sfft 1.6.3

Image Subtraction in Fourier Space

.. image:: https://github.com/thomasvrussell/sfft/blob/master/docs/sfft_logo_gwbkg.png

SFFT: Saccadic Fast Fourier Transform for image subtraction

.. image:: https://img.shields.io/pypi/v/sfft.svg :target: https://pypi.python.org/pypi/sfft :alt: Latest Version

.. image:: https://static.pepy.tech/personalized-badge/sfft?period=total&units=international_system&left_color=grey&right_color=orange&left_text=Downloads :target: https://pepy.tech/project/sfft

.. image:: https://img.shields.io/badge/python-3.7-green.svg :target: https://www.python.org/downloads/release/python-370/

.. image:: https://zenodo.org/badge/doi/10.5281/zenodo.6463000.svg :target: https://doi.org/10.5281/zenodo.6463000 :alt: 1.0.6

.. image:: https://img.shields.io/badge/License-MIT-yellow.svg :target: https://opensource.org/licenses/MIT | Saccadic Fast Fourier Transform (SFFT) is an algorithm for fast & accurate image subtraction in Fourier space. SFFT brings about a remarkable improvement of computational performance of around an order of magnitude compared to other published image subtraction codes.

SFFT method is the transient detection engine for several ongoing time-domain programs, including the DESIRT <https://ui.adsabs.harvard.edu/abs/2022TNSAN.107....1P/abstract>_ survey based on DECam & DESI, the DECam GW-MMADS Survey for GW Follow-ups and the JWST Cycle 3 Archival program AR 5965 <https://www.stsci.edu/jwst/science-execution/program-information?id=5965>. SFFT is also the core engine for the differential photometry pipeline of the Roman Supernova PIT <https://github.com/Roman-Supernova-PIT>.

Get started

• Documentation: https://thomasvrussell.github.io/sfft-doc/ [recommended]
• Installation: https://thomasvrussell.github.io/sfft-doc/installation/
• Tutorials: https://thomasvrussell.github.io/sfft-doc/tutorials/
• Source code: https://github.com/thomasvrussell/sfft
• Contact the author: [e-mail] or [e-mail]

Installation

To install the latest release from PyPI, use pip: ::

pip install sfft

For more detailed instructions, see the install guide <https://thomasvrussell.github.io/sfft-doc/installation/>_ in the docs.

Citing

Image Subtraction in Fourier Space, Lei Hu et al. 2022, The Astrophysical Journal, 936, 157

See ADS Link: https://ui.adsabs.harvard.edu/abs/2022ApJ...936..157H/abstract

Publications using SFFT method

See ADS Library: https://ui.adsabs.harvard.edu/public-libraries/lc4tiTR_T--92f9k0YrRQg