@inproceedings{97119f1b61df49cda200bc5e331a3271,
title = "PyXRF: Python-based X-ray fluorescence analysis package",
abstract = "We developed a python-based fluorescence analysis package (PyXRF) at the National Synchrotron Light Source II (NSLS-II) for the X-ray fluorescence-microscopy beamlines, including Hard X-ray Nanoprobe (HXN), and Submicron Resolution X-ray Spectroscopy (SRX). This package contains a high-level fitting engine, a comprehensive commandline/ GUI design, rigorous physics calculations, and a visualization interface. PyXRF offers a method of automatically finding elements, so that users do not need to spend extra time selecting elements manually. Moreover, PyXRF provides a convenient and interactive way of adjusting fitting parameters with physical constraints. This will help us perform quantitative analysis, and find an appropriate initial guess for fitting. Furthermore, we also create an advanced mode for expert users to construct their own fitting strategies with a full control of each fitting parameter. PyXRF runs single-pixel fitting at a fast speed, which opens up the possibilities of viewing the results of fitting in real time during experiments. A convenient I/O interface was designed to obtain data directly from NSLS-II's experimental database. PyXRF is under open-source development and designed to be an integral part of NSLS-II's scientific computation library.",
keywords = "Quantitative analysis, X-ray fluorescence",
author = "Li Li and Hanfei Yan and Wei Xu and Dantong Yu and Annie Heroux and Lee, {Wah Keat} and Campbell, {Stuart I.} and Chu, {Yong S.}",
note = "Publisher Copyright: {\textcopyright} 2017 SPIE.; X-Ray Nanoimaging: Instruments and Methods III 2017 ; Conference date: 07-08-2017 Through 08-08-2017",
year = "2017",
doi = "10.1117/12.2272585",
language = "English (US)",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Andrea Somogyi and Barry Lai",
booktitle = "X-Ray Nanoimaging",
address = "United States",
}