Literature DB >> 35232526

Reproducible Spectrum and Hyperspectrum Data Analysis Using NeXL.

Nicholas W M Ritchie1.   

Abstract

NeXL is a collection of Julia language packages (libraries) for X-ray microanalysis data processing. NeXLCore provides basic atomic and X-ray physics data and models including support for microanalysis-related data types for materials and k-ratios. NeXLMatrixCorrection provides algorithms for matrix correction and iteration. NeXLSpectrum provides utilities and tools for energy-dispersive X-ray spectrum and hyperspectrum analysis including display, manipulation, and fitting. NeXL is integrated with the Julia language infrastructure. NeXL builds on the Gadfly plotting library and the DataFrames tabular data library. When combined with the DrWatson package, NeXL can provide a highly reproducible environment in which to process microanalysis data. Data availability and reproducible data analysis are two keys to scientific reproducibility. Not only should readers of journal articles have access to the data, they should also be able to reproduce the analysis steps that take the data to final results. This paper will both discuss the NeXL framework and provide examples of how it can used for reproducible data analysis.

Entities:  

Keywords:  EDS; hyperspectrum; quantification; reproducible; software

Year:  2022        PMID: 35232526      PMCID: PMC9437143          DOI: 10.1017/S143192762200023X

Source DB:  PubMed          Journal:  Microsc Microanal        ISSN: 1431-9276            Impact factor:   4.099


  11 in total

1.  Logarithmic 3-Band Color Encoding: Robust Method for Display and Comparison of Compositional Maps in Electron Probe X-ray Microanalysis.

Authors: 
Journal:  Microsc Microanal       Date:  1999-09       Impact factor: 4.127

2.  Introduction to hierarchical clustering.

Authors:  Michael J Guess; Scott B Wilson
Journal:  J Clin Neurophysiol       Date:  2002-04       Impact factor: 2.177

3.  Automated analysis of SEM X-ray spectral images: a powerful new microanalysis tool.

Authors:  Paul G Kotula; Michael R Keenan; Joseph R Michael
Journal:  Microsc Microanal       Date:  2003-02       Impact factor: 4.127

4.  Reproducible research in computational science.

Authors:  Roger D Peng
Journal:  Science       Date:  2011-12-02       Impact factor: 47.728

5.  Diluvian Clustering: A Fast, Effective Algorithm for Clustering Compositional and Other Data.

Authors:  Nicholas W M Ritchie
Journal:  Microsc Microanal       Date:  2015-08-24       Impact factor: 4.127

6.  Maximum pixel spectrum: a new tool for detecting and recovering rare, unanticipated features from spectrum image data cubes.

Authors:  D S Bright; D E Newbury
Journal:  J Microsc       Date:  2004-11       Impact factor: 1.758

7.  Electron probe microanalysis of thin films and multilayers using the computer program XFILM.

Authors:  Xavier Llovet; Claude Merlet
Journal:  Microsc Microanal       Date:  2009-12-24       Impact factor: 4.127

8.  ϕ(ρz) Distributions in Bulk and Thin-Film Samples for EPMA. Part 2: BadgerFilm: A New Thin-Film Analysis Program.

Authors:  Aurélien Moy; John Fournelle
Journal:  Microsc Microanal       Date:  2021-04       Impact factor: 4.127

9.  Manganese-Cycling Microbial Communities Inside Deep-Sea Manganese Nodules.

Authors:  Marco Blöthe; Anna Wegorzewski; Cornelia Müller; Frank Simon; Thomas Kuhn; Axel Schippers
Journal:  Environ Sci Technol       Date:  2015-06-12       Impact factor: 9.028

10.  A manifesto for reproducible science.

Authors:  Marcus R Munafò; Brian A Nosek; Dorothy V M Bishop; Katherine S Button; Christopher D Chambers; Nathalie Percie du Sert; Uri Simonsohn; Eric-Jan Wagenmakers; Jennifer J Ware; John P A Ioannidis
Journal:  Nat Hum Behav       Date:  2017-01-10
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