qbiocode.apps.quvine.data.random_graphs_extended module#

Extended Random Graph Generator for QuVINE#

Combines original QuVINE random graph generators with five new synthetic graph families especially useful for studying quantum-vs-classical random-walk embedding:

Original generators:

  • Erdős-Rényi, Barabási-Albert, Watts-Strogatz, Powerlaw Cluster

  • Stochastic Block Model, Random Geometric, Modular, Hierarchical

  • Core-Periphery, Bipartite Random

New extended generators:

  1. Random regular / expander-like graphs

  2. Heterophilic / disassortative stochastic block models

  3. Degree-corrected stochastic block models

  4. Grid / torus lattices

  5. Configuration-model graphs with power-law or log-normal degrees

Design notes#

  • New generators favor target average degree parameterizations for fair comparison

  • Graphs can optionally be made connected by adding minimal bridge edges

  • Metadata is returned with every generated graph for downstream analysis

  • All generators maintain backward compatibility with existing QuVINE code

Dependencies: networkx, numpy

__all__: add_hub_nodes, generate_barabasi_albert, generate_bipartite_random, generate_core_periphery, generate_erdos_renyi, generate_graph_with_seeds_and_targets, generate_hierarchical_network, generate_modular_network, generate_powerlaw_cluster, generate_random_geometric, generate_stochastic_block_model, generate_watts_strogatz, get_graph_statistics