Skip to main content

Uniform interface for multiple dust reddening maps.

Project description

DOI DOI

dustmaps

The dustmaps package provides a uniform interface for dealing with a number of 2D and 3D maps of interstellar dust reddening/extinction.

Supported Dust Maps

The currently supported dust maps are:

  1. Burstein & Heiles (1982; BH'82)
  2. Chen et al. (2014)
  3. Green, Schlafly, Finkbeiner et al. (2015,2018,2019; Bayestar)
  4. Marshall et al. (2006)
  5. Planck Collaboration (2013)
  6. Planck Collaboration (2016; GNILC)
  7. Sale et al. (2014; IPHAS)
  8. Schlegel, Finkbeiner & Davis (1998; SFD'98)
  9. Lenz, Hensley & Doré (2017)
  10. Peek & Graves (2010)
  11. Leike & Enßlin (2019)
  12. Leike, Glatzle & Enßlin (2020)
  13. Edenhofer et al. (2023)
  14. Chiang (2023; CSFD)

To request addition of another dust map in this package, file an issue on GitHub, or submit a pull request.

Installation

Download the repository from GitHub and then run:

python setup.py install --large-data-dir=/path/where/you/want/large/data/files/stored

Alternatively, you can use the Python package manager pip:

pip install dustmaps

Getting the Data

To fetch the data for the SFD dust map, run:

python setup.py fetch --map-name=sfd

You can download the other dust maps by changing "sfd" to "csfd", "planck", "planckGNILC", "bayestar", "iphas", "marshall", "chen2014", "lenz2017", "pg2010", "leikeensslin2019", "leike2020", "edenhofer2023" or "bh".

Alternatively, if you have used pip to install dustmaps, then you can configure the data directory and download the data by opening up a python interpreter and running:

>>> from dustmaps.config import config
>>> config['data_dir'] = '/path/where/you/want/large/data/files/stored'
>>>
>>> import dustmaps.sfd
>>> dustmaps.sfd.fetch()
>>>
>>> import dustmaps.csfd
>>> dustmaps.csfd.fetch()
>>>
>>> import dustmaps.planck
>>> dustmaps.planck.fetch()
>>>
>>> import dustmaps.planck
>>> dustmaps.planck.fetch(which='GNILC')
>>>
>>> import dustmaps.bayestar
>>> dustmaps.bayestar.fetch()
>>>
>>> import dustmaps.iphas
>>> dustmaps.iphas.fetch()
>>>
>>> import dustmaps.marshall
>>> dustmaps.marshall.fetch()
>>>
>>> import dustmaps.chen2014
>>> dustmaps.chen2014.fetch()
>>>
>>> import dustmaps.lenz2017
>>> dustmaps.lenz2017.fetch()
>>>
>>> import dustmaps.pg2010
>>> dustmaps.pg2010.fetch()
>>>
>>> import dustmaps.leike_ensslin_2019
>>> dustmaps.leike_ensslin_2019.fetch()
>>>
>>> import dustmaps.leike2020
>>> dustmaps.leike2020.fetch()
>>>
>>> import dustmaps.edenhofer2023
>>> dustmaps.edenhofer2023.fetch()

Querying the Maps

Maps are queried using astropy.coordinates.SkyCoord objects. This means that any coordinate system supported by astropy can be used as input. For example, we can query SFD'98 as follows:

>>> from dustmaps.sfd import SFDQuery
>>> from astropy.coordinates import SkyCoord
>>>
>>> sfd = SFDQuery()
>>>
>>> c = SkyCoord(
        '05h00m00.00000s',
        '+30d00m00.0000s',
        frame='icrs')
>>> print sfd(c)
0.483961

Above, we have used the ICRS coordinate system (the inputs are RA and Dec). We can use other coordinate systems, such as Galactic coordinates, and we can provide coordinate arrays. The following example uses both features:

>>> c = SkyCoord(
        [75.00000000, 130.00000000],
        [-89.00000000, 10.00000000],
        frame='galactic',
        unit='deg')
>>> print sfd(c)
[ 0.0146584   0.97695869]

Documentation

Read the full documentation at http://dustmaps.readthedocs.io/en/latest/.

Citation

If you make use of this software in a publication, please cite Green (2018) in The Journal of Open Source Software:

@ARTICLE{2018JOSS....3..695M,
       author = {{Green}, {Gregory M.}},
        title = "{dustmaps: A Python interface for maps of interstellar dust}",
      journal = {The Journal of Open Source Software},
         year = "2018",
        month = "Jun",
       volume = {3},
       number = {26},
        pages = {695},
          doi = {10.21105/joss.00695},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2018JOSS....3..695M},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

Development

Development of dustmaps takes place on GitHub, at https://github.com/gregreen/dustmaps. Any bugs, feature requests, pull requests, or other issues can be filed there. Contributions to the software are welcome.

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

dustmaps-1.0.13.tar.gz (1.8 MB view details)

Uploaded Source

Built Distribution

dustmaps-1.0.13-py3-none-any.whl (750.6 kB view details)

Uploaded Python 3

File details

Details for the file dustmaps-1.0.13.tar.gz.

File metadata

  • Download URL: dustmaps-1.0.13.tar.gz
  • Upload date:
  • Size: 1.8 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.12

File hashes

Hashes for dustmaps-1.0.13.tar.gz
Algorithm Hash digest
SHA256 895b4df742f1d7d4ec2d010cc11d42eb33fd3681ece2b348d1e511d182898206
MD5 a77157958da9930c7604c8e658a14cd1
BLAKE2b-256 a71af70408ef09d94092d072e0b3b06df6a8b1b55087b88da845620a81453d75

See more details on using hashes here.

File details

Details for the file dustmaps-1.0.13-py3-none-any.whl.

File metadata

  • Download URL: dustmaps-1.0.13-py3-none-any.whl
  • Upload date:
  • Size: 750.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.12

File hashes

Hashes for dustmaps-1.0.13-py3-none-any.whl
Algorithm Hash digest
SHA256 c16cb6e2077640f6234e83c07f2117bd3dbb6646d0ec6204c4cb81429bb2ce71
MD5 12e0a435511ddda41c2a9f33f247668d
BLAKE2b-256 567073dc954e11fbab1b4cf939debcf1083e6c1032e7b52326aaf9091befa931

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