mirror of
https://github.com/ruvnet/RuVector.git
synced 2026-05-26 07:44:05 +00:00
d35e5906ab
Fixes across attention mechanisms, SONA engine, and examples: Attention mechanisms: - hierarchical_lorentz: Use dag.node_count(), dag.children() API - parallel_branch: Replace get_children() with children() - temporal_btsp: Fix node.estimated_cost access, remove selectivity - cache: Use dag.node_ids() and dag.children() for iteration - mincut_gated: Fix return type to match DagAttentionMechanism trait - selector: Update tests to use OperatorNode::new() SONA/QuDAG: - sona/engine: Add deprecated Scan/Join match arms - ml_kem: Fix unused parameter warnings - ml_dsa: Fix unused parameter warnings Examples: - basic_usage: Use dag.children() instead of get_children() - learning_workflow: Fix HnswScan/Sort field names, trajectory access - attention_demo: Import DagAttentionMechanism trait - attention_selection: Fix CausalConeConfig field names - self_healing: Remove non-existent result fields - federated_coherence: Add parentheses for comparison expression Cargo.toml: - Register all exotic examples with explicit paths All 12 examples now build and run successfully.
73 lines
2.1 KiB
Rust
73 lines
2.1 KiB
Rust
//! Basic usage example for Neural DAG Learning
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use ruvector_dag::dag::{QueryDag, OperatorNode, OperatorType};
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fn main() {
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println!("=== Neural DAG Learning - Basic Usage ===\n");
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// Create a new DAG
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let mut dag = QueryDag::new();
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// Add nodes representing query operators
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println!("Building query DAG...");
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let scan = dag.add_node(OperatorNode::seq_scan(0, "users"));
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println!(" Added SeqScan on 'users' (id: {})", scan);
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let filter = dag.add_node(OperatorNode::filter(1, "age > 18"));
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println!(" Added Filter 'age > 18' (id: {})", filter);
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let sort = dag.add_node(OperatorNode::sort(2, vec!["name".to_string()]));
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println!(" Added Sort by 'name' (id: {})", sort);
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let limit = dag.add_node(OperatorNode::limit(3, 10));
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println!(" Added Limit 10 (id: {})", limit);
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let result = dag.add_node(OperatorNode::new(4, OperatorType::Result));
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println!(" Added Result (id: {})", result);
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// Connect nodes
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dag.add_edge(scan, filter).unwrap();
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dag.add_edge(filter, sort).unwrap();
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dag.add_edge(sort, limit).unwrap();
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dag.add_edge(limit, result).unwrap();
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println!("\nDAG Statistics:");
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println!(" Nodes: {}", dag.node_count());
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println!(" Edges: {}", dag.edge_count());
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// Compute topological order
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let order = dag.topological_sort().unwrap();
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println!("\nTopological Order: {:?}", order);
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// Compute depths
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let depths = dag.compute_depths();
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println!("\nNode Depths:");
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for (id, depth) in &depths {
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println!(" Node {}: depth {}", id, depth);
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}
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// Get children
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println!("\nNode Children:");
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for node_id in 0..5 {
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let children = dag.children(node_id);
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println!(" Node {}: {:?}", node_id, children);
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}
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// Demonstrate iterators
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println!("\nDFS Traversal:");
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for (i, node_id) in dag.dfs_iter(scan).enumerate() {
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if i < 10 {
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println!(" Visit: {}", node_id);
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}
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}
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println!("\nBFS Traversal:");
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for (i, node_id) in dag.bfs_iter(scan).enumerate() {
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if i < 10 {
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println!(" Visit: {}", node_id);
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}
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}
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println!("\n=== Example Complete ===");
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}
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