Transients and Other Time Series Science
========================================

-  Focusing on the detection and analysis of any object that shows flux
   variation.

   -  For example: variable stars, TDE, and eclipsing binaries.
   -  **Exoplanet** and **supernova** are also trasients, but they have
      much broader impact therefore they have their own topics.

Transient Notification
----------------------

-  `pycgn - Python package for processing Gamma-ray Coordinates Network
   (GCN) notices and circulars <https://github.com/lpsinger/pygcn>`__

   -  Anonymous VOEvent client for receiving GCN/TAN notices in XML
      format

Data Access
-----------

-  `ztfquery - Access ZTF data from
   Python <https://github.com/MickaelRigault/ztfquery>`__

   -  By Mickael Rigault. **ztfquery** is a python tool to download ZTF
      (and SEDM) data

Differential Photometry
-----------------------

-  `lemon - Differential photometry for humans (and
   astronomers) <https://github.com/vterron/lemon>`__

   -  By Víctor Terrón. **LEMON** is a differential-photometry pipeline,
      written in Python, that determines the changes in the brightness
      of astronomical objects over time and compiles their measurements
      into light curves.

-  `hotpants - High Order Transform of Psf ANd Template Subtraction
   code <https://github.com/acbecker/hotpants>`__

   -  By Andy Becker.

-  `astrobase - Python modules for light curve work and variable star
   astronomy <https://github.com/waqasbhatti/astrobase>`__

   -  By `Waqas Bhatti <https://wbhatti.org/>`__. It includes
      implementations of several period-finding algorithms, batch work
      drivers for working on large collections of light curves, and a
      small web-app useful for reviewing and classifying light curves by
      stellar variability type.

Trasient Identification and Classification
------------------------------------------

-  `avocado - Photometric Classification of Astronomical Transients and
   Variables With Biased Spectroscopic
   Samples <https://github.com/kboone/avocado>`__

   -  **Avocado** is a general photometric classification code that is
      designed to produce classifications of arbitrary astronomical
      transients and variable objects.
   -  The original codebase of avocado was developed for and won the
      `2018 Kaggle PLAsTiCC
      challenge <https://www.kaggle.com/c/PLAsTiCC-2018>`__.

-  `astrorapid - Real-time Automated Photometric IDentification (RAPID)
   of astronomical transients using deep
   learning <https://github.com/daniel-muthukrishna/astrorapid>`__

   -  By `Daniel Muthukrishna <http://www.danielmuthukrishna.com/>`__.
      **RAPID** (Real-time Automated Photometric IDentification) can
      classify multiband photometric light curves into several different
      transient classes. It uses a deep recurrent neural network to
      produce time-varying classifications.

-  `astrodash - Deep learning for the automated spectral classification
   of supernovae <https://github.com/daniel-muthukrishna/astrodash>`__

   -  By `Daniel Muthukrishna <http://www.danielmuthukrishna.com/>`__.
      Software to classify the type, age, redshift and host for any
      supernova spectra. Two platforms exists: a python library that
      enables a user to classify several spectra (can classify thousands
      of spectra in seconds), and also a graphical interface that
      enables a user to view and classify a spectrum.

-  `UPSILoN- Automated Classification of Periodic Variable Stars Using
   Machine Learning <https://github.com/dwkim78/upsilon>`__

   -  **UPSILoN** (AUtomated Classification of Periodic Variable Stars
      using MachIne LearNing)

-  `SuperNNova - Open Source Photometric
   classification <https://github.com/supernnova/SuperNNova/>`__

   -  Using recurrent network technique. Based on `SuperNNova: an
      open-source framework for Bayesian, Neural Network based supernova
      classification <https://arxiv.org/abs/1901.06384>`__

Lightcurve and Exoplanet
------------------------

-  `lightkurve - A friendly package for Kepler & TESS time series
   analysis in Python <https://github.com/KeplerGO/lightkurve>`__

   -  **Lightkurve** is a community-developed, open-source Python
      package which offers a beautiful and user-friendly way to analyze
      astronomical flux time series data, in particular the pixels and
      lightcurves obtained by NASA’s Kepler and TESS exoplanet missions.

-  `eleanor - light curves from
   TESS <https://github.com/afeinstein20/eleanor>`__

   -  **eleanor** is a python package to extract target pixel files from
      TESS Full Frame Images and produce systematics-corrected light
      curves for any star observed by the TESS mission.

-  `starry - Analytic occultation light curves for
   astronomy <https://github.com/rodluger/starry>`__

   -  By `Rodrigo Luger <https://rodluger.github.io/>`__. Based on `a
      very nice
      paper <https://docs.google.com/viewer?url=https://github.com/rodluger/starry/raw/master-pdf/tex/starry.pdf>`__

-  `everest - EPIC Variability Extraction and Removal for Exoplanet
   Science Targets <https://github.com/rodluger/everest>`__

   -  A pipeline for de-trending K2 light curves with pixel level
      decorrelation and Gaussian processes.]

-  `wotan - Automagically remove trends from time-series
   data <https://github.com/hippke/wotan>`__

   -  By `Michael Hippke <http://www.jaekle.info/>`__. Offers free and
      open source algorithms to automagically remove trends from
      time-series data.