d803bfe2b1
git-subtree-dir: vendor/ruvector git-subtree-split: b64c21726f2bb37286d9ee36a7869fef60cc6900
76 lines
2.1 KiB
Markdown
76 lines
2.1 KiB
Markdown
# exo-hypergraph
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Hypergraph substrate for higher-order relational reasoning with persistent
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homology and sheaf theory. Enables cognitive representations that go beyond
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pairwise edges to capture n-ary relationships natively.
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## Features
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- **Hyperedge storage** -- first-class support for edges that connect
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arbitrary sets of nodes, stored in a compressed sparse format.
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- **Sheaf sections** -- attach typed data (sections) to nodes and edges
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with consistency conditions enforced by sheaf restriction maps.
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- **Sparse persistent homology (PPR-based O(n/epsilon))** -- computes
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topological features efficiently using personalised PageRank
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sparsification.
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- **Betti number computation** -- extracts Betti-0 (connected components),
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Betti-1 (loops), and higher Betti numbers to summarise structural
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topology.
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## Quick Start
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Add the dependency to your `Cargo.toml`:
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```toml
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[dependencies]
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exo-hypergraph = "0.1"
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```
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Basic usage:
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```rust
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use exo_hypergraph::{HypergraphSubstrate, HypergraphConfig};
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use exo_core::{EntityId, Relation, RelationType};
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let config = HypergraphConfig::default();
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let mut hg = HypergraphSubstrate::new(config);
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let e1 = EntityId::new();
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let e2 = EntityId::new();
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let e3 = EntityId::new();
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// Create a 3-way hyperedge
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let relation = Relation {
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relation_type: RelationType::new("collaboration"),
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properties: serde_json::json!({"project": "EXO-AI"}),
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};
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hg.create_hyperedge(&[e1, e2, e3], &relation).unwrap();
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// Compute topological invariants
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let betti = hg.betti_numbers(2);
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println!("Betti numbers: {:?}", betti);
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```
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## Crate Layout
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| Module | Purpose |
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|-------------|--------------------------------------------|
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| `graph` | Core hypergraph data structure |
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| `sheaf` | Sheaf sections and restriction maps |
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| `homology` | Sparse persistent homology pipeline |
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| `betti` | Betti number extraction and summarisation |
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## Requirements
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- Rust 1.78+
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- Depends on `exo-core`
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## Links
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- [GitHub](https://github.com/ruvnet/ruvector)
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- [EXO-AI Documentation](https://github.com/ruvnet/ruvector/tree/main/examples/exo-ai-2025)
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## License
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MIT OR Apache-2.0
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