The policy system provides a way for users to ensure that they get a network with certain traits. For example being sure that the network they get has all of the proton proton reactions in its base reaction set. This is an extensible system which is intended to be used by researchers to build various determanistic network policies to make network results more reproducable
previousl the sparsity calculations for the jacobian matrix were completly broken. The method subgraph_sparsity was returning that all derivities were only depenednt on temperature and density. It should have been reporting that they also depended on some of the abundances. This was resolved by switching to a different structural sparsity engine (for_jac_sparsity). This bug had turned the solver into a fixed point iteration solver which failed for the stiff system we have. Now that it is resolved the solver can once again evolved over Gyr timescales.
essentially all callers can now inform the graph engine about which species they hold active and graph engine then uses those to define a sparsity pattern and only calculate the jacobian along that sparsity pattern
bigs were introduced by the interface change from accepting raw molar abundance vectors to using the composition vector. This commit resolves many of these, including preformant ways to report that a species is not present in the composition and unified index lookups using composition object tooling.
BREAKING CHANGE:
Major weak rate progress which includes: A refactor of many of the public interfaces for GridFire Engines to use composition objects as opposed to raw abundance vectors. This helps prevent index mismatch errors. Further, the weak reaction class has been expanded with the majority of an implimentation, including an atomic_base derived class to allow for proper auto diff tracking of the interpolated table results. Some additional changes are that the version of fourdst and libcomposition have been bumped to versions with smarter caching of intermediate vectors and a few bug fixes.
