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super-fast source finder routine using polygon based approach

Project description

tw-source-finder

Documentation Status

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 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.

Features

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

t = o - d

m = mask derived from a comparison where t > some signal m * t = m * (o - d)

o_d = output diffuse image

=o - m * t

=o - (m * o - m * d)

=o - m * o + (m * d)

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 = o - m * o and

o_c = image of compact objects = 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

$$o* = o_d + m_c * o_c$$

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

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