reductus: A Stateless Python Data-Reduction Service with a Browser Frontend

Published: October 01, 2018

Author(s)

Brian B. Maranville, William D. Ratcliff, Paul Kienzle

Abstract

The online data reduction service reductus transforms measurements in experimental science from laboratory coordinates into physically meaningful quantities with accurate estimation of uncertainties based on instrumental settings and properties. This reduction process is based on a few well-known transformations, but flexibility in the application of the transforms and algorithms supports flexibility in experiment design, supporting a broader range of measurements than a rigid reduction scheme for data. The user interface allows easy construction of arbitrary pipelines from well-known data transforms using a visual dataflow diagram. Source data is drawn from a networked, open data repository. The Python backend uses intelligent caching to store intermediate results of calculations for a highly responsive user experience. The reference implementation allows immediate reduction of measurements as they are recorded for the three neutron reflecometry instruments at the NIST Center for Neutron Research (NCNR),
Citation: Journal of Applied Crystallography
Volume: 51
Issue: 5
Pub Type: Journals

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Created October 01, 2018, Updated November 19, 2018