Skip to main content

GalCraft: Building integral-field spectrograph data cubes of the Galaxy

Project description

GalCraft: Building integral-field spectrograph data cubes of the Milky Way

pypi arXiv DOI

GalCraft is a flexible software to create mock IFS observations of the Milky Way and other hydrodynamical/N-body simulations. It is entirely written in Python3 and conducts all the procedures from inputting data and spectral templates to the output of IFS data cubes in fits format.

The produced mock data cubes can be analyzed in the same way as real IFS observations by many methods, particularly codes like Voronoi binning (Cappellari & Copin 2003), Penalized Pixel-Fitting (pPXF, Cappellari & Emsellem 2004; Cappellari 2017, 2023), line-strength indices (e.g., Worthey 1994; Schiavon 2007; Thomas et al. 2011; Martín-Navarro et al. 2018), or a combination of them (e.g., the GIST pipeline, Bittner et al. 2019).

An elaborate, Python-native parallelization is implemented and tested on various machines from laptops to cluster scales.

Installation

Using pip

pip install GalCraft

From the git repo

git clone https://github.com/purmortal/galcraft.git
cd galcraft
pip install .

Example

Follow the command below to generate your first mock MUSE data cube by GalCraft:

wget https://github.com/purmortal/galcraft/archive/refs/heads/test_kit.zip
unzip test_kit.zip
cd galcraft-test_kit/tests/
GalCraft --config test_kit --default-dir configFiles/defaultDir

The data cubes are saved into ./output/test_kit/

Documentation

A detailed documentation of GalCraft will be available soon.

Citing GalCraft

If you use this software framework for any publication, please cite the original paper Wang et al. (2024), which describes the method and its application to mock Milky Way observations.

@ARTICLE{2024MNRAS.534.1175W,
       author = {{Wang}, Zixian and {Sharma}, Sanjib and {Hayden}, Michael R. and {van de Sande}, Jesse and {Bland-Hawthorn}, Joss and {Vaughan}, Sam and {Martig}, Marie and {Pinna}, Francesca},
        title = "{Validating full-spectrum fitting with a synthetic integral-field spectroscopic observation of the Milky Way}",
      journal = {\mnras},
     keywords = {Astrophysics - Astrophysics of Galaxies, Astrophysics - Instrumentation and Methods for Astrophysics},
         year = 2024,
        month = oct,
       volume = {534},
       number = {2},
        pages = {1175-1204},
          doi = {10.1093/mnras/stae2148},
archivePrefix = {arXiv},
       eprint = {2310.18258},
 primaryClass = {astro-ph.GA},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2024MNRAS.534.1175W},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

License

This software is governed by the MIT License. In brief, you can use, distribute, and change this package as you want.

Contact

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

galcraft-1.3.1.tar.gz (223.0 kB view details)

Uploaded Source

File details

Details for the file galcraft-1.3.1.tar.gz.

File metadata

  • Download URL: galcraft-1.3.1.tar.gz
  • Upload date:
  • Size: 223.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.4

File hashes

Hashes for galcraft-1.3.1.tar.gz
Algorithm Hash digest
SHA256 b71b9e2dfb0b1f8f8cab429f89aef5f47a49edd5b708cf4a2d3e03b6e4c611e0
MD5 50e2afc73785d628828fdc1a525957af
BLAKE2b-256 90f6b2c9ac8f0ee9a9175a90b260f415aaa63cb05cfca757cac53cf91ff82d8f

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page