Metadata-Version: 2.1
Name: astroPIPS
Version: 0.3.0a4
Summary: Processes photometric data for variable stars
Home-page: https://PIPS.readthedocs.io
Author: Y. Murakami, A. Hoffman, J. Sunseri, A. Savel
Author-email: sterling.astro@berkeley.edu
Maintainer: Y. Murakami
Maintainer-email: sterling.astro@berkeley.edu
License: MIT
Description: # Period-determination and Identification Pipeline Suite (PIPS)
        
        ![GitHub tag (latest SemVer pre-release)](https://img.shields.io/github/v/tag/SterlingYM/PIPS?include_prereleases)
        ![GitHub](https://img.shields.io/github/license/SterlingYM/PIPS)
        [![Build Status](https://dev.azure.com/PIPS-developers/PIPS/_apis/build/status/SterlingYM.PIPS?branchName=master)](https://dev.azure.com/PIPS-developers/PIPS/_build/latest?definitionId=1&branchName=master)
        [![codecov](https://codecov.io/gh/SterlingYM/PIPS/branch/master/graph/badge.svg?token=R1W2S30XV2)](https://codecov.io/gh/SterlingYM/PIPS)
        [![Documentation Status](https://readthedocs.org/projects/pips/badge/?version=latest)](https://pips.readthedocs.io/en/latest/?badge=latest)
        
        PIPS is a Python pipeline designed to analyze the lightcurves of astronomical objects whose brightness changes periodically. Our pipeline can be imported quickly and is designed to be user friendly. PIPS was originally developed to determine the periods of RR Lyrae variable stars and offers many features designed for variable star analysis. We have expanded PIPS into a suite that can obtain period values for almost any type of lightcurve with both speed and accuracy. PIPS can determine periods through several different methods, analyze the morphology of lightcurves via fourier analysis, and determine stellar properties based on preexisting stellar models. Currently our team is also exploring the possibility of using this pipeline to detect periods of exoplanets as well.
        
        (last edit: April 1st, 2021) 
        
        ![](sample_lightcurve.png)
        
        --------------------------
        ## Developers
        
        * Head developer: [Yukei S. Murakami](https://www.fromthecalmsea.com) (sterling.astro@berkeley.edu)
        * Developers: [Arjun Savel](https://www.arjunsavel.com) (asavel@umd.edu), [Andrew Hoffman]() (andrew@hoffman.aero), [James Sunseri](https://sites.google.com/view/jamessunseri/home) (jamessunseri@berkeley.edu)
        
        --------------------------
        ## Publications
        Please cite the following if PIPS is utilized for a scientific project:
        * Hoffman et al. 2021 [![DOI:10.1093/mnras/stab010](https://zenodo.org/badge/DOI/10.1093/mnras/stab010.svg)](https://doi.org/10.1093/mnras/stab010) (arxiv: [2008.09778](https://arxiv.org/abs/2008.09778))
        * Murakami et al. (Paper in prep, Arxiv link pending)
        
        
        --------------------------
        ## Dependencies
        * python (>=3.7)
        * numpy
        * scipy
        * matplotlib
        * time
        * astropy
        * ~~seaborn~~
        
        
        --------------------------
        ## Usage (ver 0.3.0)
        
        1. ```$ git clone https://github.com/SterlingYM/PIPS```
        2. ```$ cd PIPS```
        4. ```$ jupyter notebook```
        5. Start a new Python notebook. In a jupyter cell, run the following:
        ```python
        import PIPS
        
        # data preparation -- create [time,mag,mag_err] list
        data = PIPS.data_readin_LPP('sample_data/005.dat',filter='V')
        phot_obj = PIPS.photdata(data)
        
        # period detection
        star.get_period(multiprocessing=False)
        
        # generate best-fit light curve
        x_th,y_th = star.get_bestfit_curve()
        
        # plot light curve
        star.plot_lc()
        plt.plot(x_th/star.period,y_th,c='yellowgreen',lw=3,alpha=0.7) # x-axis normalized to unitless phase
        plt.plot(x_th/star.period+1,y_th,c='yellowgreen',lw=3,alpha=0.7)
        ```
        
        Sample data credit: UCB SNe Search Team (Filippenko Group)
        
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Natural Language :: English
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Topic :: Scientific/Engineering :: Astronomy
Requires-Python: >3.7.0
Description-Content-Type: text/markdown
