Crate scirs2_graph 

Graph processing module for SciRS2

This module provides graph algorithms and data structures for scientific computing and machine learning applications.

Features

• Basic graph representations and operations
• Graph algorithms (traversal, shortest paths, etc.)
• Network analysis (centrality measures, community detection)
• Spectral graph theory
• Support for graph neural networks

API Stability and Versioning

scirs2-graph follows strict semantic versioning with clear stability guarantees:

Stability Classifications

• ✅ Stable: Core APIs guaranteed until next major version (2.0.0)
• ⚠️ Experimental: May change in minor versions, marked with #[cfg(feature = "experimental")]
• 📋 Deprecated: Will be removed in next major version, use alternatives

Version Guarantees

• MAJOR (1.x.x → 2.x.x): Breaking changes to stable APIs allowed
• MINOR (1.0.x → 1.1.x): New features, deprecations only (no breaks to stable APIs)
• PATCH (1.0.0 → 1.0.1): Bug fixes only, no API changes

Stable Core APIs (v0.1.0-beta.1+)

• Graph data structures (Graph, DiGraph, MultiGraph)
• Basic algorithms (traversal, shortest paths, connectivity)
• Graph generators and I/O operations
• Community detection with _result suffix functions
• Error handling and core types

Re-exports

pub use algorithms::articulation_points;

pub use algorithms::astar_search;

pub use algorithms::astar_search_digraph;

pub use algorithms::betweenness_centrality;

pub use algorithms::bidirectional_search;

pub use algorithms::bidirectional_search_digraph;

pub use algorithms::breadth_first_search;

pub use algorithms::breadth_first_search_digraph;

pub use algorithms::bridges;

pub use algorithms::center_nodes;

pub use algorithms::closeness_centrality;

pub use algorithms::complement;

pub use algorithms::connected_components;

pub use algorithms::cosine_similarity;

pub use algorithms::depth_first_search;

pub use algorithms::depth_first_search_digraph;

pub use algorithms::diameter;

pub use algorithms::dijkstra_path;

pub use algorithms::dinic_max_flow;

pub use algorithms::edge_subgraph;

pub use algorithms::eigenvector_centrality;

pub use algorithms::eulerian_type;

pub use algorithms::floyd_warshall;

pub use algorithms::floyd_warshall_digraph;

pub use algorithms::fluid_communities_result;

pub use algorithms::greedy_coloring;

pub use algorithms::greedy_modularity_optimization_result;

pub use algorithms::hierarchical_communities_result;

pub use algorithms::infomap_communities;

pub use algorithms::is_bipartite;

pub use algorithms::jaccard_similarity;

pub use algorithms::k_core_decomposition;

pub use algorithms::k_shortest_paths;

pub use algorithms::label_propagation_result;

pub use algorithms::line_digraph;

pub use algorithms::line_graph;

pub use algorithms::louvain_communities_result;

pub use algorithms::maximal_matching;

pub use algorithms::maximum_bipartite_matching;

pub use algorithms::maximum_cardinality_matching;

pub use algorithms::minimum_cut;

pub use algorithms::minimum_spanning_tree;

pub use algorithms::minimum_weight_bipartite_matching;

pub use algorithms::modularity;

pub use algorithms::modularity;

pub use algorithms::modularity_optimization_result;

pub use algorithms::pagerank;

pub use algorithms::personalized_pagerank;

pub use algorithms::push_relabel_max_flow;

pub use algorithms::radius;

pub use algorithms::random_walk;

pub use algorithms::random_walk;

pub use algorithms::stable_marriage;

pub use algorithms::strongly_connected_components;

pub use algorithms::subdigraph;

pub use algorithms::subgraph;

pub use algorithms::tensor_product;

pub use algorithms::topological_sort;

pub use algorithms::transition_matrix;

pub use algorithms::weight_filtered_subgraph;

pub use algorithms::AStarResult;

pub use algorithms::BipartiteMatching;

pub use algorithms::BipartiteResult;

pub use algorithms::CommunityResult;

pub use algorithms::CommunityStructure;

pub use algorithms::EulerianType;

pub use algorithms::GraphColoring;

pub use algorithms::InfomapResult;

pub use algorithms::MaximumMatching;

pub use algorithms::MotifType;

pub use algorithms::are_graphs_isomorphic;

pub use algorithms::are_graphs_isomorphic_enhanced;

pub use algorithms::cartesian_product;

pub use algorithms::chromatic_number;

pub use algorithms::find_isomorphism;

pub use algorithms::find_isomorphism_vf2;

pub use algorithms::find_motifs;

pub use algorithms::find_subgraph_matches;

pub use algorithms::graph_edit_distance;

pub use algorithms::has_hamiltonian_circuit;

pub use algorithms::has_hamiltonian_path;

pub use base::BipartiteGraph;

pub use base::DiGraph;

pub use base::Edge;

pub use base::EdgeWeight;

pub use base::Graph;

pub use base::Hyperedge;

pub use base::Hypergraph;

pub use base::MultiDiGraph;

pub use base::MultiGraph;

pub use base::Node;

pub use error::ErrorContext;

pub use error::GraphError;

pub use error::Result;

