for Estimating AGN Time Lags

pyPetal is a pipeline made in python to obtain time lags from multi-band AGN time-series data. Normally, AGN geometric and kinematic analyses (e.g. reverberation mapping) utilize a variety of different tools to obtain time lags between two (or more) light curves. This package combines four popular algorithms for estimating time lags (pyCCF, pyZDCF, PyROA, and JAVELIN), and uses the popular Damped Random Walk algorithm to model input light curves for outlier rejection.

Currently, pyPetal has combined the functionality of pyCCF, pyZDCF, PyROA, MICA2m and JAVELIN to produce cross-correlation functions, discrete correlation functions, and mean time lags. This is only made to run on Linux-based operating systems, though this may be improved in the future.

Getting Started

• Installation
• A Quick Start to pyPetal

Tutorials

• DRW-Based Outlier Rejection
• Detrending
• pyCCF
• pyZDCF
• PLIKE
• PyROA
• MICA2
• JAVELIN
• Weighting
• Using All Modules
• Loading Prior Results
• Using pyPetal From an Input File
• Using pyPetal from the Command Line
• References

API

• pyPetal Arguments
• pyPetal Output
• pyPetal Output Files and Directories
• DRW-Based Outlier Rejection
• pyCCF
• pyZDCF
• PyROA
• JAVELIN
• Weighting
• Loading Prior Results
• Plotting

Citing pyPetal

To cite the pyPetal code itself, use the ASCL reference: /https://ascl.net/2401.004

To cite the paper pyPetal was used in: https://ui.adsabs.harvard.edu/abs/2023arXiv230501014S

References

pyPetal makes use of a multitude of packages:

• pyCCF: https://arxiv.org/abs/astro-ph/9802103, http://ascl.net/code/v/1868

• pyZDCF: https://doi.org/10.5281/zenodo.7253034,

• PLIKE: http://arxiv.org/abs/1302.1508

• PyROA: https://ui.adsabs.harvard.edu/abs/2021MNRAS.508.5449D

• MICA2: https://ui.adsabs.harvard.edu/abs/2016ApJ…831..206L

• JAVELIN: http://adsabs.harvard.edu/abs/2013ApJ…765..106Z, http://adsabs.harvard.edu/abs/2011ApJ…735…80Z, http://adsabs.harvard.edu/abs/2016ApJ…819..122Z