YODA

A small set of data analysis classes for MC event generator validation analyses

YODA is a small set of data analysis (specifically histogramming) classes being developed by MCnet members as a lightweight common system for MC event generator validation analyses. A few key features of YODA are as follows: * Storage of all information needed for statistically correct run combination and reweighting up to second-order correlations (e.g. variances, std devs, etc.) not just in the number of entries in a bin, but also the correlations of that with the x and y fill values. * Separation of statistics and data handling from presentation. YODA is primarily a library for doing the data part correctly: while we love really high quality data presentation, that's a separate goal. * A sensible class hierarchy for histogramming, recognising that a histogram contains details of fill history beyond the pure visual height of a bin, and that just counting weights, or binning arbitrary types on an axis are valuable operations. * Flexible data format support, including a new text-based, compact, and human-readable YODA format. * Proper and convenience treatment of "details" like irregular bin widths, gaps in contiguous binning, and overflows/underflows/etc. (incuding how they impact normalisation and calculation of histo- wide stat quantities) * Carefully designed programming interfaces in C++ and Python. We are very welcoming of feedback and design evolution, too!