Magni: A Python Package for Compressive Sampling and Reconstruction of Atomic Force Microscopy Images
by Thomas Arildsen
Our new software metapaper Magni: A Python Package for Compressive Sampling and Reconstruction of Atomic Force Microscopy Images has just been published in Journal of Open Research Software. The paper describes our new software package Magni:
Magni is an open source Python package that embraces compressed sensing and Atomic Force Microscopy (AFM) imaging techniques. It provides AFM-specific functionality for undersampling and reconstructing images from AFM equipment and thereby accelerating the acquisition of AFM images. Magni also provides researchers in compressed sensing with a selection of algorithms for reconstructing undersampled general images, and offers a consistent and rigorous way to efficiently evaluate the researchers own developed reconstruction algorithms in terms of phase transitions. The package also serves as a convenient platform for researchers in compressed sensing aiming at obtaining a high degree of reproducibility of their research.
Go ahead and check it out if you are into compressed sensing or atomic force microscopy. Pull requests welcome if you have ideas.