fours 0.0.3

Data post-processing for high-contrast imaging with the 4S Algorithm.

Use the 4S (Signal Safe Speckle Subtraction) for High-Contrast Imaging

This is the documentation of fours, a Python package for PSF subtraction with the 4S algorithm for exoplanet high contrast imaging (HCI). Using the 4S algorithm, we were able to recover the planet AF Lep b in archival data from 2011. This demonstrates the power of the 4S algorithm for data post-processing in HCI.

This repository contains the code needed to reproduce the results of our paper (paper in preparation).

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Documentation

A full documentation of the package, including several examples and tutorials can be found on ReadTheDocs.

This short guide will walk you through the required steps to set up and install fours.

Installation

The code of fours is available on the PyPI repository as well as on GitHub. We strongly recommend you to use a virtual environment to install the package.

Installation from PyPI

Note: The package is currently in the process of being uploaded to PyPI.

Installation from GitHub

Start by cloning the repository and install fours as a Python package:

git clone [e-mail]:markusbonse/fours.git ;
cd fours ;
pip install .

In case you intend to modify the package you can install the package in "edit mode" by using the -e flag:

pip install -e .

Additional Options

Depending on the use case fours can be installed with additional options. If you install fours from GitHub you can add them by:

pip install -e ".[option1,option2,...]"

The following options are available:

1. dev: Adds all dependencies needed to build this documentation page with sphinx.
2. plotting: Installs the libraries seaborn, matplotlib and bokeh which we use in our plots.

Demonstration dataset

If you want to reproduce our results or get some example data to play with you can download the data used in our paper. The data is publicly available at COMING SOON.

The repository contains three files:

1. 30_data: These are the NACO L'-band datasets as hdf5 files. The data was pre-processed with PynPoint.
2. 70_results: Contains the intermediate results of our paper. If you don't have access to a high-performance computing cluster you can use these files.

Reproduce our results

Check out the plot gallery in the fours documentation.

Authors and Citation

All code was written by Markus J. Bonse. Detailed information on the citation can be found here.