catalog
graph_generators.catalog
The curated GraphGenerator catalog: entry lookup, declared defaults, reference matrices.
What is left here is the residue that no printer should ever emit. Graph construction itself lives in :mod:tvbo.graph_generators.procedural, which resolves a generator’s typed DAG to SymPy and renders it through the printer tables in tvbo/codegen/code.py — one primitive definition per backend. This module used to carry a second, numpy-only implementation of those same primitives (sampling, reductions, linear algebra) behind a restricted eval; that table is gone, because two implementations of one vocabulary can only ever agree by coincidence, and the disagreement would show up as a network that differs between a local run and a swept one.
Functions
| Name | Description |
|---|---|
| declared_defaults | Default values from a curated entry’s parameters: interface block. |
| load_matrix | Resolve source (IRI / path / bare DB name) into a 2-D adjacency matrix. |
| run_generator | Materialise a curated generator by name from its typed procedure: DAG. |
declared_defaults
graph_generators.catalog.declared_defaults(entry)Default values from a curated entry’s parameters: interface block.
A curated entry declares each parameter (datatype, description, default) while a concrete Network supplies its value. Only the defaults cross over into evaluation — the declaration itself is an interface, not a value, and binding it as one would hand a step a {'datatype': ...} dict where it expects a number.
load_matrix
graph_generators.catalog.load_matrix(source)Resolve source (IRI / path / bare DB name) into a 2-D adjacency matrix.
run_generator
graph_generators.catalog.run_generator(name, params, seed=None)Materialise a curated generator by name from its typed procedure: DAG.
Convenience entry point for scripts and notebooks. Network._resolve goes through the same resolver, so a generator built here matches the one a recipe builds value for value.