General
-----------------------------------------
We are releasing our Planck-based two-component fit results as a set of nested 
order Nside=2048 HEALPix maps in Galactic coordinates. These maps, which 
include 545 GHz optical depth, hot dust temperature, and associated 
uncertainties, are contained in the file planck_2comp.fits. Our data release 
also includes software to obtain reddening and emission predictions based on
this results summary file. The util_2comp.tar.gz archive contains IDL and 
Python implementations of the emission/reddening prediction software. We do
not recommend extrapolating our two-component emission model to frequencies 
outside of the 100-3000 GHz range over which the model has been fit.


Notes
------------------------------------------
We have conducted a thorough comparison of the values output by the IDL/Python
software tools, and verified that both return identical emission/extinction
predictions for identical queries.


Software Download
-----------------------------------------
After unpacking util_2comp.tar.gz, you should see the following directory
structure.

$ tree -d util_2comp
util_2comp
|-- pro
`-- python

util_2comp/pro contains the IDL software utilities. util_2comp/python contains 
the Python software utilities.


Environment
------------------------------------------
Both the Python and IDL implementations require that the ETC_2COMP environment 
variable be set to the directory containing the Planck-based two-component 
fit results summary file, planck_2comp.fits.


IDL
-----------------------------------------
Include util_2comp/pro in your IDL_PATH.

IDL> pred = getval_2comp(nu=150)

In this example, the return value is a full-sky, Nside=2048 HEALPix map
of predicted 150 GHz thermal dust emission in MJy/sr. See the header 
documentation for further options and details.

The IDL implementation has been tested with IDL 7.1.1, 8.1, 8.2.2 and IDLUTILS
v5_4_24.


Python
-----------------------------------------
Include util_2comp/python in your PYTHONPATH.

>> import util_2comp
>> pred = util_2comp.getval_2comp(nu=150)

In this example, the return value is a NumPy array containing a full-sky, 
Nside=2048 HEALPix map of predicted 150 GHz thermal dust emission in MJy/sr. 
See the docstrings for further options and details.

The Python implementation has been tested with Python 2.7.1, NumPy 1.6.0, and 
PyFITS 2.4.0.