livewdd's Introduction

Live Reconstruction using Wigner Distribution Deconvolution

This repository contains a reformulation of Wigner Distribution Deconvolution (WDD) for live reconstruction and scripts to reproduce the results in the related paper.

To benchmark against an existing implementation of WDD we refer to the implementation in pyPtychoSTEM that can be acessed at the following link: https://gitlab.com/pyptychostem/pyptychostem

The datasets for graphene and SrTiO3 can be downloaded here:

Graphene: https://zenodo.org/record/4476506#.YxioTdVBxH5
Experimental SrTiO3: https://zenodo.org/record/5113449#.Yxnh7dVBxH4

The result to reproduce the images and graphs can be downloaded here:

Result: https://zenodo.org/record/7390871#.Y4oe7zPMJH5

Requirements

The requirements for live reconstruction can be installed as dependencies with pip install . from this repository. The scripts and notebooks require the following additional packages:

click
https://github.com/sk1p/python-perf-utils
psutil
tikzplotlib

This repository is presented to reproduce the result and act as supplementary material for the paper below. Link:http://arxiv.org/abs/2212.01309

For continued development please refer the Ptychography 4.0 repository: https://github.com/Ptychography-4-0/ptychography

Citation

@article{bangun2022wdd,
title={Wigner Distribution Deconvolution Adaptation for Live Ptychography
       Reconstruction},
author={Bangun, Arya and Baumeister, Paul F and Clausen, Alex and Weber, Dieter and Dunin-Borkowski, Rafal E.},
journal={arXiv.2212.01309},
url={https://doi.org/10.48550/arXiv.2212.01309},
year={2022}
            }