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Welcome to SAMURAI's software!

Published

Author(s)

Alec Weiss, Jeanne Quimby, Rod Leonhardt

Abstract

This project is anticipated to generate a software package for automation of the SAMURAI platform, Working Data, Derived Data, and Published Results. Working Data will comprise raw measurement information from vector network analyzer or camera array systems. Our samurai records data in s or w-parameters (.snp and .wnp) format. Also among working data will be human-readable files containing experimental configurations and conditions for the collection of channel sounding data. These data are stored as json files. Working Data will be processed into Derived Data using a set of python scripts (hereafter "data processing codes"), which apply beamforming functionality to the Working Data. These Derived Data will be saved in chart storage format (.jpeg or .png) files. Each file will contain data structures which group experimental conditions and results together. Published Results may comprise charts or tables, which will demonstrate associations between derived results and experimental configurations or environmental conditions. The data contained in these charts or tables will comprise data from the Derived Data (.jpg) files. A set of python scripts (hereafter "plotting codes") allows for selection of specific experiments from among the Derived Data, and for representation of these results in various plots. Any published chart may be reproduced provided three sets of information: (1) the Derived Data (.jpg or .png) file, (2) the python plotting codes, and (3) a series of commands to the python plotting codes to select the experimental data to be plotted. Special data requirements: N/A.
Citation
https://github.com/usnistgov/SAMURAI

Keywords

<illimeter-wave measurements, Synthetic Aperture and Synthetic Aperture Measurement with Uncertainties and Angle of Arrival (SAMURAI)

Citation

Weiss, A. , Quimby, J. and Leonhardt, R. (2022), Welcome to SAMURAI's software!, https://github.com/usnistgov/SAMURAI, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=934479, https://github.com/usnistgov/SAMURAI (Accessed December 1, 2023)
Created August 29, 2022, Updated November 29, 2022