Getting Started
This package leverages a parallelization boiler-plate code to provide a super fast source finder routine which deletes background sources using a polygon based approach.
Watch the video on YouTube video for detailed instructions on how to use the data analysis scripts. Hopefully, it will not put you to sleep! More detailed written instructions may follow.
Main scripts
There are two main scripts in the package, viz: get_morphology_images and get_galaxy_parameters.
get_morphology_images
Uses morphological erosion and dilation to remove background sources from a radio astronomy image. It extends the technique described in Rudnick, 2002.
The process can be described through the following equations:
o = original image
d = output from erosion/dilation
t = white TopHat, which should show only 'compact' structures
m = mask derived from a comparison where t > some signal
\(m*d\) would add the masked dilated image to the ‘diffuse’ image and we do not want to do that so we ignore it to get \(o_d\) = output diffuse image and \(o_c\) = image of compact objects.
\(o_d = o - m * o\)
\(o_c = m * o\)
So the original image equates to \(o_d + o_c\). We may want to judiciously add selected components of \(o_c\) to \(o_d\) to get a final \(o*\). We select the components of \(o_c\) we wish to add by masking their defining polygons to get a mask \(m_c\)
get_galaxy_parameters
Integrates the signal contained within specified polygon areas of a radio astronomy image to derive integrated flux densities and other parameters of a radio source.
Requirements
The code has been tested with python 3.8 on Ubuntu 20.04. See pyproject.toml or requirements.txt for package dependencies.
Installation
Install from source
> pip install .
Use the routine
> tw-source-list -f xyz.fits -t 6.5