Montage Montage is an astronomical image toolkit with components for reprojection, background matching, coaddition and visualization of FITS files. It can be used as a set of command-line tools (Linux, OS X and Windows), C library calls (Linux and OS X) and as Python binary extension modules.

The Montage source is written in ANSI-C and code can be downloaded from GitHub ( https://github.com/Caltech-IPAC/Montage ). The Python package can be installed from PyPI ("</i>pip install MontagePy"). The package has no external dependencies. See http://montage.ipac.caltech.edu/ for details on the design and applications of Montage.

MontagePy.main modules: mBgExec

The Montage modules are generally used as steps in a workflow to create a mosaic of a set of input images. These steps are: determine the geometry of the mosaic on the sky, reproject the images to a common frame and spatial sampling; rectify the backgrounds to a common level, and coadd the images into a mosaic. This page illustrates the use of one Montage module, mBgExec, which is used to modify the backgrounds for a set of images.

Visit Building a Mosaic with Montage to see how mBgExec is used as part of a workflow to creage a mosaic (or the one shot version if you just want to see the commands). See the complete list of Montage Notebooks here.

In [1]:
from MontagePy.main import mBgExec, mViewer

Help on built-in function mBgExec in module MontagePy.main:

    mBgExec takes the background correction for each image (usually from mBgModel) and subtracts it using mBackground.
    path : str
        Path to input image directory.
    tblfile : str
        Table file list of images to correct.
    fitfile : str
        Table of background correction parameters.
    corrdir : str
        Directory for output corrected images.
    noAreas : bool, optional
        Flag indicating there are no area images.
    debug : int, optional
        Debugging output level.
    status : int
        Return status (0: OK, 1:ERROR).
    msg : str
        Return message (for errors).
    count : int
        Total number of images.
    nocorrection : int
        Number of images with no correction parameters.
    failed : int
        Number of images where the correction failed.

mBgExec Example

If we coadd a set of reprojected 2MASS images after reprojection but without doing anything about the backgrounds, the differences in background levels are obvious:

In [3]:
from IPython.display import Image

mViewer('-color black -imginfo M17/rimages.tbl \
         -ct 1 -gray M17/uncorrected.fits -2s max gaussian-log \
         -out work/M17/uncorrected.png',
        '', mode=2)