Reference guide

• Network models
  • Operations on multilayer networks
    • Class MLNetworkActor
    • Class MultilayerNetwork
    • Class MultilayerNetworkTorch
  • Operations on temporal networks
    • Class TemporalNetwork
• Collection of networks
  • Networks shipped with the library
    • get_toy_network_cim()
    • get_toy_network_piotr()
    • get_l2_course_net()
  • Generators of artificial networks
    • MultilayerERGenerator
    • MultilayerPAGenerator
    • generate()
• Spreading models
  • Base structures for concrete models
    • BaseModel
    • CompartmentalGraph
    • NetworkUpdateBuffer
  • Concrete propagation models
    • DSAAModel
    • MLTModel
    • MICModel
    • TemporalNetworkEpistemologyModel
• Seed selection classes for propagation models
  • Base structures for concrete seed selectors
    • BaseSeedSelector
  • Concrete seed selectors
    • BetweennessSelector
    • CBIMSeedselector
    • CIMSeedSelector
    • ClosenessSelector
    • DegreeCentralityDiscountSelector
    • DriverActorSelector
    • KatzSelector
    • KPPShellSeedSelector
    • KShellMLNSeedSelector
    • KShellSeedSelector
    • MockingActorSelector
    • NeighbourhoodSizeDiscountSelector
    • PageRankMLNSeedSelector
    • PageRankSeedSelector
    • RandomSeedSelector
    • VoteRankMLNSeedSelector
    • VoteRankSeedSelector
• Minimal Dominating Set
  • Methods for obtaining the MDS
    • get_mds_greedy()
    • get_mds_locimpr()
• Performing experiments
  • Simulator
    • Simulator.__init__()
    • Simulator.perform_propagation()
  • Logger
    • Logger.__init__()
    • Logger.add_global_stat()
    • Logger.add_local_stat()
    • Logger.convert_logs()
    • Logger.get_aggragated_logs()
    • Logger.get_detailed_logs()
    • Logger.plot()
    • Logger.report()
• Auxiliary methods
  • set_rng_seed()
  • compute_area()
  • compute_gain()