{
    "info": {
        "author": "Nicolas Chotard",
        "author_email": "nchotard@in2p3.fr",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 3 - Alpha",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python :: 2",
            "Topic :: Scientific/Engineering :: Astronomy",
            "Topic :: Software Development :: Build Tools"
        ],
        "description": ".. image:: http://readthedocs.org/projects/extinctions/badge/?version=latest\n   :target: http://extinctions.readthedocs.io/en/latest/?badge=latest\n   :alt: Documentation Status\n      \n.. image:: https://landscape.io/github/nicolaschotard/extinctions/master/landscape.svg?style=flat\n   :target: https://landscape.io/github/nicolaschotard/extinctions/master\n   :alt: Code Health\n\n.. image:: https://travis-ci.org/nicolaschotard/extinctions.svg?branch=master\n   :target: https://travis-ci.org/nicolaschotard/extinctions\n   :alt: Travis CI build status (Linux)\n\n.. image:: https://codecov.io/gh/nicolaschotard/extinctions/branch/master/graph/badge.svg\n  :target: https://codecov.io/gh/nicolaschotard/extinctions\t \n\n.. inclusion-marker-do-not-remove\n\t \nextinctions\n-----------\n\nPython package including different extinction laws and dust maps. Useful to\n\n- get E(B-V) for a set of coordinates (or list of coordinates) from different\n  \n  - distant sources (IRSA, NED)\n  - local maps (SFD98, Schlafly 2014, Planck 2013, Green 2015)\n\n- compute the ISM transmission for different extincion laws\n  \n  - CCM89: Cardelli, Clayton and Mathis (`<http://adsabs.harvard.edu/abs/1989ApJ...345..245C>`_)\n  - OD94: O'Donnell (`<http://adsabs.harvard.edu/abs/1994ApJ...422..158O>`_)\n  - FM98: Fitzpatrick & Massa (1998)\n  - G08: Goobar (`<http://adsabs.harvard.edu/abs/2008ApJ...686L.103G>`_)\n    \nInstallation\n------------\n\nTo install::\n\n  git clone https://github.com/nicolaschotard/extinctions.git\n  pip install extinctions/\n\nTo install in a local directory ``mypath``, use::\n\n  pip install --prefix='mypath' extinctions/\n\nand do not forget to add it to your PYTHONPATH.\n\nTo upgrade to a new version (after a ``git pull`` or a local modification), use::\n\n  pip install --upgrade (--prefix='mypath') extinctions/\n\nTo install a release version (no release version available yet)::\n\n  pip install http://github.com/nicolaschotard/extinctions/archive/v0.1.tar.gz\n\nAlso works with the master::\n\n  pip install (--upgrade) https://github.com/nicolaschotard/extinctions/archive/master.zip\n\nIn the future, release versions will be listed at this `location\n<http://github.com/nicolaschotard/extinctions/releases>`_.\n\n\nDependencies\n------------\n\n`extinctions` has a few python dependencies listed in the `requirements\n<requirements.txt>`_ file. To install them all, use::\n\n  pip install -r requirements.txt\n\nRequirements are:\n\n- numpy==1.11.2\n- scipy==0.17.1\n- matplotlib==1.5.1\n- seaborn==0.7.0\n- pyyaml==3.11\n- astropy==1.2.1\n- requests==2.10.0\n- astroquery==0.3.1\n- wget==2.2\n- healpy==1.9.1\n\n\n  \nDust map setup\n--------------\n\nYou can automatically download the dust maps listed in the `maps.yaml\n<extinction/data/maps.yaml>`_ file using the script `get_maps.py`. It\nwill, by default, put them in $HOME/.extinction/maps, but other\nlocations are of course possible (option `--outdir`). If you choose to\nstore them in an other diretory, you must set a $MAPSDIR environment\nvariable pointing to it. Already existing maps in the output directory\nwill not be downloaded again.\n\nThe available dust maps are:\n\n- `SFD98 <http://lambda.gsfc.nasa.gov/product/foreground/dust_map.cfm>`_, full sky Healpy format\n- SFD98 `north <http://www.sdss3.org/svn/repo/catalogs/dust/trunk/maps/SFD_dust_4096_ngp.fits>`_ and `south <http://www.sdss3.org/svn/repo/catalogs/dust/trunk/maps/SFD_dust_4096_sgp.fits>`_ dust maps\n- `Planck <http://irsa.ipac.caltech.edu/data/Planck/release_1/all-sky-maps/previews/HFI_CompMap_ThermalDustModel_2048_R1.20/index.html>`_\n- `Schlafly 2014 <http://lambda.gsfc.nasa.gov/product/foreground/fg_ebv_map_info.cfm>`_\n- `Green 2015 <http://lambda.gsfc.nasa.gov/product/foreground/fg_ebv_2015_map_info.cfm>`_\n\n\nDownload the maps\n-----------------\n\nTo download the extinction maps listed above, use the script\n`get_maps.py`. The following options are available::\n\n  get_maps.py -h\n  usage: get_maps.py [-h] [--outdir OUTDIR] [--update] [--list]\n                   [--select SELECT] [--exclude EXCLUDE]\n\n  optional arguments:\n     -h, --help         show this help message and exit\n     --outdir OUTDIR    Output directory in where to put the dust maps\n     --update           Update the maps directory in case of changes of maps.yaml\n     --list             List of available maps and exit\n     --select SELECT    Select maps to download (coma separated)\n     --exclude EXCLUDE  Exclude map(s) (coma separated).If the select option is\n                        used, the exclude option will be ignored.\n\n\nUsage\n-----\n\nGet E(B-V)\n``````````\n\nHere is an example of how to get the value of E(B-V) for a set of\ncoordinates (RA,DEC):\n\n.. code:: python\n\t  \n  In [1]: ra, dec = 340.83, -9.59 # could also be arrays or list of ra/dec\n  In [2]: from extinctions import reddening\n  In [3]: red = reddening.Reddening(ra, dec) # ra dec can also be lists of coordinates\n  INFO: Loading the maps from local directory /home/chotard/.extinction/maps/\n  - green is loaded\n  - schlafly is loaded\n  - sfd is loaded\n  - planck is loaded\n\nYou can then get E(B-V) from different sources:\n\n.. code:: python\n\t  \n  # from the local maps\n  In [4]: red.query_local_map(dustmap='sfd')\n  Out[4]: 0.047723956233310674\n  In [5]: red.query_local_map(dustmap='schlafly')\n  Out[5]: 0.062566755984547445\n  In [6]: red.query_local_map(dustmap='planck')\n  Out[6]: 0.052058338535565914\n  In [7]: red.query_local_map(dustmap='green')\n  Out[7]: 0.035786284169101318\n\n\n  # from the SFD98 north/south maps using `sncosmo`\n  In [8]: red.from_sncosmo()\n  Out[8]: array([ 0.0473752])\n\n  # Using astroquery\n  In [9]: red.from_astroquery()\n  Downloading http://irsa.ipac.caltech.edu//workspace/TMP_XG1Joz_30445/DUST/340.8300_-9.5900.v0001/extinction.tbl\n  |==============================================================================================| 4.3k/4.3k (100.00%)         0s\n  Out[9]: [0.047377326565143825]\n\n\nMake some plots\n```````````````\n\nTo have a look at the different extinction laws amd dust maps, you can\nuse the script `extinction_plots.py`.\n",
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