API reference

Basic concepts and classes

• Helper types
• NetworkGenerator: Generate instances from a class of random networks
  • NetworkGenerator
  • Defining the class of network
  • Single instance generation
  • Multiple instance generation (iteration)
• Process: Base class for network processes
  • Process
  • Setup and initialisation
  • Process hierarchy
  • Getting ready to run
  • Accessing and evolving the network
  • Loci
  • Events
  • Event distributions
  • Identifiers for instances, runs, and state
  • Containment
• Locus: Loci of disease dynamics
  • Locus
  • Handlers
  • Locus sub-classes
• NetworkExperiment: An experiment over a network
  • NetworkExperiment
  • In use
• Dynamics: Process dynamics over networks
  • Dynamics
  • In use
  • Attributes
  • Configuring the simulation
  • Running the experiment
  • Loci
  • Stochastic event distributions
  • Posted events
  • Event taps
• CompartmentedModel: Compartmented models of disease
  • CompartmentedModel
  • Model state variables
  • Model setup
  • Building and querying the model
  • Evolving the network
  • Generating results

Dynamics: How processes are simulated

• SynchronousDynamics: Synchronous process dynamics
  • SynchronousDynamics
  • Extra metadata
  • Running a dynamics
• StochasticDynamics: Stochastic (Gillespie) process dynamics
  • StochasticDynamics
  • Running a dynamics

Reference epidemic disease processes

• SIR: The SIR process
  • SIR
  • Dynamical states
  • Parameters
  • Loci
  • Building the model
  • Event methods
• SIS: The SIS process
  • SIS
  • Dynamical states
  • Parameters
  • Loci
  • Building the model
  • Event methods
• SEIR: The SEIR process
  • SEIR
  • Dynamical states
  • Parameters
  • Loci
  • Building the model
  • Event methods

Disease process variants

• SIR_FixedRecovery: SIR with a fixed recovery interval
  • SIR_FixedRecovery
  • Additional parameters and node attributes
  • Building the model
  • Events
• SIR_VariableInfection: SIR with per-edge infectivity
  • SIR_VariableInfection
  • Different parameters and additional node attributes
  • Building the model
  • The event distribution
• SIS_FixedRecovery: SIS with a fixed recovery interval
  • SIS_FixedRecovery
  • Additional parameters and node attributes
  • Building the model
  • Setup and events
  • Events
• SIRS: The SIRS process
  • SIRS
  • Parameters
  • Building the model
  • Event methods

Other processes

• AddDelete: The addition-deletion process
  • AddDelete
  • Parameters
  • Loci
  • Building the model
  • Evolving the network
  • Events
• PulseCoupledOscillator: The canonical synchronisation process
  • PulseCoupledOscillator
  • Parameters
  • Results
  • State variables
  • Core parts of the oscillator process
  • Setup and initialisation
  • Events
  • Managing state and phase
  • Tuning parameters
• Percolate: Perform bond percolation
  • Percolate
  • Using percolation
  • Percolation
  • Actions
  • Building
• Shuffle processes: Degree-preserving rewirings of networks
  • ShuffleK: Degree-preserving rewiring
• Opinion: An opinion dynamics process
  • Opinion
  • Dynamical states
  • Parameters
  • Loci
  • Building the model
  • Event methods
  • Running the model
• SIvR: SIR with vaccination
  • SIvR
  • Parameters
  • Loci
  • Helper method
  • Building the model
  • Event methods
• Vaccinate: A vaccination process
  • Vaccinate
  • Parameters
  • Building the process
  • Event methods

Analysis processes

• Monitor: A process to monitor other processes
  • Monitor
  • Parameters
  • Results
  • Building the process
  • Events
• NetworkStatistics: A process to collect summary statistics
  • NetworkStatistics
  • Results
  • Building the process

Process combinators

• ProcessSequence: A process built from other processes
  • ProcessSequence
  • Building the process
  • Equilibrium and termination
  • Anonymous and non-anonymous sequences

Other experiments

• Bond and site percolation
  • The Newman-Ziff algorithm
  • Results
  • Bond percolation
  • Site percolation
  • Events

Network generators

• Standard network generators
  • FixedNetwork: A single example network
  • ERNetwork: Random networks with Poisson-distributed node degrees
  • BANetwork: Random networks with powerlaw-distributed node degrees
  • PLCNetwork: Random networks with powerlaw-distributed node degrees and an exponential cutoff
• CorePeripheryNetwork: A core-periphery network generator
  • CorePeripheryNetwork
  • Experimental parameters
  • Generator methods
  • Accessing the core and periphery
• ModularNetwork: A modular ER network generator
  • ModularNetwork
  • Experimental parameters
  • Generator methods
  • Accessing the core and satellites

Generating functions

• Generating functions
  • Importing the library
  • Construction
  • In use
• Standard generating functions
  • gf_er()
  • gf_powerlaw()
  • gf_ba()
  • gf_plc()

Supporting code

• Random number generation
• DrawSet: A set with an efficient random draw
  • DrawSet
  • The set interface
  • Random drawing