Optimal Image Subtraction
Optimal Image Subtraction (OIS)
OIS is a Python package to perform optimal image subtraction on astronomical images. It also has a companion command-line program written entirely in C.
OIS offers different methods to subtract images:
- Modulated multi-Gaussian kernel (as described in Alard&Lupton (1998))
- Delta basis kernel (as described in Bramich (2010))
- Adaptive Delta Basis kernel (as described in Miller (2008))
Each method can (optionally) simultaneously fit and remove common background.
You can find a Jupyter notebook example with the main features at http://toros-astro.github.io/ois.
To install the Python module:
$ pip install ois
To instal and run the C command-line program, download this repo to your local machine and execute:
$ git clone https://github.com/toros-astro/ois.git $ cd ois $ make ois $ ./ois --help
The C command-line program is somewhat limited in functionality compared to the Python module. Please see the documentation for more information.
Minimal usage example
>>> from ois import optimal_system >>> diff = optimal_system(image, image_ref)
Check the documentation for a full tutorial.
kernelshape: shape of the kernel to use. Must be of odd size.
bkgdegree: degree of the polynomial to fit the background. To turn off background fitting set this to None.
method: One of the following strings
Bramich: A Delta basis for the kernel (all pixels fit independently). Default method.
AdaptiveBramich: Same as Bramich, but with a polynomial variation across the image. It needs the parameter poly_degree, which is the polynomial degree of the variation.
Alard-Lupton: A modulated multi-Gaussian kernel. It needs the gausslist keyword. gausslist is a list of dictionaries containing data of the gaussians used in the decomposition of the kernel. Dictionary keywords are: center, sx, sy, modPolyDeg
Extra parameters are passed to the individual methods.
poly_degree: needed only for
AdaptiveBramich. It is the degree
of the polynomial for the kernel spatial variation.
gausslist: needed only for
Alard-Lupton. A list of dictionaries with info for the modulated multi-Gaussian. Dictionary keys are:
- center: a (row, column) tuple for the center of the Gaussian. Default: kernel center.
- modPolyDeg: the degree of the modulating polynomial. Default: 2
- sx: sigma in x direction. Default: 2.
- sy: sigma in y direction. Deafult: 2.
Author: Martin Beroiz
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