Skip to content

kirxkirx/vast

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

build_and_test_ubuntu build_and_test_macos build_freebsd circlci build test Version

VaST: A Software Tool for Finding Variable Objects

The Variability Search Toolkit (VaST) is a software tool that helps in finding variable objects in a series of astronomical images. VaST can process a series of CCD frames or digitized photographic plates that are taken with the same instrument using the same filter and saved in the FITS format. The input images may be shifted, rotated, or flipped with respect to each other, but they have to have the same scale (arcsec/pix) and overlap with each other by at least ~40%. It is not necessary to have World Coordinate System (WCS) information in the FITS image header for basic processing and light curve construction. However, VaST may need to plate-solve the images using the astrometry.net code if automated object identification is required. VaST relies on Source Extractor for source detection and photometry.

VaST is written in C (and partly in BASH scripting language) and is intended to work on Linux operating system. The latest versions of VaST have also been tested on macOS (with XQuartz and MacPorts or Homebrew) and FreeBSD. The most practical way to run VaST on Windows is through Linux installed in a VirtualBox.

To install VaST, clone this repository and type make. It will inform you of any missing packages. Generally, to compile VaST, you'll need gcc, g++, gfortran, X11 libraries, and optionally libpng. A more detailed description of the installation procedure for various systems and the code itself can be found at the project's homepage and in the VaST paper.

Bug reports and pull requests, as well as new feature suggestions, are warmly welcomed!