Using the Autoproc Toolkit for Data Processing and Analysis

Abstract

A typical diffraction experiment yields several pictures and datasets from various crystals within ‎a brief timeframe. This poses a barrier for the efficient operation of advanced synchrotron ‎beamlines and the following data processing. Novice users, in particular, may have a sense of ‎being inundated by the tables, graphs, and numerical information that is provided to them via ‎different data-processing systems and software packages. Here, we outline many common ‎obstacles that users face while processing a collection of photos to generate a processed dataset. ‎Our main emphasis is on the challenges that often occur while transitioning from the earliest ‎phases of converting experimental data collecting into an interpreted electron density model. ‎Examining certain data properties during processing may frequently help solve or identify ‎challenges such as unforeseen crystal formations, issues with crystal manipulation, and ‎suboptimal selection of data-collection techniques. Ultimately, it is important to distinguish ‎between concerns that are beyond of one's immediate control after the experiment has concluded ‎and those that can be dealt with later.‎ Presenting auto PROC, an innovative software solution ‎that combines external processing packages with new tools and an automated workflow script. ‎This program is designed to help users effectively handle data that is impacted by the issues ‎outlined above. It specifically focuses on automating the processing of multi-sweep data sets ‎produced from multi-axis gonio metrics. It offers consumers both instruction and important ‎insights into the processing of data that is not done online.‎

Authors and Affiliations

Muhammad D. Hassan

Keywords

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  • EP ID EP736955
  • DOI 10.47191/ijmra/v7-i06-13
  • Views 104
  • Downloads 1

How To Cite

Muhammad D. Hassan (2024). Using the Autoproc Toolkit for Data Processing and Analysis. International Journal of Multidisciplinary Research and Analysis, 7(06), -. https://europub.co.uk/articles/-A-736955