Code Monkey home page Code Monkey logo

sneratio's Introduction

SNeRatio: A supernova ratio calculator for x-ray observation of galaxies and galaxy clusters.

Citation

If you use this package either from the source code or from the web app for a publication please cite:

M K Erdim, C Ezer, O Ünver, F Hazar, M Hudaverdi, The relative supernovae contribution to the chemical enrichment history of Abell 1837, Monthly Notices of the Royal Astronomical Society, Volume 508, Issue 3, December 2021, Pages 3337–3344

https://doi.org/10.1093/mnras/stab2730

Web App (Under Maintenance)

This package can be used as a web app from the following link:

Description

A supernova ratio calculator for x-ray observation of galaxies and galaxy clusters.

Inter Cluster Medium (ICM) is the hot plasma that fills the environment in galaxy cluster. This plasma has been enriched in element abundance as a result of nucleosynthesis that takes place in stars and supernova explosions (SNe) over billions of years. Different types of SNe produce each element in different proportions. There are many studies on which SNe type will produce how much of each element, and it is available as "SNe yield tables" in the literature. Using elemental abundance measurements in plasma, it is possible to predict which type of SNe at what percentage. The same is true for the plasma that fills the interstellar environment within galaxies. The SNeRatio package makes this SNe ratio estimation using elemental abundance measurements.

This package calculates the best fit percentage contribution of supernova types (SNIa and SNcc) for a given abundance data for selected yield tables and models.

This package is introduced and used in the paper "The Relative Supernovae Contribution to the Chemical Enrichment History of Abell 1837" (https://doi.org/10.1093/mnras/stab2730).

Usage:

  • Installing, and using locally:

    (Type the following commands in terminal)

    1- Create a Python virtual environment (Optional)

      $ cd /path/of/the/installation/   # go to the path that you want to install the app
      $ python3 -m venv venv            # create a python3 virtual environment named venv
      $ source venv/bin/activate        # activate the virtual environment
    

    2- Clone the repository and install the requirements.

      (venv) $ git clone https://github.com/kiyami/sneratio.git   # clone the repository (or download from github.com)
    
      (venv) $ cd sneratio                                        # change directory
      (venv) $ pip3 install -r requirements.txt                   # install the required libraries via pip3
    

    3- Prepare a data file for your abundance values as the example file 'test_data.txt' in 'data' folder.

    4- Open the 'main.py' with a text editor and update the 'my_selections' part.

    For example:

      "abund_data": "data/abund_data.txt" -> enter the path of your data file
    

    5- Run the app.

      (venv) $ python3 main.py                                     # run the app
    

    6- Check the results from the 'outputs' folder.

    7- Deactivate the virtual environment.

      (venv) $ deactivate
    

    8- To uninstall the app, delete the "sneratio" and "venv" folders.

Feel free to make contributions or report bugs.

M.K.Erdim

[email protected]

[email protected]

sneratio's People

Contributors

dependabot[bot] avatar kiyami avatar

Stargazers

 avatar  avatar  avatar

Watchers

 avatar  avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.