lcps: light curve pre-selection

Introduction

lcps is a tool to search for transit-like features (i.e. dips) in photometric data.

Its main purpose is to restrict large sets of light curves to a number of files that show interesting behavior (i.e. drops in flux). While lcps is adaptable to any format of time series, its current I/O module was designed specifically for photometry of the Kepler spacecraft. It extracts the pre-conditioned PDCSAP data from light curves files created by the standard Kepler pipeline. It can also handle csv-formatted ascii files.

lcps uses a sliding window technique to compare a section of flux time series with its surroundings. A dip is detected if the flux within the window is lower than a threshold fraction of the surrounding fluxes.

Installation

pip

The easiest and recommended way of installing lcps is via pip. To install the latest released version of lcps from PyPI:

$ pip install lcps

From Source

If you prefer to use the most current development version, you can download lcps from GitHub.

After unpacking the package, go to its root directory and run the setup script:

$ sudo python setup.py install

Quick Start Guide

Use the lcps_batch module to run lcps on a set of Kepler long cadence photometry, say, a complete K2 campaign:

>>> import lcps
>>> path = 'K2C8/'             # path to light curve files
>>> logfile = 'K2C8/lcps.log'  # dip detections are written to this file
>>> lcps.lcps_batch.batchjob(path, logfile)

Module Reference

Indices and tables