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TY - CONF AU - Nelson, S. ED - White, Karen S. ED - Brown, Kevin A. ED - Dyer, Philip S. ED - Schaa, Volker RW TI - Developing a Toolkit for Analysis of LCLS Pump-Probe Data J2 - Proc. of ICALEPCS2019, New York, NY, USA, 05-11 October 2019 CY - New York, NY, USA T2 - International Conference on Accelerator and Large Experimental Physics Control Systems T3 - 17 LA - english AB - The data format and volume at LCLS requires significant computing expertise which not all user groups can provide. We will describe the path to and current status of a Python module that enables user groups to translate and reduce their data into a format that they can easily work with. The package is developed in Python and uses the standard LCLS data analysis framework. It encapsulates knowledge of the standard beam line components and adds convenient ways to reduce the data of larger detectors. Both an event-based (best for small event sizes) and a binned approach which is able to handle larger data as megapixel size detectors are simple to setup. MPI is used for fast turn around, enabling close to real time feedback necessary to make decisions of how to use the limited amount of beam time. Jupyter notebooks are provided to demonstrate some of the available options and can serve as a convenient quick start for fast turn around analysis. PB - JACoW Publishing CP - Geneva, Switzerland SP - 795 EP - 798 KW - experiment KW - detector KW - framework KW - photon KW - interface DA - 2020/08 PY - 2020 SN - 2226-0358 SN - 978-3-95450-209-7 DO - doi:10.18429/JACoW-ICALEPCS2019-TUCPR01 UR - https://jacow.org/icalepcs2019/papers/tucpr01.pdf ER -