Conditional Graph Factorization is a submodule of the SimianQuant code generator that generalizes the concept of *calibration*. Given a sequence of partitions of the domain, it factorizes the full computational graph into a sequence of subgraphs conditional on the respective partition and the inferred codomain of the previous subgraph. This article illustrates the principle and some applications.

The SimianQuant library provides a Fluent API on top of its symbolic engine to implement functions with feedback. Technical indicators are a classic example of the usage of this pattern. This article presents the results of benchmarking the generated implementations (in C++) of common indicators.

The sequence of operations that convert input to output can be visualized as a graph. Graph compression is the family name for a suite of SimianQuant algorithms that rewrite the computational graph to reduce the time and/or memory required.