pub use generators::barabasi_albert_graph;

pub use generators::complete_graph;

pub use generators::cycle_graph;

pub use generators::erdos_renyi_graph;

pub use generators::grid_2d_graph;

pub use generators::grid_3d_graph;

pub use generators::hexagonal_lattice_graph;

pub use generators::path_graph;

pub use generators::planted_partition_model;

pub use generators::star_graph;

pub use generators::stochastic_block_model;

pub use generators::triangular_lattice_graph;

pub use generators::two_community_sbm;

pub use generators::watts_strogatz_graph;

pub use measures::centrality;

pub use measures::clustering_coefficient;

pub use measures::graph_density;

pub use measures::hits_algorithm;

pub use measures::katz_centrality;

pub use measures::katz_centrality_digraph;

pub use measures::pagerank_centrality;

pub use measures::pagerank_centrality_digraph;

pub use measures::CentralityType;

pub use measures::HitsScores;

pub use spectral::laplacian;

pub use spectral::normalized_cut;

pub use spectral::spectral_radius;

pub use weighted::MultiWeight;

pub use weighted::NormalizationMethod;

pub use weighted::WeightStatistics;

pub use weighted::WeightTransform;

pub use weighted::WeightedOps;

pub use attributes::AttributeSummary;

pub use attributes::AttributeValue;

pub use attributes::AttributeView;

pub use attributes::AttributedDiGraph;

pub use attributes::AttributedGraph;

pub use attributes::Attributes;

pub use memory::suggest_optimizations;

pub use memory::BitPackedGraph;

pub use memory::CSRGraph;

pub use memory::CompressedAdjacencyList;

pub use memory::FragmentationReport;

pub use memory::HybridGraph;

pub use memory::MemoryProfiler;

pub use memory::MemorySample;

pub use memory::MemoryStats;

pub use memory::OptimizationSuggestions;

pub use memory::OptimizedGraphBuilder;

pub use performance::LargeGraphIterator;

pub use performance::LargeGraphOps;

pub use performance::MemoryMetrics;

pub use performance::ParallelConfig;

pub use performance::PerformanceMonitor;

pub use performance::PerformanceReport;

pub use performance::StreamingGraphProcessor;

pub use embeddings::DeepWalk;

pub use embeddings::DeepWalkConfig;

pub use embeddings::Embedding;

pub use embeddings::EmbeddingModel;

pub use embeddings::Node2Vec;

pub use embeddings::Node2VecConfig;

pub use embeddings::RandomWalk;

pub use embeddings::RandomWalkGenerator;

pub use layout::circular_layout;

pub use layout::hierarchical_layout;

pub use layout::spectral_layout;

pub use layout::spring_layout;

pub use layout::Position;

pub use temporal::temporal_betweenness_centrality;

pub use temporal::temporal_reachability;

pub use temporal::TemporalGraph;

pub use temporal::TemporalPath;

pub use temporal::TimeInstant;

pub use temporal::TimeInterval;

pub use advanced::create_advanced_processor;

pub use advanced::execute_with_advanced;

pub use advanced::AdvancedConfig;

pub use advanced::AdvancedProcessor;

pub use advanced::AdvancedStats;

pub use advanced::AlgorithmMetrics;

pub use advanced::GPUAccelerationContext;

pub use advanced::NeuralRLAgent;

pub use advanced::NeuromorphicProcessor;

pub use graph_memory_profiler::AdvancedMemoryProfiler;

pub use graph_memory_profiler::EfficiencyAnalysis;

pub use graph_memory_profiler::MemoryProfile;

pub use graph_memory_profiler::MemoryProfilerConfig;

pub use graph_memory_profiler::MemoryStats as GraphMemoryStats;

pub use graph_memory_profiler::OptimizationOpportunity;

pub use graph_memory_profiler::OptimizationType;

pub use numerical_accuracy_validation::create_comprehensive_validation_suite;

pub use numerical_accuracy_validation::run_quick_validation;

pub use numerical_accuracy_validation::AdvancedNumericalValidator;

pub use numerical_accuracy_validation::ValidationAlgorithm;

pub use numerical_accuracy_validation::ValidationConfig;

pub use numerical_accuracy_validation::ValidationReport;

pub use numerical_accuracy_validation::ValidationResult;

pub use numerical_accuracy_validation::ValidationTolerances;

pub use io::*;

Modules

advanced

Advanced Mode Integration for Graph Processing

algorithms

Graph algorithms

attributes

Node and edge attribute system

base

Base graph structures and operations

embeddings

Graph embedding algorithms and utilities

error

Error types for the graph processing module

generators

Graph generation algorithms

graph_memory_profiler

Memory Usage Profiler for Advanced Mode

io

Input/output operations for graphs

layout

Graph layout algorithms for visualization

measures

Graph measures and metrics

memory

Memory profiling and optimization utilities for graph data structures

numerical_accuracy_validation

Numerical Accuracy Validation for Advanced Mode

performance

Performance optimizations for large graph operations

spectral

Spectral graph theory operations

temporal

Temporal graph structures and algorithms

weighted

Specialized weighted graph operations and analysis

Traits

IndexType

Trait for the unsigned integer type used for node and edge indices.