Refactor populate features base #113
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gregmedlock
approved these changes
Sep 2, 2025
| rxn_vals[mid] = rxn_attrs[reaction] | ||
| else: | ||
| # Use default bounds if reaction missing from model | ||
| rxn_vals[mid] = {'lower_bound': 0, 'upper_bound': 0} # TODO remark: could use MISSING_ATTRIBUTE_DEFAULT instead |
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@jgilis I think it's fine to keep your implementation as-is; the global REACTION_ATTRIBUTES and MISSING_ATTRIBUTE_DEFAULT were intended for generalizability anticipating implementation of alternative GPRs for the same reaction across ensemble members. The rest of Medusa doesn't support that yet, so I'm OK with these changes focusing the current implementation more towards reaction presence+directionality. Adding support for alternative GPRs will require some other refactoring and addition of utility functions for simulation methods that use GPRs anyway.
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Merging this PR will update the
ensemble.pyfunction, more specifically, the_populate_features_basesubroutine. This feature speeds up generating an ensemble from an existing list of GEMs considerably, e.g., for my personal project with a list of 150 GEMs, the runtime reduces from 1min30s to 2s. The speed gain can be largely attributed to pre-caching the model reaction attributes in dictionaries, thus avoiding repeatedgetattrcalls.