Mass characterisation of Detached Eclipsing Binary Stars

A tool for characterising even mo'dEBs.

Setup of runtime environment

This code base was developed within the context of a Python3 virtual environment which supports Python 3.9-3.12, numpy, scipy, uncertainties, matplotlib, astropy, lightkurve, dust_extinction, mocpy, emcee, corner, mariadb and the custom ebopmaven, sed fit & deblib packages upon which the code is dependent. The dependencies are documented in the requirements.txt file.

Having first cloned this GitHub repo, open a Terminal at the root of the local repo and run the following commands. First to create and activate the venv;

$ python -m venv .modebs
$ source .modebs/bin/activate

Then run the following to set up the required packages:

$ pip install -r requirements.txt

You may need to install the jupyter kernel in the new venv:

$ ipython kernel install --user --name=.modebs

MariaDB and the data aceess layers

The MariaDB requirement is a dependency of the MariaDbTableDal data access layer class. This is one of a number of options for storing target working data as it is populated and updated by the various stages of the pipeline. The other Dal classes, the QTableDal and QTableFileDal, store the working data in astropy QTables, with the latter saving this to a file as updates are made. The significance of the MariaDbTableDal is that, by using a database table as its underlying storage mechanism, it can safely support multiple concurrent client processes. This QTable Dals are suited to small datasets and with a single running client, whereas the MariaDBTableDal is intended for large datasets and scaling out the fitting processes with the use of multiple concurrent clients.

Clearly there is a dependency of a working installation of MariaDB, either locally or accessible over a network connection. Installation instructions can be found here. There may be client side dependencies, depending on the operating system in use. Documentation covering the setup of the python MariaDB connector and configuring database connections can be found here.

The mariadb requirement may be omitted (commented out in requirements.txt) if you do not intend on using the MariaDbTableDal.

JKTEBOP

These codes have a dependency on the JKTEBOP tool for generating and fitting lightcurves. The installation media and build instructions can be found here. The JKTEBOP_DIR environment variable is used to locate the executable at runtime.

$ export JKTEBOP_DIR=~/jktebop/

Set this to match the location where JKTEBOP has been set up.

MIST Isochrones

MIST pre-build model grids are required to support stellar MASS fitting. The instructions on downloading these data are documented in the readme.txt file.

Alternative, conda virtual environment

To set up an modebs conda environment, from the root of the local repo run the following command;

$ conda env create -f environment.yaml

You will need to activate the environment whenever you wish to run any of these modules. Use the following command;

$ conda activate modebs

The conda environment sets the JKTEBOP_DIR environment variable to ~/jktebop/.