Struct RuVectorGraphAnalyzer 

pub struct RuVectorGraphAnalyzer { /* private fields */ }

Graph connectivity analysis for ruvector

Useful for:

• Detecting communities in vector similarity graphs
• Finding cut points in knowledge graphs
• Partitioning data for distributed processing

Implementations

impl RuVectorGraphAnalyzer

pub fn new(graph: Arc<DynamicGraph>) -> Self

Create analyzer for a graph

pub fn from_similarity_matrix( similarities: &[f64], num_vectors: usize, threshold: f64, ) -> Self

Build graph from similarity matrix

Creates edges between vectors with similarity above threshold

pub fn from_knn(neighbors: &[(usize, Vec<(usize, f64)>)]) -> Self

Build k-NN graph from vectors

pub fn min_cut(&mut self) -> u64

Compute minimum cut

pub fn partition(&mut self) -> Option<(Vec<VertexId>, Vec<VertexId>)>

Get partition (two sides of minimum cut)

pub fn is_well_connected(&mut self, threshold: u64) -> bool

Check if graph is well-connected (min cut above threshold)

pub fn find_bridges(&self) -> Vec<EdgeId>

Find bridge edges (edges whose removal disconnects graph)

pub fn invalidate_cache(&mut self)

Invalidate cache after graph modification

pub fn add_edge( &mut self, u: VertexId, v: VertexId, weight: Weight, ) -> Result<EdgeId>

Add edge and invalidate cache

pub fn remove_edge(&mut self, u: VertexId, v: VertexId) -> Result<()>

Remove edge and invalidate cache