MOPEX User's Guide - IRSA

MOPEX User’s Guide
mosaic_mask.pl: Allows making of a mosaic “OR”-mask, and optionally a mask cube. See
http://irsa.ipac.caltech.edu/data/SPITZER/docs/files/spitzer/mosaic_mask.p
df for documentation. An example namelist is in
cdf/mosaic_mask_I1_example.nl.
mosaic_sed.pl: MIPS SED data reduction. This script performs interpolation and
coaddition of MIPS SED (spectral energy distribution) images, and extracts
the spectra. See
http://irsa.ipac.caltech.edu/data/SPITZER/docs/files/spitzer/mosaic_sed.pdf
for documentation.
2.5 Which Modules Should I Choose?
When running MOPEX, each data reduction step should be tailored to the dataset. Users do this
by selecting certain modules to run, and setting the input parameters for those modules. The
number of modules and parameters in MOPEX can be a little daunting, so here we give a short
introduction to the most-used modules. Detailed descriptions of the modules can be found later in
the manual.
First-time users should start with the template namelists found in the File Menu, rather than trying
to build up the name list in an empty pipeline. These templates are intended only as guides, and
will need fine-tuning for use with your data. With experience, you will be able to include or
exclude modules as needed and tune the input parameters for specific purposes. MOPEX
typically saves the results from each module in . These intermediate results can be
examined to evaluate the performance at each step.
For data reduction walk-throughs, including more advice on options to use with different data
sets, see the Spitzer Data Analysis Cookbook. We stress that these are not exhaustive, and are
continually being developed.
2.5.1 Overlap (overlap.pl)
The Overlap pipeline (run on the command line with the script overlap.pl) performs background
matching (§8.5) on the input images, and is fully described in Chapter 4. It does not set the
background level to zero, rather it adds (or subtracts) a constant to bring it to an average level.
This process is recommended for Spitzer data, as there can be variation in the sky level that will
lead to a patchy-looking final mosaic if not corrected, but this step may not be necessary if the
BCDs downloaded from the Spitzer archive have already been background-subtracted, e.g. by
MOPEX’s “Median” filtering.
Overview of MOPEX 13
Which Modules Should I Choose?