GridFire failed to compile on gcc and gnu stdlibc++ this has been
resolved. Further, the boost dependency has been removed since we no
longer use boost at all. This should dramatically simplify installation.
Finally we have added some build system checks to ensure that the
correct version of a C++ and fortran compiler are present on the system
Python bindings have now been brought back up to feature pairity with
C++. Further, stubs have been added for all python features so that code
completion will work
Previously QSE solving was done using Eigen. While this worked we were
limited in the ability to use previous iterations to speed up later
steps. We have switched to KINSOL, from SUNDIALS, for linear solving.
This has drastically speed up the process of solving for QSE abundances,
primarily because the jacobian matrix does not need to be generated
every single time time a QSE abundance is requested.
one major issue was that QSE solving was only running at each partition. This was creating effectivley infinite sources of partitioned species. Now we partition when engine updates are triggered, however, solveQSEAbundance is called every timestep. This has major performance implications and so has required a lot of optimization to make it even somewhat viable. For now construction is much slower. Time per iteration is still slower than it was before; however, it is tractable. There is also currently too much stiffness in the network. This is likeley a bug that was introduced in this refactoring which will be addressed soon.
This entailed a major rewrite of the composition handling from each engine and engine view along with the solver and primer. The intent here is to let Compositions be constructed from the same extensive property which the solver tracks internally. This addressed C0 discontinuity issues in the tracked molar abundances of species which were introduced by repeadidly swaping from molar abundance space to mass fraction space and back. This also allowed for a simplification of the primeNetwork method. Specifically the mass borrowing system was dramatically simplified as molar abundances are extensive.
Mirroring what was done in fourdst (see fourdst/tree/v0.8.5) we have added a temporary patch to let python bindings work on mac while the meson-python folks resolve the duplicate rpath issue in the shared object file
This fourdst version bump brings the libcomposition v1.9.0 which brings the abstract base class CompositionAbstract. This will allow us to impliment overrides which return specific molarAbundances skirting around Composition internal checks. This is for the purpose of allowing unrestricted molar flow when ccalculating the destruction rate constant for particular species.
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.
Fized stoichiometry matrix initialization, added penames to reablib reactions, began work on LogicalReaction to sum the contributions of different fitting functions provided by reaclib
