This is the package associated to the 2nd phase of the exoplanet imaging data challenge. It provides the tools required for:

• injecting fake companion spectra;
• reading participants submitted results;
• evaluate and analyze the results.

Jupyter notebook tutorials

Three Jupyter notebooks are available in the tutorials folder:

• planet_injection_trainingset shows how fake companions with given spectra are injected in a test IFU dataset - this may be useful for participants wishing to replicate the injection procedure in order to train their algorithm;
• preprocessing_example shows how to perform a better preprocessing of the provided data cubes (bad pixel correction, bad frame rejection). We did not run the latter for 2 reasons: i) we wished to provide the participants with the data cubes as they come out of their respective official pipelines, and ii) different retrieval methods may suffer/benefit in different ways from softer/harder bad frame trimming or the presence of residual bad pixels.
• MEF_creation_example shows how to write your results in Multi-Extension Fits file format, the requested format for submission of your results to the data challenge.

Installation and dependencies

Using the setup.py file

You can download eidc2 (for exoplanet imaging data challenge phase 2) from its GitHub repository as a zip file. A setup.py file (setuptools) is included in the root folder of phase2. Enter the package's root folder and run:

$ python setup.py install

Using Git

First, clone the repository:

$ git clone https://github.com/exoplanet-imaging-challenge/phase2.git

Before installing the package, it is highly recommended to create a dedicated conda environment to not mess up with the package versions in your base environment. This can be done easily with (replace eidc2_env by the name you want for your environment):

$ conda create -n eidc2_env python=3.9 ipython

Then, to install eidc2, simply cd into the phase2 directory (in your local clone of the repository), and run the setup file to install the package:

$ cd eidc2
$ python setup.py install

Using Git (data challenge organizers only)

Organisers wishing to contribute or experiment with the code first need to make a fork of the repository (click on the fork button in the top right corner). Then it is a matter of cloning your fork with:

$ git clone https://github.com/<replace-by-your-username>/phase2.git

And follow the same steps as highlighted in the previous section. The only 2 exceptions are: 1) to run the setup file using the 'develop' mode, instead of 'install':

$ cd eidc2
$ python setup.py develop

2) make sure to link your phase2 directory to the upstream source, to be able to easily update your local copy after modifications by other organizers:

$ git add remote upstream https://github.com/exoplanet-imaging-challenge/phase2

Loading eidc2

Finally, start Python or IPython and check that you are able to import eidc2:

import eidc2