Library Usage

To take advantage of some of the more advance options in astrosource, you want to import the library as part of a larger code base.

Getting Started

The fundamental role of astrosource is the analysis of time-series data. So, the basic class in astrosource is called TimeSeries.

There are only 2 required inputs: a list of targets and a directory where the input files can be found.

from astrosource import TimeSeries
import numpy as np

targets = np.array([(12.7249867, -34.68742, 0, 0)])
indir = '/home/wbyrd/data/my-target/'

ts = TimeSeries(indir=indir, targets=targets)

This will instantiate the TimeSeries object and sort through all the files in indir.

Required

The possible inputs are: indir str

The location of either the input photometry files or fz files with photometry tables.

targets

A numpy array of targets. Each target must be padded with 2 extra zeros at the end.

Optional Inputs

format str

A file extension for the files in indir which contain the photometry data.

imgreject float

Image fraction rejection allowance. Defaults to 0.0. Increasing this will allow astrosource to reject some of your data files if there are not enough comparison stars.

Analysis

To find the stars in the photometry tables and find comparisons. This will perform photometric calibration unless calib=False is passed.

If you would like to output CSV files with the photometry data, you need to pass filesave=True as shown below.

This is an example of the full analysis code using the input directory indir and targets from above.

The plot stage has 3 optional inputs:

• detrend: detrend exoplanet data
• period: recursively attempt to find a period (for periodic sources like variable stars or binaries)
• eebls: Edge Enhanced Box-fitting Least Squares analysis for an exoplanet transit curve