Closed redeboer closed 3 years ago
@spflueger This is related to #40, as the recipe file contains a selection of the particle list that forms the starting point for the expertsystem.
Since the internals of the expertsystem only functions if the input particle info comes in the form of dict
s that assume our old XML format (those dict
s are used to populate the edges of the graph), I plan to 'enclose' the expertsystem input (namely a particle list) and output (a recipe file) in the form of data structures that can load and dump to those XML-formatted dict
s.
A series of PRs will follow, starting with a ParticleCollection
containing Particle
instances that can be built from both YAML and XML and then dumps its info into a nested dict
. Later on, this internal nested dict
structure can then slowly be replaced Particle
instances.
Intended structure/workflow:
So the idea is that all recipe I/O and the recipe structure is pinned down in the form of classes. Then the expertsystem becomes an actual dependency of tensorwaves and there's no need to define dict
to TF object conversions each time the recipe file structure changes.
Closed by #454
Perhaps this issue is even more general: both
expertsystem
andtensorwaves
(perhaps evenpycompwa
) need to agree on the syntax on the recipe, so it's natural to put some sort of recipe module into the expert system._Originally posted by @redeboer in https://github.com/ComPWA/tensorwaves/pull/60/review_comment/create_