Galaxy Data Mines

A command line tool to compare object classifications given by NED and SIMBAD in common regions. Objects are found in user provided searches: "cone search" or via region names ("M83").

Watch Demo Video

Designed by Harryarts / Freepik

Motivation

When astronomers work between NED (NASA extragalactic Database) and SIMBAD (Set of Identifications, Measurements, and Bibliography for Astronomical Data) it becomes noticeable that both systems use different classification schemes for objects. Although many of these objects are identical, they may be given different names or symbols between the two systems.

As can be imagined, this situation produces some confusion, and causes a researcher (or curious mind) to go through more work in order to sort out whether or not the two systems do or do not agree about a particular object, or set of objects, in a given region of the sky.

The goal of this project is 2 fold:

1. Create a command line tool to automate some of this inter-database object comparison process.
2. Attempt to quantify and infer overall similarity between the two systems: done through selective queries to the Messier object set.

Code style

Though there are portions of the project which do not yet conform perfectly to this standard. It has and is being used as the guiding style for the project. Progress will continue to be made to match the the PEP8 standard.

Screenshots

A few screenshots of the gdmines tool.

Help Screen - Provides overview of commands and options

Match Stats - Provides a summary of the match likeness of given query
example: m83 galaxy

Plot Results 1 - Graphical display of the objects in the sky, coloured by match status
example: m83 galaxy, radius = 1 arcmin

Plot Results 2 - Graphical display of the objects in the sky, coloured by match status
example: m83 galaxy, radius = 9 arcmin

Tech/framework used

Built with

• Python 3.7+
• Click
• Astropy
• Astroquery
• Treelib
• SciPy
  • Matplotlib
  • pandas
  • NumPy

Features

• Query a region by name, M31 for example and get comparison results between NED and SIMBAD.
• Adjust parameters such as match-tolerance and obj-radius to fine tune your query.
• Do a cone search of a particular location for those who know exactly what they're looking for.
• View match statistics to get a better idea of the match breakdown.
• Show the match table for detailed match results for each object pair and their relationship.
• Display a 2D plot of overlapping objects in the sky, coloured by their computed match type.
• View the SIMBAD tree structure used to compare object classifications.
• Get a glossary of terms to define what each match type really means.

Installation

Prerequisites: update and install the latest version of python and pip.

1. Clone the repo
2. Setup a virtualenv
   1. run pip install --upgrade pip virtualenv
   2. run virtualenv env
   3. run source ./env/bin/activate on mac or source ./env/Scripts/activate on windows (assumes using gitbash). You should now see (env) above your prompt, you are now running python and pip in a virtualenv.
3. Go to the directory which contains the galaxy_data_mines project folder and run:

pip install galaxy_data_mines

alternatively cd into galaxy_data_mines and run pip install .

You should now be able to use the gdmines command.

Tests

There is a small test file tree_tester.py which tests the comparison_tree.py operations used to determine the relationships between NED and SIMBAD objects. This can be run by in the following way:

python3 tree_tester.py

How to use?

For now try this:

gdmines --help

Contribute

If you feel intrigued by the project and would like to improve upon it, please feel free to fork it and submit a pull request. Thank you.

Credits

Thank you to my thesis advisor Pauline Barmby, who developed the original idea for this project, contributed some foundational elements to the codebase, and provided guidance. The project would not exist without her contributions.

License

MIT © mshubat