  We develop tools for explicitly constructing categories enriched over
generating data and that compose via ordinary scalar and matrix arithmetic
arithmetic operations. We characterize meaningful size maps, weightings, and
magnitude that reveal features analogous to outliers that these same notions
have previously been shown to reveal in the context of metric spaces.
Throughout, we provide examples of such "outlier detection" relevant to the
analysis of computer programs, neural networks, cyber-physical systems, and
networks of communications channels.
