Dust in 3D in the Milky Way

Please define an environment variable DUST_DIR before installing the code; this is a directory that will contain the dust data.

Standard python setup.py build/install

Either

sudo python setup.py install

or

python setup.py install --prefix=/some/directory/

The installation automatically downloads the relevant dust data. You might have to define an environment variable SUDO_USER if not installing with sudo.

The code can automatically download all of the necessary data (use the installation option --no-downloads to turn this off). These data are put in subdirectories of a directory DUST_DIR, with roughly the following lay-out:

$DUST_DIR/
   combined15/
      dust-map-3d.h5
   green15/
      dust-map-3d.h5
   maps/
      SFD_dust_4096_ngp.fits
  SFD_dust_4096_sgp.fits
   marshall06/
      ReadMe
  table1.dat
   sale14/
      Amap.dat
      ReadMe

The data for the Drimmel et al. (2003) map is installed in the code directory, because it is not very large.

All of the maps can be initialized similar to:

import mwdust
drimmel= mwdust.Drimmel03(filter='2MASS H')
sfd= mwdust.SFD(filter='2MASS H')

which sets up a Drimmel et al. (2003) map for the H-band filter. The maps can be evaluate for a given Galactic longitude l, Galactic latitude b, and an array (or scalar) of distances D:

drimmel(60.,0.,3.) # inputs are (l,b,D)
array([ 0.42794197])
drimmel(30.,3.,numpy.array([1.,2.,3.,10.]))
array([ 0.24911393,  0.53050198,  0.78045575,  1.14657304])
# SFD is just the constant SFD extinction
sfd(30.,3.,numpy.array([1.,2.,3.]))
array([ 1.19977335,  1.19977335,  1.19977335])

and they can be plotted as:

drimmel.plot(55.,0.5) # inputs are (l,b)

(plot not shown).

Currently only a few filters are supported; if no filter is supplied, E(B-V) is returned on the SFD scale if the object is initialized with sf10=True (which tells the code to use re-scalings from Schlafly & Finkbeiner 2011). sf10=True is the default initialization for every map, so be careful in interpreting the raw E(B-V) that come out of the code. Only use sf10=False when you have an extinction map in true E(B-V), not SFD E(B-V). No map currently included in this package is in this situation, so using sf10=False is never recommended.

To check what bandpasses are supported on the sf10=True scale do (these are all the bandpasses from Table 6 in Schlafly & Finkbeiner 2011):

from mwdust.util import extCurves  
extCurves.avebvsf.keys()

which gives:

['Stromgren u',
 'Stromgren v',
 'ACS clear',
 'CTIO R',
 'CTIO V',
 'CTIO U',
 'CTIO I',
 ...]

To check the bandpasses that are supported on the old SFD scale (sf10=False), do:

numpy.array(extCurves.avebv.keys())[True-numpy.isnan(extCurves.avebv.values())]

which gives:

array(['CTIO R', 'CTIO V', 'CTIO U', 'CTIO I', 'CTIO B', 'DSS-II i',
 'DSS-II g', 'WISE-1', 'WISE-2', 'DSS-II r', 'UKIRT H', 'UKIRT J',
 'UKIRT K', 'IRAC-1', 'IRAC-2', 'IRAC-3', 'IRAC-4', '2MASS H',
 'SDSS r', 'SDSS u', 'SDSS z', 'SDSS g', 'SDSS i', '2MASS Ks',
 '2MASS J'], 
dtype='|S14'

When making use of this code in a publication, please cite Bovy et al. (2015a). Also cite the relevant papers for the dust map that you use:

• mwdust.SFD: Schlegel et al. (1998)
• mwdust.Drimmel03: Drimmel et al. (2003)
• mwdust.Marshall06: Marshall et al. (2006)
• mwdust.Sale14: Sale et al. (2014)
• mwdust.Green15: Green et al. (2015)
• mwdust.Combined15: Combination of Marshall et al. (2006), Green et al. (2015), and Drimmel et al. (2003); see Bovy et al. (2015a)
• mwdust.Zero: Bovy et al. (2015b) 😏