Welcome to iCCF's documentation

This package provides clear and well-documented implementations of common
line profile indicators measured from the cross-correlation function (CCF).
And many other utility functions to work with CCFs.

I’m sold, let’s use it GitHub repository

Installation

Using pip, installation is quite easy

pip install iCCF

You can also clone the GitHub repository and install it yourself

git clone https://github.com/j-faria/iCCF
cd iCCF
python setup.py install # (or better yet, develop)

If you experience any problems during installation, open an issue on GitHub.

Getting started

If you want to read more about CCFs, go here.
The list and description of the indicators implemented in iCCF is here.

Let’s start by using iCCF with the provided example data.

import iCCF

rv, ccf = iCCF.utils.load_example_data()

This is a CCF calculated from a HARPS spectrum. It looks like this

We can now load the arrays into an Indicators class

i = iCCF.Indicators(rv, ccf)

and get the CCF indicators as attributes

i.RV
i.FWHM
i.BIS

The same thing can be accomplished by reading from a CCF fits file

i = iCCF.Indicators.from_file('CCF_file.fits')

Cite

As of now, all the indicators implemented in iCCF are based on the works of others. Please cite the appropriate papers from the following list if you use this package.

• Queloz et al 2001
• Nardetto et al 2006
• Boisse et al 2011
• Figueira et al 2013
• Santerne et al 2015
• Lanza et al 2018

See also

• Similar codes were developed by Figueira et al. A&A 557, A93 (2013)
  with a Python package available here (described in Appendix A of Santos et al. A&A 566, A35 (2014))

• A similar package (in IDL) was developed by Lanza et al. A&A 616, A155 (2018).
  It is available here.