Comments (1)
Sounds good to me 👍
Also, looking at this now, id_to_key
could just be a list or Sequence or whatever since the keys will always be 0 to N-1. This requires a sort, but will be more memory efficient. What do you think?
We also need to update so tests pass with NetworkX 3.3, so don't expect CI to pass right now. My bad for being slow--I'm in the middle of big life changes. The change I know we need to make is to allow conversion from ga.Graph
to nx.Graph
to be able to be structure-only. This means graphblas-algorithms graphs need to know the edge property, and allow the edge property to be None and all values present in the adjacency matrix should be 1.
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Related Issues (15)
- Automated testing to compare with networkx HOT 1
- COMMUNITY: Regular GraphBLAS Algorithms community conference calls (Open to all)
- Alternative for square counting (for square clustering)
- Improving onboarding and enabling contributions HOT 2
- multi-property graphs and handling of "weight" parameter
- Update README
- Raw vs Wrapped objects
- Add `graph-tool` backend to `scripts/bench.py`
- Add `igraph` backend to `scripts/bench.py` HOT 1
- Logo for `graphblas-algorithms` HOT 3
- square_clustering output using networkx api HOT 14
- `NodeMap` and other results need better reprs
- Redo/refactor calculations and caching of properties such as degrees
- Degree Centrality Calculation Differs From Networkx HOT 1
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