Rigorous Data Processing and Automatic Documentation of SRF Cold Tests

Performance curves for SRF cavities are derived from primary quantities which are processed by software. Commonly, the mathematical implementation of this analysis is hidden in software such as Excel or LabVIEW, making it difficult to verify or to trace, while text-based programming like Python and MATLAB require some programming skills for review and use. As part of an initiative to consolidate and standardise SRF data analysis tools, we present a Python program converting a module containing the collection of all commonly used functions into a \LaTeX (PDF) document carrying all features of the implementation and allowing for a review by SRF experts, not programmers. The resulting document is the reference for non-experts, beginners and test stand operators. The module is imported in any subsequent processing and analysis steps like the symbolic analysis of the measurement uncertainties or the study of sensitivities. As an additional layer of protection the functions can be further wrapped including assertions, type and sanity checks. This process maximises function reuse, reduces the risk of human errors and guarantees automatically validated and documented cold test results.